JEOL USA Blog

How Does Field Ionization Work?

How Does Field Ionization Work?

Mass spectral interpretation begins with the molecular ion. Electron ionization (EI) has traditionally been the primary method for generating this species, valued for its reproducibility and extensive reference mass libraries. Yet the high-energy electrons at 70 eV used in EI often deposit excess internal energy, leading to extensive fragmentation and suppressing the molecular ion. Field ionization (FI) avoids such an outcome by eliminating collision-based ionization and instead extracting an electron using an intense electric field. Understanding how field ionization works reveals why it excels at preserving molecular ions while retaining meaningful structural information.

The Fundamental Physics: Quantum Mechanical Tunneling

Field ionization is governed by quantum mechanical principles rather than classical collision ionization processes. In a field ionization source, analyte molecules pass through an extremely strong electric field, typically on the order of 10⁷ to 10⁸ V/cm, established between a high-potential emitter and counter electrode. Under normal conditions, electrons remain bound to molecules through a potential energy barrier that exceeds the molecule’s ionization energy. The applied electric field distorts this barrier, effectively narrowing it on one side of the molecule. When the barrier becomes sufficiently thin, quantum mechanical tunneling can occur. This behavior reflects the Heisenberg Uncertainty Principle, which states that electrons are delocalized probability distributions instead of fixed, classical particles. In the presence of the distorted barrier, the quantum nature of the electron enables tunneling out of the molecule without a physical collision. Ionization therefore proceeds with minimal energy transfer, producing a molecular radical cation in a low vibrational state and largely preserving molecular structure.

Emitter Architecture and Field Concentration

Generating the electric fields required for field ionization depends as much on emitter geometry as on the voltage applied between the emitter and counter electrode. Electric field strength scales in proportion to the applied potential divided by the radius of curvature of the conducting surface, so reducing that radius sharply increases local field intensity. FI emitters are engineered specifically to leverage this relationship. A typical design employs a fine metal wire, often around 10 micrometers in diameter, coated with carbon dendritic structures commonly referred to as whiskers or micro-needles. The dendritic structures terminate in tips with nanometer-scale radii of curvature, forming regions of extreme electric field concentration. In these regions, field strengths readily reach levels required for ionization, enabling field ionization at voltages compatible with practical mass spectrometer operation.

Comparative Dynamics: Field Ionization and Other Soft Ionization Methods

Occupying a distinct position among soft ionization techniques, FI minimizes secondary chemical interactions during ion formation. Chemical ionization (CI), by contrast, relies on reagent gases and ion-molecule reactions that commonly introduce protonated species, adducts, and chemical background. Field ionization bypasses these pathways entirely, producing spectra typically dominated by the intact molecular ion and often simpler to interpret. Photoionization (PI) is another low-energy alternative, but its effectiveness depends on photon absorption cross sections that are often low for non-polar compounds. Because FI does not depend on photon absorption, it is suitable for saturated hydrocarbons and other chemically inert species. In addition, FI operates without elevated source temperatures, reducing thermal stress and extending its applicability to thermally labile compounds. Such a combination of advantages makes FI a valuable option for analyses that require molecular ion preservation and minimal chemical interference, such as petroleomics workflows and the analysis of thermally labile compounds.

Analytical Applications in Complex Characterization

Field ionization is applied when molecular ion preservation is required for reliable mass spectral interpretation and to provide intact molecular ions for the identification of unknown compounds. The ionization process transfers very little excess internal energy, limiting fragmentation at the point of ion formation and enabling the molecular ion to remain dominant in the resulting spectrum. Access to intact molecular ions under such conditions enables analytical workflows that depend on direct molecular weight determination and composition assignment to proceed without ambiguity introduced by fragmentation.
  • Saturated hydrocarbon analysis
    Linear and branched alkanes often yield weak or absent molecular ion signals in EI, limiting confident molecular weight determination. Field ionization overcomes this limitation by consistently generating intact molecular ions for non-polar hydrocarbons, supporting petroleomics workflows such as group-type and compositional analysis.
  • High-resolution mass spectrometry synergy
    Field ionization spectra retain intact molecular ions, allowing integration with high-resolution mass spectrometry. Accurate mass measurements can be applied directly to molecular ions, supporting reliable elemental composition assignments based on exact mass, even in chemically complex mixtures.
  • Oligomeric and polymer characterization
    Low- to mid-molecular-weight polymers can be characterized through FI by preserving molecular ion series with minimal fragmentation, maintaining molecular weight distributions, and enabling direct assessment of oligomer populations.

Advancing Mass Spectrometry with JEOL USA

Field ionization enables direct control over ion formation through retaining molecular ions with minimal excess internal energy. Its capabilities enable analysts to tailor ionization behavior to the chemical problem, balancing molecular ion preservation against structural information. JEOL USA implements FI within GC-MS platforms like the JMS-T2000GC AccuTOF™ GC-Alpha 2.0 Gas Chromatograph-Time-of-Flight Mass Spectrometer and AccuTOF™ GCxGC Mass Spectrometer, as well as EI and FI within a single ion source. Access to multiple ionization modes ensures analysts can select the optimal balance between fragmentation and molecular ion preservation, extending robust molecular characterization across diverse analytical challenges. Reach out to JEOL USA for more information about our FI-enabled GC-MS solutions and available method development support.

    An Introduction to FIB-SEM

    An Introduction to FIB-SEM

    The behavior of materials and biological systems is often shaped by the hidden structures that lie beneath their surfaces. A crack deep within a metal, a fault in a semiconductor device, or the architecture of a biological cell can hold insights about a sample’s structure and function that surface imaging alone cannot provide. Traditional microscopy techniques each have their place in characterizing surfaces and structures. Scanning electron microscopy (SEM) delivers detailed surface information, while transmission electron microscopy (TEM) reaches atomic resolution, although it does require ultrathin specimens. However, neither SEM nor TEM alone can easily provide subsurface or three-dimensional data. Researchers therefore have turned to focused ion beam-scanning electron microscopy (FIB-SEM), which overcomes these limitations by combining precision milling with high-resolution imaging. It has since become a well-established tool across many areas that require advanced microscopy, including materials science, semiconductors, life sciences, and energy research.

    What is FIB-SEM?

    A FIB-SEM is a dual-beam instrument that brings together:
    By combining an ion beam for material removal and an electron beam for imaging, FIB-SEM helps scientists to:
    • Examine hidden structures beneath the specimen’s surface.
    • Collect a sequence of images that can be reconstructed into a 3D model.
    • Produce ultrathin lamellae at selected locations for TEM analysis.
    • Deposit protective coatings or modify surfaces as needed.
    Rather than serving a single function, FIB-SEM unites fabrication and imaging in one system, making it uniquely versatile and a powerful tool for investigating complex structures.

    How Does FIB-SEM Work?

    The Workflow

    FIB-SEM workflows are built around a repeated cycle of milling and imaging. It typically consists of four key stages:
    1. Identify the region of interest
      The SEM is used to visualize the sample surface and locate the exact area of investigation. Researchers can zoom in on features such as defects, grain boundaries, or regions of biological tissue that require closer examination.
    2. Mill with the ion beam
      A finely focused beam of ions, usually gallium, is directed at the chosen site. With the adjustment of the beam current, operators can switch between fast, coarse milling for removing bulk material and gentle, fine milling for polishing delicate features, ensuring the resulting cross-section is clean and ready for imaging.
    3. Image with the SEM
      At this point, the SEM directs an electron beam across the newly exposed surface, generating contrast that highlights the sample's surface structures and microstructural features.
    4. Repeat the cycle
      Alternating between milling and imaging allows researchers to cut through the sample layer by layer. The set of acquired scans can then be assembled into a 3D reconstruction or used to prepare an ultrathin lamella for TEM analysis.

    The Components Behind the Workflow

    Several key components are required to make the FIB-SEM workflow possible:
    • Ion source: Gallium liquid metal ion sources provide precise, stable milling.One
    • Electron column: This part of the SEM generates and focuses the electron beam, producing high-resolution images that reveal surface detail and compositional contrast.
    • Stage and chamber: A motorized, multi-axis stage positions the sample with nanometer accuracy, and large chambers accommodate varied specimen sizes.
    • Detectors and accessories: Options such as STEM detectors, EDS for elemental mapping, and gas injection systems (GIS) expand the analytical capabilities of the FIB-SEM and support processes like protective coating and lamella preparation.

    Applications of FIB-SEM

    The adaptability of FIB-SEM has made it valuable across many fields:
    • Materials science: Studying grain boundaries, porosity, and failure mechanisms, often using protective coatings to safeguard delicate regions of the sample during milling.
    • Life sciences and neuroscience: Imaging tissues and cells in 3D, mapping neural networks, and preserving ultrastructure through cryo-FIB-SEM workflows.
    • Energy and geosciences: Characterizing battery electrodes, porous rocks, and other complex materials to understand performance and degradation.
    • Semiconductors and electronics: Inspecting device defects, modifying circuits, and preparing lamellae for TEM, with gas-assisted deposition enabling both shielding and microfabrication.

    Advantages of FIB-SEM

    FIB-SEM offers a unique set of benefits:
    • High-resolution 3D imaging that reveals both surface and subsurface features, providing insights that are unavailable from conventional microscopy.
    • Site-specific targeting, which allows researchers to focus on regions of interest without damaging surrounding material.
    • Integrated milling, imaging, deposition, and analysis, reducing the need for multiple instruments and streamlining workflows.
    • Flexibility across scientific and industrial applications, from failure analysis to biological imaging, making it versatile enough to cater to diverse research challenges.

    Advancing FIB-SEM Research With JEOL Solutions

    FIB-SEM has established a means of exploring beyond surface imaging and studying subsurface structures in greater detail. The JIB-PS500i from JEOL supports these investigations with precise ion milling, seamless integration with TEM, and cryogenic options for sensitive samples. Its spacious chamber and 5-axis motorized stage accommodate diverse specimens, while integrated STEM and EDS detectors keep imaging and analysis within a single platform.
    For researchers working with frozen hydrated or otherwise delicate materials, the CRYO-FIB-SEM CryoLameller adds a dedicated cryogenic workflow. Liquid-nitrogen cooling, cryocooled transfer, and controlled low-temperature milling help maintain sample integrity and enable the production of high-quality TEM lamellae. Together, the JIB-PS500i and CRYO-FIB-SEM CryoLameller provide complementary approaches for conventional and cryogenic FIB-SEM studies. Reach out to our specialists to learn which configuration would best support your research.

      Featured Image - Using High-Resolution SEM and TEM for Advanced Semiconductor Packaging - JEOL USA.png

      Using High-Resolution SEM and TEM for Advanced Semiconductor Packaging

      Using High-Resolution SEM and TEM for Advanced Semiconductor Packaging

      Semiconductor packaging is undergoing significant changes. For years, the focus was on shrinking the pitch of micro-bumps and Through-Silicon Vias (TSVs). Now, driven by the insatiable demand for more bandwidth, lower power consumption, and reduced latency, the industry has adapted the latest technology of direct copper-to-copper (Cu-Cu) hybrid bonding.

      This shift from micro-scale interconnects to direct, atomic-scale bonds marks a fundamental change in what we need to measure and control. The challenge is no longer just seeing the bump; it’s about characterizing the interface itself. Reliability and yield are now decided by nanometer-scale details: oxide layers, voids, contaminants, and crystal grain alignment.

      To succeed in this new paradigm of heterogeneous integration, packaging engineers need a complementary analytical toolkit. JEOL's Field Emission SEM (FE-SEM) and atomic-resolution Transmission Electron Microscopy (TEM/STEM) provide the complete workflow required to characterize these critical interfaces, from the die level down to the atomic scale.

      What Must Be Measured Now

      In an era of hybrid bonding and high-density interconnects, the list of critical-to-quality parameters has grown longer and moved to a much smaller scale. Success depends on precise control over:
      • Interface Cleanliness & Planarity: Pre-bond oxide thickness and surface uniformity are paramount for a successful bond.
      • Post-Bond Integrity: Detecting nanometer-scale voids, gaps, and contaminants at the bond interface.
      • Dimensional Control: Measuring copper recess and dielectric thickness with nanometer precision.
      • Alignment: Verifying die-to-wafer alignment at the nanometer level.
      • Crystallography & Chemistry: Understanding the copper grain structure, orientation, and the presence of unwanted oxides or contamination at the bond line.
      • Legacy Joint Reliability: In traditional micro-bumps, identifying and quantifying Intermetallic Compound (IMC) phases that dictate long-term reliability.

      JEOL SEM for High-Throughput Packaging Inspection

      For rapid, high-throughput inspection of large areas, JEOL’s FE-SEM is the first line of defense.

      The JSM-IT800/IT810 FE-SEM with integrated Energy Dispersive X-ray Spectroscopy (EDS) is ideal for characterizing micro-bump arrays, hybrid bond pads, and Redistribution Layers (RDLs).
      • Imaging Modes: Use Secondary Electron (SE) imaging for high-resolution topographical detail and Backscattered Electron (BSE) imaging for powerful materials contrast, which is perfect for distinguishing between solder, IMCs, copper, and underfill materials.
      • Automated Workflows: Our SEM Center software enables automated recipes for inspecting hundreds of bond pads, providing statistically significant data on pad integrity and defects.
      The quality of any analysis depends on the quality of the specimen. The JEOL Cross Section Polisher™ (CP) uses a broad, low-energy argon ion beam to create large, clean, and artifact-free cross-sections of challenging multi-material stacks containing solder, copper, and polymers. Standard and cooling stage options prevent heat damage to sensitive materials, while air-isolation transfer options protect the sample from atmospheric contamination.

      JEOL HR-TEM/STEM for Interfaces That Decide Reliability

      When an interface fails, or when you need to certify a new process, you must go beyond the resolution limits of SEM. JEOL's aberration-corrected TEM/STEM provides undeniable, atomic-scale proof.

      The JEM-ARM300F (GRAND ARM) is designed for this exact challenge.
      • Sub-Ångstrom Imaging: High-Angle Annular Dark-Field (HAADF) STEM imaging can easily resolve nanometer-scale oxide layers, voids, and defects directly at the Cu-Cu bond interface.
      • Chemical Analysis: Integrated EDS and Electron Energy Loss Spectroscopy (EELS) can perform line scans across the bond to map the precise location and concentration of oxygen, carbon, and other contaminants. EELS can even determine the oxidation state of copper, distinguishing between problematic oxides and pure metal.
      • Crystallographic Information: Using diffraction modes, you can analyze crystal grain orientation and measure nanoscale strain, both of which are critical for predicting bond reliability.

      Workflow Examples: From Process Control to Failure Analysis

      1. Verifying a Hybrid Bond Interface:
      • Create a cross-section of the bond area using the JEOL Cross Section Polisher™.
      • Use a JSM-IT800 FE-SEM for a rapid survey and EDS mapping to confirm the location and general composition.
      • Prep site-specific TEM lamella targeting the bond interface using JEOL dual beam PS500i.
      • In the JEM-ARM300F, acquire a STEM-EELS oxygen map across the interface. The resulting data can be used to set clear pass/fail criteria (e.g., oxide thickness must be <1 nm, void area fraction must be <0.5%).
      2. Assessing Micro-bump Reliability:
      • Use the CP to create a clean cross-section through a series of solder bumps.
      • In the SEM, use Backscattered Electron (BSE) imaging to clearly highlight the different Intermetallic Compound (IMC) layers.
      • Use integrated EDS to perform phase identification and quantify the elemental composition of each IMC layer.
      • For advanced failure analysis, a TEM sample can be prepared to measure IMC layer thickness with nanometer precision and investigate the morphology of any micro-voids.

      Reporting for Actionable Engineering Insights

      A comprehensive engineering report moves beyond pretty pictures. It translates raw data into actionable metrics. Using JEOL's integrated suite, your reports can include:
      • Histograms of bond pad alignment error.
      • Distributions of oxide thickness measurements from EELS data.Three
      • Void size and area fraction distributions.
      • Quantification of IMC phase fractions and layer thicknesses.
      This data allows you to set firm, statistically validated acceptance windows for your semiconductor packaging processes, directly linking nanoscale metrology to device reliability and yield.

      Ready to see your interface? Set up a JEOL packaging interface study—SEM + ARM-class TEM recipe designed for your pad stack and pass/fail metrics.

      How is Metrology Used in Failure Analysis?

      How is Metrology Used in Failure Analysis?

      Every credible failure analysis is supported through metrology, the science of measurement. When a component, material, or system fails, engineers need more than visual clues. They require quantitative data that reveals how and why the failure occurred. In semiconductor devices, where functionality depends on nanoscale geometries, interface integrity, and material uniformity, metrology is essential for distinguishing normal process variation from true failure mechanisms. By characterizing geometry, surface features, and internal structure with traceable accuracy, it ensures the analysis is grounded in verifiable results and stands as a reliable determination of the underlying cause of failure.

      Why Measurement Quality Matters in Failure Analysis

      Before engineers can test a hypothesis, they must record exactly how the part failed, as these details are what enable a failure analysis to be trustworthy. Without reliable data, conclusions are speculative and corrective actions may miss the true cause of failure. Accurate metrology turns observation into quantifiable fact, ensuring each dimension, defect, and deviation is captured with confidence.

      In practice, this means:
      • Quantifying geometry and defects - reveals how features such as crack width, distortion, void size, and coating thickness contributed to failure.
      • Comparing "as-failed" to "as-designed"- identifies if dimensions have drifted beyond tolerance and where a process or material deviation occurred.
      • Ensuring traceability and reproducibility - provides calibrated, uncertainty-defined results that can withstand quality or warranty scrutiny.
      When measurement quality is strong, engineers can trust the data enough to trace the failure back to its true cause and understand how it developed in the first place.

      How Metrology Is Used in Failure Analysis

        1. Initial visual and dimensional inspection

        The process starts with a non-destructive evaluation of the failed part. Optical or coordinate measurements capture overall geometry, identifying distortion or dimensional drift relative to design drawings. Collecting these measurements early helps engineers preserve the "as-failed" condition before moving on to further testing.

        2. Surface metrology and form measurement

        Scanning electron microscopy (SEM) delivers surface metrology that reveals fine details of pattern deformation, line-edge roughness, contamination, and localized damage within semiconductor structures. Quantifying roughness and topography uncovers how stress, friction, or environmental conditions contributed to the failure.

        3. Internal defect detection

        Focused Ion Beam (FIB) 3D reconstruction provides high-resolution, site-specific internal metrology by sequentially milling and imaging material volumes at the nanoscale. This approach enables engineers to visualize and measure buried voids, interconnect discontinuities, delamination, and interface defects that cannot be resolved through surface inspection alone and are often responsible for electrical or reliability failures in semiconductor devices.

        4. Cross-section and microstructural metrology

        If destructive sectioning is needed, optical or electron microscopy measures grain size, inclusion distribution, or microcrack geometry to determine whether the cause of failure lies in material quality or processing.

        5. Correlation with design and process data

        Metrology measurements are compared with design tolerances and manufacturing records to locate where deviation occurred, be it in raw material, machining, or assembly.

        6. Validation and modeling

        Dimensional and microstructural data generated through metrology feed directly into computational models such as finite-element analysis (FEA). Using real, measured parameters, engineers can simulate stress propagation or fatigue behavior to assess how well the modeled mechanism matches the failure observed.
        Throughout the investigation, metrology is able to supply consistent data that supports the failure analysis, allowing engineers to connect observation with the mechanisms that contributed to the defect and identify the improvements that can prevent it from recurring.

        Techniques That Enable Quantitative Failure Analysis

        Failure analysis draws on several branches of metrology, which offer unique insight into geometry, surface condition, or internal structure:
        • Dimensional metrology- Coordinate measuring machines (CMMs), laser trackers, and optical scanners quantify part geometry and tolerance drift.
        • Surface metrology- Stylus and optical profilometers measure roughness and waviness, while SEM provides high-resolution images of fracture surfaces and wear tracks.
        • Internal defect metrology-Internal defect metrology- X-ray and CT scanning allow for the measurement of internal voids, inclusions, or delamination without altering the sample.
        • Electron microscopy-based metrology- SEM and Transmission Electron Microscopy (TEM) measure micro- and nano-scale features such as inclusions and interface integrity.
        • Analytical extensions- Energy-dispersive X-ray spectroscopy (EDS), electron energy loss spectroscopy (EELS), and mass spectrometry add chemical information that links structure to composition.
        Together, these complementary metrology techniques support evidence-based failure analysis across a range of industries, including aerospace and energy.

        How Electron Microscopy Is Used in Semiconductor Failure Analysis

        In the semiconductor industry, where critical features reach the nanometer scale, Transmission Electron Microscopy (TEM) and Scanning Electron Microscopy associated with Focused Ion Beam (SEM/FIB) provide the resolution to identify failures within complex device architectures, including dislocations, voids, interface defects, and other nanoscale features that influence device performance.

        A typical semiconductor failure-analysis workflow includes:
        1. Fault localization- Electrical testing or SEM identifies the suspect region.
        2. Sample preparation- FIB milling thins the site to tens of nanometers, generating an electron-transparent lamella.
        3. TEM or STEM imaging- High-energy electrons pass through the sample, revealing dislocations, voids, or interface defects with atomic-scale clarity.
        4. Analytical mapping- EDS and EELS quantify elemental distribution and chemical bonding to connect material changes with electrical behavior.
        5. Correlation- JEOL software enables quantitative metrology of critical dimensions within device features, such as interconnects, gate structures, dielectric layers, and material interfaces, allowing engineers to confirm whether voids, oxide breakdown, or interface defects caused the functional failure.
        SEM, FIB, and TEM metrology supplies evidence that engineers can use to diagnose device failures accurately and make informed changes that enhance manufacturing outcomes.

        Strengthening Failure Analysis with Metrology Solutions from JEOL USA

        Modern failure analysis requires precise metrology tools that can measure and resolve defects and variations that lead to component or system issues, including nanoscale dimensional and material variations common in semiconductor devices. JEOL USA offers advanced electron microscopy, mass spectrometry, and electrical analysis systems that can characterize structural features, identify chemical contaminants, and locate electrical defects with high accuracy. Speak with JEOL USA to learn more about our available products, including our TEMs and SEMs, designed for high-precision failure analysis and how they can help drive comprehensive, data-driven investigations that accelerate root-cause identification and support more resilient product development cycles.

            Featured Image - What is a FinFET and How Does it Work - JEOL USA.png

            What is a FinFET and How Does it Work?

            What is a FinFET and How Does it Work?

            For decades, the planar MOSFET was the bedrock of integrated circuits. But as semiconductor nodes shrank, the physical limits of this 2D design began to show. Engineers faced a critical challenge: "short-channel effects." As the distance between the source and drain decreased, the gate lost electrostatic control, leading to current leakage and increased power consumption.

            The industry needed a new transistor geometry. The solution was to go 3D.

            Enter the FinFET. This multi-gate transistor architecture revolutionized semiconductor design by enabling the development of advanced nodes. Instead of a planar channel, the FinFET uses a vertical silicon "fin" that rises from the substrate. The gate is wrapped around this fin on three sides, providing superior electrostatic control and mitigating the short-channel effects that plagued its planar predecessors.

            This "multi-gate" approach is a key concept. A multi-gate device, as the name implies, has more than one gate on a single transistor. This family of devices includes not only FinFETs but also future architectures like Gate-All-Around (GAA) FETs, which promise even greater control and scaling.

            A Quick Primer: Planar vs. FinFET

            To understand the difference, imagine a simple cross-section:
            • Planar MOSFET: A flat, 2D channel lies on the silicon substrate. The gate sits on top, controlling the flow of current.
            • FinFET: A 3D fin of silicon rises vertically. The gate wraps around the fin, creating a larger, more effective control area.
            Key terms to know for FinFETs include:
            • Fin Height (Hfin): The height of the silicon fin.
            • Fin Width (Wfin): The thickness of the fin.
            • Pitch: The distance between adjacent fins.
            • Gate Length: The length of the gate as it wraps around the fin.

            How a FinFET Actually Operates

            The genius of the FinFET lies in its 3D gate control. By wrapping the gate around the fin, the FinFET achieves:
            • Superior Depletion: The gate can more effectively deplete the channel of charge carriers, leading to a much lower "off-state" leakage current.
            • Steeper Subthreshold Slope: The subthreshold slope is a measure of how quickly a transistor can switch from "off" to "on." A steeper slope means a more efficient switch, and FinFETs excel in this regard. This translates to lower power consumption.
            • Increased Drive Current: At the same supply voltage (Vdd), a FinFET can deliver a higher drive current than a planar device. This means faster, more powerful processors.
            • Parasitics to Watch: The 3D structure also introduces new parasitic capacitances and resistances that must be carefully managed during design and characterization.

            Boxed Math: The Fin Aspect Ratio

            The electrostatic control of a FinFET is directly related to its fin aspect ratio (Hfin/Wfin). A taller, thinner fin (a higher aspect ratio) provides better gate control and reduces short-channel effects. However, it also presents significant manufacturing and characterization challenges.

            Complementary FET (CFET) architectures represent the next step beyond FINFET-based scaling. In a CFET, the n-type and p-type transistors that form a completely metal-oxide semiconductor (CMOS) pair are vertically stacked rather than placed side by side. This vertical arrangement significantly reduces standard cell area without relying on further lateral pitch scaling. CFETs build directly on the gate-control concepts established by “Gate-All-Around” devices, but shift the primary scaling benefit toward stacking and layout efficiency, making them a leading candidate for technology nodes below 2 nm.

            Why 3D Geometry Demands New Characterization

            The complex, three-dimensional nature of FinFETs presents new challenges for process control and failure analysis. Simply put, you can't characterize what you can't see. Key challenges include:
            • Targeting Specific Fins: In dense arrays of fins, isolating a single, specific fin for analysis is a major hurdle.
            • Preserving Interfaces: The interfaces between the high-k dielectric and the metal gate (HKMG) stack are critical to device performance. Preparing a sample for analysis without damaging these delicate layers is essential.
            This is where JEOL's purpose-built workflows come in.

            The JEOL Workflow: From Specimen to Atomic-Scale Analysis

            JEOL provides an end-to-end solution for FinFET characterization, from specimen preparation to atomic-scale imaging and analysis.
            • Site-Specific Preparation:
              • FIB-SEM: Our Focused Ion Beam (FIB) and Scanning Electron Microscope (SEM) systems allow for precise, site-specific milling to isolate the fin of interest.
              • Cross Section Polisher™ (CP): For wide, clean, and damage-free cross sections, our CP tools use a broad argon ion beam to gently polish the sample surface. For sensitive materials, our air-isolation options protect the sample from atmospheric contamination.
            • High-Resolution Imaging and Analysis:
              • JSM-IT800/IT810 FE-SEM: These Field Emission SEMs provide ultra-high-resolution imaging for critical dimension (CD) measurements, line-edge roughness analysis, and defect localization. Integrated Energy Dispersive X-ray Spectroscopy (EDS) provides elemental composition information.
            • Atomic-Scale Structure and Chemistry:
              • JEM-ARM300F (GRAND ARM): This aberration-corrected STEM (Scanning Transmission Electron Microscope) achieves resolutions of 58-63 pm, allowing for the direct imaging of atomic structures. With integrated EDS and Electron Energy Loss Spectroscopy (EELS), you can perform detailed chemical analysis of the gate stack and interfaces.
            • 3D Device Tomography:
              • JEOL's STEM/EDS tomography capabilities enable the 3D reconstruction of fins and contacts, providing a complete picture of the device's structure.

              Application Example: Creating a TEM Specimen of a FinFET

              A typical JEOL workflow for creating a TEM specimen of a FinFET might look like this:
              • SEM Targeting: Use a JEOL SEM to locate the specific fin or feature of interest.
              • CP or FIB Preparation: Use our Cross Section Polisher™ for a wide, damage-free cross-section, or a FIB-SEM for site-specific milling and lift-out.
              • Lift-Out and Mounting: The prepared lamella is carefully lifted out and attached to a grid mounted on a double-tilted TEM holder.
              • HR-STEM Imaging and EELS: The specimen is then transferred to a JEM-ARM300F for high-resolution STEM imaging and EELS mapping of the gate oxide and work-function metals.

              Common Pitfalls and How JEOL Mitigates Them

              • Curtaining and Mechanical Damage: Traditional cross-sectioning methods can introduce artifacts like "curtaining" (vertical lines on the cross-section) and mechanical damage. JEOL's Cross Section Polisher™ (CP) minimizes these effects.
              • Beam Damage and Contamination: Sensitive materials can be damaged by the electron beam or contaminated by exposure to air. JEOL's air-isolation transfer systems and advanced beam control technologies protect your sample throughout the workflow.

              The Takeaway

              The performance and reliability of FinFET devices are inseparable from their atomic-scale structure and chemistry. JEOL's comprehensive, end-to-end workflow—from specimen preparation to imaging and analysis—provides the critical insights needed to shorten development cycles and accelerate process learning.

              Discuss a               FinFET specimen-to-analysis workflow on your device—schedule a session with JEOL applications.

                  What Is Surface Analysis?

                  What Is Surface Analysis?

                  Surface analysis is an analytical technique to elucidate elemental composition, chemical state, and micro structure from material surface layer (several nm to several µｍ). As phenomena such as corrosion, wear, adhesion, and reactions that impact performance and reliability occur primarily on the surface, surface analysis is vital for material evaluation, quality control, and failure analysis.
                  For analysis, it is necessary to select the most suitable method, according to the sample state (target point, size, material, etc.) and analysis purpose.
                  What information we want to know? What is the material of the sample?
                  What is the range of information that we want to know? How deep?
                  Is it water-soluble? Does it react with solvents? Pre-treatment needed?
                  It is important to select the analytical method suitable for the purpose.

                  Types and features of surface analysis instruments

                  The figure below shows the comparison of typical surface analysis methods from various points of view, such as excitation source, detection signal, quantitativeness, whether the chemical state can be analyzed or not, sensitivity, handling of an insulator, and analysis capability of depth direction. It is important to understand the feature of each method and properly select the analysis method according to the purpose.
                  Analytical methods EPMA (WDS)/SXES/EDS AES XPS XRF SIMS
                  Excitation source Electron beam Electron beam X-ray X-ray Ion
                  Signal Characteristic X-ray Auger electron Photoelectron Fluorescence X-ray Secondary ion
                  Detectable element Be ~ (WDS, EDS)
                  Li (SXES, Windowless EDS)                  		 Li ~ Li ~ C ~ H~
                  Quantitative analysis ○ ○ ○ ○ ×
                  Chemical state △ ○ ○ × Organic compound
                  Detection depth Several µm Several nm Several nm Several mm Several nm
                  Sensitivity Several ten ppm
                  （Mass concentration）                  		 Several thousand ppm
                  （Atomic concentration）                  		 Several thousand ppm
                  （Atomic concentration）                  		 Several ten ppm
                  （Mass concentration）                  		 Several ppm
                  （Atomic concentration）
                  Insulator ○ (Conductive coating) △ ○ ○ ○
                  Depth analysis △ ○ ○ × ○
                  Strength Qualitative analysis
                  Quantitative analysis
                  Wide area ~ micro area analysis                   		Micro area analysis
                  Chemical bonding state analysis
                  Depth profile analysis                   		Insulator analysis
                  Chemical bonding state analysis
                  Depth profile analysis                   		Qualitative analysis
                  Thin film analysis
                  Trace element analysis                   		Organic substance analysis
                  Trace element analysis
                  Challenge Chemical bonding state analysis
                  (Strong at SXES)
                  Organic substance analysis                   		Wide area analysis
                  Insulator analysis
                  Organic substance analysis                   		Micro area analysis
                  Trace element analysis                   		Micro area analysis Qualitative analysis
                  Quantitative analysis
                  In this column, we explain surface analysis instruments that JEOL offers, such as XPS (photoelectron spectrometer), AES (Auger microprobe) , XRF (X-ray Fluorescence Spectrometer) , EPMA (Electron Probe Microanalyzer) with *standard wavelength-dispersive X-ray spectrometer, SEM+EDS (Scanning Electron Microscope＋Energy Dispersive X-ray Spectrometer), and SXES (soft X-ray emission spectrometer) that can be installed to EPMA (WDS) and SEM.
                  We clearly explain each mechanism, its strengths and weaknesses in analysis, and key points for selecting the instrument.

                  Difference of analysis area/depth according to surface analysis instrument

                  XRF enables elemental analysis in the deepest and widest region. It is suitable for understanding the average composition of the entire bulk material and is utilized in qualitative/quantitative analysis in a wide field of view.
                  On the other hand, SEM + EDS and EPMA (WDS) can investigate the local elemental distribution by detecting x-rays that are generated in a local area of about several micrometers. SEM+EDS enables simultaneous evaluation of morphology and elemental analysis, while EPMA provides superior capabilities in more precise quantitative analysis and area analysis.
                  Moreover, AES and XPS makes it possible to obtain signals from the very shallow surface layer of about several nanometers deep. They are optimal for evaluating chemical state of the surface layer such as surface processing, contamination, and oxidization state.
                  Thus, to investigate the extreme surface at the nanometer scale, AES or XPS is suitable. For local analysis at the micrometer level, SEM combined with EDS or EPMA is appropriate. If the target is a wide area on the millimeter scale, XRF is the best choice. The appropriate instrument varies depending on the required analysis depth and the field of view size.

                  Difference in principles and detection signals of surface analysis instruments

                  As shown below, each instrument has a different excitation source (incident probe) and detection signal, and the information obtainable is different according to their features.

                  Points for selecting surface analysis method

                  In surface analysis, it is important to select the appropriate technique based on the properties of the specimen and the purpose of the analysis. For specimens that are susceptible to vacuum, such as biological or liquid specimens, methods like XRF, which can be performed under atmospheric pressure, or SEM equipped with a low-vacuum mode are effective. If the specimen can withstand a vacuum environment, more sensitive and higher-resolution techniques such as XPS, AES, or EPMA can also be considered. This section introduces the optimal analytical method for each purpose, along with the figures.

                  Qualitative/Quantitative Analysis

                  Area Analysis

                  State Analysis

                  Summary

                  Surface analysis is a technique to obtain key information that directs to performance and reliability of the instrument. This article explains the tips of instrument selection through the features of typical analysis methods and points of selection, strength by instrument, and concrete application examples.
                  JEOL Ltd. has product line-ups that can satisfy a wide range of needs from beginners to researchers, and that can be utilized with support from introduction to operation.
                  COSY/TOCSY Analysis│Interpreting spin correlations using 2D NMR

                  COSY/TOCSY Analysis│Interpreting spin correlations using 2D NMR

                  In this article, we explain the basic principles and analysis methods of COSY and TOCSY, which are representative techniques of 2D NMR. Starting from confirming correlations between adjacent protons using COSY, we introduce spin network analysis with TOCSY and analysis of carbohydrate using 1D and 2D TOCSY, with concrete examples.

                  What is COSY?

                  COSY（COrrelation SpectroscopY）is a basic method for visualizing couplings between adjacent 1Hs by using 2D NMR. Traditionally, homodecoupling of 1Hs was used to locate neighboring 1H atoms one by one. However, with the appearance of COSY, it became possible to analyze 1H-1H coupling correlations simultaneously over a broad range, dramatically improving the efficiency of structural analysis. Currently, COSY is widely used as an introductory 2D NMR method for confirming 1H-1H correlations.

                  COSY shows correlations between adjacent 1Hs - in other words, 1Hs that are 3 bonds apart. The spin coupling of 3 bonds apart is expressed as 3JHH. If the adjacent 1H is known, the connection of 1Hs in a molecule can be understood.

                  Fig.1 COSY spectrum of cinnamic acid cis-3-hexenyl ester
                  Fig.1 COSY spectrum of cinnamic acid cis-3-hexenyl ester

                  Fig.1 shows a COSY spectrum for the region corresponding to 1Hs at 1 to 6 in "cinnamic acid cis-3-hexenyl ester". As indicated above, when the correlation signals and 1H spectrum of 1D on both axes are connected, 5 correlations can be observed: 1-2, 2-3, 3-4, 4-5, and 5-6. The result allows us to infer that 1Hs from 1 to 6 have a neighboring structure each. In addition, the COSY allows us to understand the connection between carbon atoms indirectly from the coupling information of neighboring 1Hs. The information is extremely important for determining the substructure.

                  Fig.1 COSY spectrum of cinnamic acid cis-3-hexenyl ester
                  Fig. 2 Complex COSY spectrum
                  However, what happens when the COSY spectrum is as complex as the one in Fig. 2? Looking at the region highlighted in green, you can see that the signals overlap, making it hard to identify correlations. In this situation, moving forward with structure determination seems almost impossible.

                  For compounds like polysaccharides or cyclic molecules, where 1H signals densely appear in a narrow range as in Figure 2, relying on COSY alone can lead to a dead end in structural analysis.

                  One solution for the situation when the COSY does not adequately analyze is TOCSY. We will explain TOCSY in the next section.

                  What is TOCSY?

                  TOCSY（TOtal Correlation SpectroscopY）is a 2D NMR technique that allows you to visualize all 1Hs belonging to the same spin network at once. Because spin couplings propagate through the network, TOCSY reveals not only adjacent positions but also correlations across the entire spin system, making it highly effective for analyzing complex organic molecules, sugars, and amino acids. TOCSY is also known as HOHAHA（HOmonuclear HArtmann-HAhn spectroscopy), which essentially refers to the same experiment.

                  Fig. 3 Network of continuous 1H spin couplings

                  For example, suppose that there are atomic connections as shown in Figure 3. HA・HB・HC・HD are connected through spin couplings between neighboring 1Hs, and this connection is called spin system (spin network). The spin system does not propagate through quaternary carbons without attached H or 1H coupled via oxygen, so the network is interrupted at these points. TOCSY allows us to observe correlations between nuclei within the same spin system even if they are not directly coupled--for instance, between 1HA and 1HD. In TOCSY, the magnetization is transferred step by step: from HA to HB, then from HB to HC, and finally from HC to HD. In other words, magnetization moves through the spin system, connecting everything along the way. This magnetization transfer is called "relay". TOCSY observes the correlation signals based on this relay.

                  Fig. 4 Pulse sequences of COSY and TOCSY
                  Fig. 4 shows the pulse sequences for COSY and TOCSY. COSY uses two 90° pulses, while with the TOCSY, the second pulse is a spin lock pulse. The duration of this spin lock pulse is called "mixing time," which is a key parameter with TOCSY. By increasing the mixing time, you can observe correlation signals that have been relayed over longer distances within the spin system.

                  Mixing time and correlation signal of TOCSY

                  Fig. 5 Schematic diagram of TOCSY spectrum

                  Fig. 5 shows a schematic diagram of a TOCSY spectrum of a compound having two independent spin networks. Each spin network is expressed in yellow and in green. As shown, TOCSY observes correlation of all 1Hs belonging to each spin network. At that time, if signals like "A" and "a" within the primary spectrum on both axes appear away from the region where signals appear densely, the signals are easily classified separately in the networks of yellow and green, enabling confirmation of each spin network.

                  Fig.6 Schematic diagram of TOCSY (Correlation of A)

                  Next, let's look at how the correlation signal of A changes when the mixing time is varied. Figure 6 is an enlarged view of the correlation of A from the schematic TOCSY diagram in Figure 5. With a short mixing time, the magnetization of 1HA moves only to the neighboring 1HB, and the correlation signal B with 1HB appears. When the mixing time is further increased, the magnetization moves to 1HC, and correlation signal C appears. When the mixing time is increased even more, the magnetization moves to 1HD, and correlation signal D appeared. As a result, it becomes clear that there is a connection of 1HA - 1HB - 1HC - 1HD.

                  The longer the mixing time, the farther the magnetization can move. Therefore, if a sufficiently long mixing time is used, the magnetization can be transferred through all 1Hs within the same spin system, allowing the detection of correlation signals for all 1Hs in that spin system. Furthermore, by comparing spectra obtained with different mixing times, the sequential order of the 1H connections can also be known.

                  Example of analysis for sucrose using 2D TOCSY

                  20 mg / 0.6 mL D2O solution (400 MHz)

                  Here, we present an example of analysis for sucrose using 2D TOCSY. Sucrose is a disaccharide composed of glucose and fructose linked by a glycosidic bond. Sucrose contains a total of 22 1Hs, but since the sample is dissolved in heavy water, the 1Hs of the hydroxyl groups (-OH) are not observed due to deuterium exchange. Therefore, in this case, 14 1Hs are observed, excluding the 8 1Hs of hydroxyl group.

                  Fig.7 COSY spectrum of sucrose
                  Let us show you the COSY spectrum of sucrose in Fig. 7. The part highlighted in the red frame is enlarged and shown in Fig. 8.
                  Fig. 8 COSY spectrum of sucrose
                  In Figure 7, six correlation signals can be found relatively easily. However, it is difficult to interpret the correlations of signals appearing in areas where chemical shifts are close to each other, such as those indicated by the red circles in Figure 8. Many people may get stuck at this point in the analysis. Therefore, we will try using the TOCSY method.
                  TOCSY spectrum with mixing time of 20ms
                  TOCSY spectrum with mixing time of 150ms
                  Fig. 9 TOCSY spectra measured with mixing times set to 20 ms and 150 ms

                  Figure 9 shows the TOCSY spectra measured with mixing times set to 20 ms and 150 ms, respectively. First, we focus on the correlation signal of the 1H at the anomeric position of glucose, which appears at a chemical shift well away from other signals. As shown earlier in Figure 6, we will examine how the correlation signals change with different mixing times, to confirm the relay information from the 1H at the anomeric position. It can also be observed that more correlation signals appear as the mixing time increases. Furthermore, for regions where signals overlap, it is easier to compare by using sliced data rather than the 2D spectrum. Therefore, we will compare each 1D spectra obtained by extracting slices along the X-axis (in the area indicated by the green frame) for the confirmation of correlation signal of the 1H.

                  Figure 10. One-dimensional spectra sliced along the X-axis for the correlation signal of the 1H at the anomeric position of sucrose

                  The top spectrum in Figure 10 shows a conventional 1H spectrum. Below it are sliced data obtained with mixing times varied from 20 ms to 200 ms. The signal on the left corresponds to the Glu H-1, which we consider as the starting point of the relay. At a mixing time of 20 ms, only the correlation with the neighboring Glu H-2 appears, revealing only the connection between positions 1 and 2. As the mixing time increases, correlation signals appear sequentially, and eventually, the connections from position 1 to position 6 in the glucose moiety can be confirmed. While it was difficult to clearly identify the correlation partner of the Glu H-5 using COSY, TOCSY provided this information.

                  Next, let us examine the relay starting from the Fru H-3′. As with the sucrose moiety, Figure 11 shows the TOCSY spectra obtained with different mixing times.
                  TOCSY spectrum measured with mixing time of 20ms
                  TOCSY spectrum measured with mixing time of 150ms
                  Figure 11. TOCSY spectra measured with mixing times set to 20 ms and 150 ms
                  As before, we compare sliced data along the X-axis for a signal that appears in a region without significant overlap--this time focusing on the Fru H-3′.
                  Fig. 12 One-dimensional spectra sliced along the X-axis for the correlation signal of the H-3′ proton of fructose

                  The top spectrum in Figure 12 shows a conventional 1H spectrum, and below it are sliced data obtained with different mixing times. As before, we take the Fru H-3′ as the starting point of the relay. As the mixing time increases, correlations with the Fru H-4′, Fru H-5′, and Fru H-6′ appear, allowing us to confirm the connections within the fructose moiety.

                  In this way, TOCSY enables the separation of spin networks within a compound that contains multiple spin networks. By varying the mixing time, it is also possible to assess the distance from the starting 1H. Even when the COSY spectrum becomes complicated, using TOCSY provides significant assistance in determining the molecular structure.

                  Example of analysis for glucose using 1D TOCSY

                  1D TOCSY is the one-dimensional version of 2D TOCSY, and the basic principle is the same. While 2D TOCSY is used to analyze the spin network of the entire molecule, 1D TOCSY is more effective when you want to examine only the spin system to which a specific 1H belongs. 1D TOCSY observes the magnetization transfer--i.e., the relay--from a selectively excited 1H. By gradually increasing the mixing time, the propagation of the magnetization relay along the spin network can be tracked. For selective excitation, it is best to choose a 1H whose chemical shift is sufficiently separated from other signals. Another advantage of 1D measurement is that, compared to 2D measurement, it offers higher digital resolution and makes it easier to avoid signal overlap.

                  Now, let us present an example of glucose analysis.

                  Fig 13. 1H spectrum of glucose

                  Glucose exists in aqueous solution as α- and β-anomers. Therefore, the 1H NMR spectrum is a mixed spectrum of α-glucose and β-glucose, as shown in Figure 13. For selective excitation of a 1H signal, it is typically to choose 1H appearing at a lower field than others (in the case of sugars, 1H at the anomeric position). The result of a 1D TOCSY experiment by selectively exciting the anomeric 1H at position 1 of α-glucose is shown in Figure 14.

                  Vivamus sagittis lacus vel augue laoreet rutrum faucibus dolor auctor. Duis mollis, est non commodo luctus.
                  Fig.14 1D TOCSY spectrum of glucose

                  By varying the mixing time from 20 ms to 200 ms, it was possible to trace the spin network starting from the anomeric 1H at position 1 of α-glucose as the relay point. The bottom spectrum with a mixing time of 200 ms represents the extraction of only the spin network of α-glucose from the mixed spectrum of α-glucose and β-glucose. Furthermore, as explained earlier, 1D TOCSY provides better digital resolution than 2D sliced data. Thus, 1D TOCSY is more effective for extracting and confirming spin systems connected through spin couplings from crowded spectra. It is recommended to use 1D TOCSY and 2D TOCSY appropriately depending on the purpose.
                  Basics of NOE/NOESY: Causes and Solutions When NOE Is Not Detected

                  Basics of NOE/NOESY: Causes and Solutions When NOE Is Not Detected

                  NOE (Nuclear Overhauser Effect) is an important NMR measurement technique that can reveal spatial proximity relationships within molecules. In this column, we discuss the difference between difference NOE, 1D NOESY, and 2D NOESY, and how to select each method, the relaxation time that is key for analysis. The causes and solutions for cases when NOE is not detected are also covered. Moreover, we answer the frequently asked questions and explain the key points for effective use of NOE measurement.

                  What is NOE measurement?

                  What is NOE measurement?
                  NOE measurement (Nuclear Overhauser Effect) is a method to observe nuclei in spatially close distance. The NOE measurement is utilized to obtain stereochemistry of molecules, and distinguish isomers and confirm location of substituent group, for application of small molecular compound.

                  Principle of NOE

                  The NOE is a phenomenon where spatially close nuclei magnetically affect each other and cause an NMR signal intensity change.

                  1. Relation between nuclear spin and magnetic field

                  When placed under the influence of external magnetic field, the energy state of nuclear spin of proton splits (Zeeman splitting).

                  2. Saturation by radio wave

                  When radio wave continues to irradiate to a specific proton, the spin state of the proton "saturates". In saturation state, energy absorption and release are balanced, and the signal disappears.

                  3. Dipole - dipole interaction

                  When saturated proton magnetically interacts with another spatially close proton, the signal intensity of this proton changes. This interaction is classified as "bipolar-bipolar interaction".
                  Principle of NOE
                  Considering NOE, we think about two protons in one molecule as shown in the above figure.
                  When these protons are close to each other, the NOE is observed due to dipole interaction.
                  On the other hand, if the distance between protons is far, the NOE is not observed as there is no dipole interaction.
                  It is known that the dipole interaction is closely related to the inter-nuclear distance and molecular mobility, and if the distance between two nuclei is shorter than 6 Å, NOEs may be observed.
                  On the other hand, since the magnitude of the interaction is proportional to the inter-nuclear distance (r) to the minus sixth power (r-6), When the inter-nuclear distance increases, the interaction rapidly decreases, making it difficult to observe NOEs.

                  How to observe NOE

                  Different from the splitting by spin-coupling, the NOE is not observed with the NMR spectrum (1D, 2D NMR) that we have introduced so far.
                  Therefore, the following steps are required for the NOE measurement.
                  • Irradiating radio wave to specific proton (excitation/saturation)
                  • Observing signal intensity change of other protons
                  • Judging if this change is coming from the NOE

                  Types of NOE Measurement

                  Types of NOE Measurement
                  There are three main types of NOE measurements.
                  • Difference NOE: observe a steady state NOE by taking the difference in spectra with and without radio wave irradiation.
                  • 2D NOESY: observe transient NOE by using a 2D spectrum.
                  • 1D NOESY: selectively excite protons and observe transient NOE in one dimension.
                  Steady state NOE is to irradiate a radio wave for a long time, make a specific proton saturated, and observe the signal intensity change of other protons once the saturation state becomes steady.
                  Transient NOEs are observed during the mixing time after the spin state is temporarily changed by a short period of radio wave irradiation. Since the mechanisms by which NOEs are generated are different, the measurement conditions for each method must be determined by considering the characteristics of each.

                  Difference NOE Measurement

                  Difference NOE measurement is a method of checking the change in signal intensity of nearby protons by taking the difference between the spectra of a specific proton when irradiated with radio waves and when not irradiated with radio waves.
                  Difference NOE Measurement

                  As shown above, two protons, HI and HS are going to be considered. HI and HS are in spatially close distance and having a dipole interaction. (B) is 1H spectrum when HS was not irradiated.

                  Here, when a radio wave is irradiated to HS to saturate HS, the signal of HS becomes invisible. At this time, the signal intensity of HI becomes large due to the dipole interaction between HI and HS. This is the "Change due to NOE". Since the change of signal intensity by NOE is very small, the difference between (A) and (B) is calculated to make the difference clear. The NOE observed by difference NOE is called "steady state NOE". In general, for a small molecular compounds having high speed molecular motion in solution, when the signal change of irradiated proton is expressed downward, the NOE signal is observed as an upward signal. This is called "Positive NOE".

                  Actual example of difference NOE measurement is introduced, by using ethyl crotonate.
                  Difference NOE Measurement
                  We would like to determine whether the conformation of a double bond is cis or trans by using the difference NOE measurement. The proton of methyl group expressed as A is irradiated, and the related NOE is observed.

                  In the upper part of the above figure, the 1H spectrum of ethyl crotonate is shown. In the lower part, difference NOE spectrum when a proton of methyl group at A is saturated, is shown. This data is measured by using 400 MHz instrument and the NOE signals are observed upward at B and C.

                  Based on the obtained results, irradiation of the proton of the methyl group at A led to observable NOEs at B and C, indicating that ethyl crotonate has a trans conformation.

                  1D NOESY

                  1D NOESY is a method to selectively excite a specific proton and observe the transient NOE between the specific proton and the other spatially nearby protons as a one-dimensional spectrum. In this measurement, soft pulse (narrow bandwidth pulse) and pulsed field gradient are used to excite only the proton of interest, and the change in NOE over the mixing time is recorded. Since there is no need to subtract spectra as in difference NOE, spectra that are easy to analyze are obtained. 1D NOESY is suitable when you have a specific proton of interest or when you want to check the NOE in a simple way.
                  1D NOESY
                  Here, we present an example of a 1D NOESY measurement using ethyl crotonate. The (B) in the above figure shows 1D NOESY spectrum obtained by selective excitation of proton A, while (C) shows the spectrum obtained by selective excitation of proton C. Unlike difference NOE spectra, 1D NOESY does not show the residual signals caused by subtraction of two spectra obtained before and after radio wave irradiation, making the spectrum easier to analyze.
                  The interpretation method is similar to that of difference NOE: we check how other signals appear when the selectively excited proton signal is shown downward.
                  In example of ethyl crotonate, when proton A is selectively excited, positive NOEs are observed at B and C. Conversely, when proton C is excited, a positive NOE is observed only at A. These results also support the estimation that ethyl crotonate has a trans type stereochemistry. Thus, when determining stereochemistry with ambiguous spatial arrangements, it is important to measure 1D NOESY of the selective excitation of each part.

                  2D NOESY

                  2D NOESY is a method to observe interaction (NOE) between spatially close protons in a molecule as a two-dimensional spectrum. This experiment observes the appearance of how NOE changes (transient NOE) during the mixing time after temporarily changing the proton spin state. The obtained spectrum expressed the self-signals on a diagonal and correlated signals between spatially close protons. Since the 2D NOESY allows for comprehensive NOE correlation in the entire molecule, it is suitable for analysis of complicated structures and confirmation of entire signal assignment.
                  2D NOESY
                  From here, we will explain how to read 2D NOESY spectra. As shown in the above figure, when A and C, B and D are in close proximity to each other, such correlation signals appear. The data sliced at positions A and B (in blue dotted line) in X-axis direction, are equivalent to 1D NOESY spectra by selective excitation of A and B, respectively.
                  This figure shows 2D NOESY of ethyl crotonate. Looking at each sliced data, the signals at the selective excited part (in red) appear downward, while signals with NOE correlation (in black) appear upward (positive NOE).
                  When looking at the correlation signals in black, the following NOE correlations can be found:
                  A：B and C
                  B：A
                  C：A
                  D：E
                  E：D
                  In addition, focusing on the NOE correlations among A, B, and C, the results support the presence of the trans type conformation, consistent with the previously mentioned difference NOE and 1D NOESY results.

                  Easy guideline in selecting NOE measurement method

                  As we have explained, for an NOE measurement, it is possible to choose the method according to the purpose. We recommend that you begin with 1D NOESY which allows for easy condition setting and clear spectra to be obtained.
                  Target proton has been specified: 1D measurement
                  Want to see NOE across the molecule, or signal assignment is uncertain: 2D NOESY

                  Important factor for NOE measurement: Relaxation time

                  One of the most frustrating problems in NOE measurements is, without a doubt, "when no NOE signal is detected!" In such a case, please measure the longitudinal relaxation time (T1) of the target sample, first. Then, for difference NOE measurement, please set the irradiation time of the excitation pulse to be more than 5 times that of T1 of the target sample. Also, please set the mixing time with 1D/2D-NOESY, to be about 0.8 times that of T1 of the target sample.

                  Now, why do we need to consider the relaxation time of the target sample, for an NOE measurement? This is because NOE has a deep relationship with relaxation time, as NOE is a relaxation phenomenon based on the dipole interaction.
                  Here, we would like to provide a simple explanation about relaxation in NMR.
                  The above is the schematic diagram of energy levels of nuclear spin of spin number= 1/2 when it is placed in a static magnetic field. Nuclear spin takes up two energy states after undergoing Zeeman splitting by being affected by magnetic field. Stable state with low energy is called α state, while the one with high energy is called β state. When a radio wave having a frequency equivalent to this energy gap is irradiated, the spin in the α state absorbs the energy of radio wave and excited into the β state. When the spin number of the α state and the β state becomes the same by irradiation of a radio wave, energy absorption stops, which is called the saturation state. In the saturation state, the spin in the β state emits energy and returns to the α state, finally, it even returns to the thermal balanced state. The whole process is called relaxation. Then, a series of processes from excitation to relaxation, are called the NMR phenomenon that we are observing.
                  Two neighboring nuclear spins
                  The interaction works between two neighboring nuclear spins, which is the driving force for the relaxation explained earlier. In solution NMR, the dipole interaction is one of the major factors in promoting relaxation. Therefore, setting the parameter of relaxation time which has deep relationship with dipole interaction is an important key for successful NOE observation.

                  Cause and solution for undetectable NOE signals

                  The likely cause and action when NOE is not detected, are explained in the following 4 points.
                  1. Optimize sample adjustment/measurement conditions
                  2. Change molecular motion
                  3. Change resonance frequency
                  4. Change measurement method
                  First, check if 1. is optimized, and if the NOE is not observed, try 2 to 4.

                  1. Optimize sample adjustment/measurement conditions

                  Since the NOE signal is very weak, the result is greatly affected by the sample concentration and purity, and measurement condition setting.
                  • Concentration: if the concentration is too high, relaxation tends to occur between molecules, weakening the NOE.
                  • Caution against contamination of paramagnetic substances: dissolved oxygen and metal ions (Fe, Cu, etc.) promote relaxation, thus preventing NOE.
                  • Setting of irradiation/mixing times: Based on T1(longitudinal relaxation time), irradiation time of more than 5 times, mixing time of about 0.8 times are guidelines.

                  2. Change molecular motion

                  The intensity of NOE also depends on molecular motion. The following graph shows the relationship between NOE intensity and molecular motion.
                  This curve was theoretically brought from the relational expression of NOE intensity and dipole interaction.

                  The vertical axis expresses the NOE intensity, while the horizontal axis expresses the product of observation frequency ω multiplied by correlation time of the molecule tC. tC is the time required for a molecule to make a full rotation in solution and is a parameter expressing the motion of the molecule. Which means, the smaller the molecule is, the shorter the tC becomes. The larger the molecule is, the longer the tC becomes.

                  The left shows the region of low molecule where tC is short and the motion of molecule is fast. Here, a positive NOE is observed. On the other hand, the right shows the region of polymer where tC is long and the motion of the molecule is slow. Here, the negative NOE is observed. Which means, the graph indicates that NOE intensity greatly changes depending on the motion of the molecule.

                  What matters in performing measurement is that there is a region where NOE becomes zero. When the molecule is close to the region where the product of multiplication of observation frequency ω and correlation time of the molecule tC is 1, the NOE becomes very weak or the NOE is not observed.

                  Therefore, if NOE is not observable even if measurement conditions are reviewed with your instrument, it is possible that the product of multiplication of observation frequency ω and correlation time of the molecule tC is in this region.

                  In such a case, changing ω or tC is a possible choice. However, changing ω means changing the measurement magnetic field, and it may be difficult to try it at once if you hold only one instrument. Therefore, we suggest that you consider changing tC , which is, changing the factor that can affect tC(measurement temperature and viscosity of a solvent). We recommend that you change the measurement temperature, first.

                  3. Change resonance frequency

                  Next, I will explain the case where the observation frequency is changed, which is, where the measurement magnetic field is changed.

                  The above figure shows the magnetic field dependence of NOE intensity and correlation time tC .The vertical axis represents NOE intensity, while the horizontal axis represents correlation time tC. Each curve corresponds to a magnetic field from 90 MHz to 920 MHz. The curves shift to the left as the measurement magnetic field increases. If we focus on the tC at which the NOE becomes zero, we can see that the point at which the signal intensity becomes zero shifts to the region of low molecules (where the molecules are in fast motion) as the magnetic field is increased. This means that under the same measurement conditions, the signal intensity of positive NOE becomes weaker at higher magnetic fields. For example, it can be said that a molecule with zero NOE in a 600 MHz instrument may have a positive NOE observed in a 300 MHz instrument. In addition, for the case of a molecule with about 1000 molecular weight, the possibility is high that it can be in the region in a circle where NOEs are extremely small, so attention is needed.

                  4. Change the measurement method

                  If NOE is not observed after trying methods 1 through 3 introduced so far, a measurement method called ROESY is used. ROESY is a NOE measurement in a rotational coordinate system.
                  The above figure is the 1D NOESY and 1D ROESY spectra of gramicidin S measured at 90°C. At this temperature, the NOE of gramicidin S becomes nearly zero, but using ROESY allows the observation of correlation signals. The NOE observed in ROESY is referred to as ROE. The greatest advantage of ROESY is that, as illustrated in the schematic diagram, ROE is always positive and does not have a zero region. You might wonder, "Then why not just use ROESY from the beginning?" However, ROESY requires more careful parameter settings and tends to produce unwanted signals. Therefore, ROESY is better used when NOESY does not work well.

                  Frequently Asked Question about NOE Measurement

                  In difference NOE measurements, if the irradiation position is not set at the peak maximum, spin coupling effects can occur, causing changes in the signal shape. Therefore, the irradiation position should be set precisely at the peak maximum.
                  In difference NOE measurements, when multiplets more than doublets are selectively irradiated and if the irradiation position is shifted from the peak maximum, the signal shapes are changed. The two spectra above show difference NOE results when the methyl group protons of ethyl crotonate are irradiated. Positive NOE signals are observed at B and C. If the irradiation position is shifted to around the center ppm of signal A instead of the peak maximum, a large, asymmetric, residual-like signal appears, as shown in the dotted area of the top spectrum. This is due to spin coupling interactions with proton B. Always select the irradiation position at the peak maximum in difference NOE measurements.
                  This phenomenon is known as indirect NOE (three-spin effect), and in small molecules, it can be observed when protons are arranged nearly linearly.
                  Normally, small molecules undergoing rapid motion in solution exhibit positive NOE signals. However, signals may sometimes appear in the same direction as a negative NOE. For example, consider the spatial arrangement shown in the figure on the left, where protons A-B, and B-C are spatially close, but A-C are far apart. The figure on the right shows a 1D NOESY spectrum when proton A is selectively excited. Since A and B are close, a positive NOE is observed at B. However, an indirect NOE may also appear at C via B. This indirect NOE appears in the opposite direction to the positive NOE. It's important to note that this signal does not indicate that A-C are spatially close. This phenomenon is most likely to occur when the three protons are arranged nearly linearly in space, and it is known as the "three-spin effect."
                  When, three protons are arranged spatially special, NOE may not be observed even if the distances are close.
                  As a special case of the three spin effect, let me explain the triangle problem. As shown in the above figure, when three protons are arranged spatially special, this problem can occur.
                  When A is selectively excited, not only the distance between A and B, but also A and C are close. Thus, positive NOE is supposed to be seen between A and C, the forecasted spectra is the right in the above figure.
                  However, the positive NOE from A to C shown in orange and the indirect NOE via B shown in green can cancel each other out, resulting in no observable NOE. Theoretically, this cancellation occurs when the ratio of distances between each pair of protons is 1:1:1.26. In other words, even if the protons are spatially close, NOE may not be observed.

                  Reference

                  • Claridge, D.W.T.(2004), *Yūki kagaku no tame no kōbun Kainou NMR tekunikku* [High-resolution NMR techniques for organic chemistry] (T.Takeuchi & M. Nishikawa (Trans.) Kodansha Scientific.
                  • Fukushi, E. & Sohmiya H. (2007), *Korenara wakaru nijigen NMR* [Understanding 2D NMR made easy]. Kagaku Dojin.

                  Structural Analysis of Organic Compound Using 2D - NMR Spectrum

                  Structural Analysis of Organic Compound Using 2D - NMR Spectrum

                  In this column, we will explain the structural analysis of organic compound by using 2D-NMR spectrum.

                  Structural Analysis of one-dimensional NMR (1D-NMR)

                  One-dimensional NMR (1D-NMR) is the most basic measurement of NMR spectroscopy, in which the spectrum is displayed along a horizontal axis (chemical shift). As introduced in the previous column, information on chemical shift, integration ratio, and splitting pattern (coupling) is used to analyze the structure of an object. However, it can be difficult to perform structural analysis using only 1D-NMR data when the number of detected signals is large, when signals appear in overlapping positions, or when couplings are complex.
                  The two-dimensional (2D-NMR) spectral analysis method introduced in this column can be used extensively regardless of the object to be analyzed, since the basic sequence of steps is followed. In addition, by following the basic procedures, even beginners can mechanically perform structural analysis.

                  What is 2D-NMR?

                  2D-NMR is a method used to check a more detailed molecular structure than 1D-NMR. Since there are many 2D-NMR measurement methods, here, we introduce representative measurement methods.
                  Measurement Name What you can find out
                  COSY A method to observe coupling between neighboring same nuclides (frequent:1H/1H)
                  INADEQUATE A method to observe coupling between neighboring 13Cs
                  HMQC/HSQC A method to observe coupling of a directly coupled heterogeneous nuclei (frequent: 1H/13C)
                  HMBC/H2BC A method to observe the correlation signals of heterogeneous nuclei(frequent: 1H/13C) via 2-3 bonds
                  ADEQUATE A method to detect 13C-13C coupling by 1H observation
                  NOESY/ROESY A method to observe the correlation signals between 1Hs that are closely located(with NOE interaction)

                  Structural Analysis Using J Coupling Correlation

                  This time we introduce an example of structural analysis using "J Coupling Correlation" which is an interaction via chemical bonding. Structural analysis of an object is conducted by following the 4 steps below.
                  Structural Analysis Using J Coupling Correlation

                  In Step 1, we use a 1D-NMR spectrum of 13C and DEPT to determine and estimate the atomic group and functional group.

                  In Step 2, we use HMQC and 1D spectrum of 1H to find 13C and 1H that are directly bonded.

                  In Step 3, we use COSY to examine and locate which is the neighboring 1Hs.

                  By using information obtained in Step 2 and 3, substructures can be determined to some extent.

                  In Step 4, we use HMBC to determine the structure of the remaining parts, by considering the connection of 13C and 1H which are further apart.

                  Structural analysis example of C6H10O2

                  Now we will explain the structural analysis of a specific sample.

                  This time, we use a substance whose molecular formula C6H10O2 is only known and dissolve in heavy chloroform.

                  Step 1 13C (1D-NMR) & DEPT

                  In Step 1, we use a 1D-NMR spectrum of 13C and DEPT to determine and estimate atomic group and functional group. First, as shown in Fig. 1, we put a symbol on each signal in 1D-NMR spectrum of 13C. Starting with the signal on the right side of the spectrum, from the high-field side, add symbols A, B, C... and so on. The chemical shift of each signal is read to one decimal place. The read information is summarized in Table 1.

                  Fig. 1 13C Spectra of C6H10O2
                  Signal Chemical Shift
                  A 14.1 ppm
                  B 17.6 ppm
                  C 59.8 ppm
                  D 122.8 ppm
                  E 144.0 ppm
                  F 166.2 ppm
                  Table 1 13C Spectra Information

                  Next, we will confirm the results of the DEPT spectra. Since DEPT observes the carbon to which hydrogen is directly bonded, the series of the carbon atom of interest (the number of hydrogen directly bonded to the carbon of interest) is known. In other words, it is possible to identify atomic groups such as CH3, CH2, and CH. (DEPT cannot detect spectra of quaternary carbons.) DEPT provides three types of spectra, depending on the measurement parameters (DEPT135, DEPT90, and DEPT45).

                  Table 2 lists the signal appearance patterns in the three types of DEPT spectra. In DEPT135, the signals of CH3 and CH are detected upward, while the signal of CH2 appears downward (opposite phase). It is often possible to discriminate CH3 or CH from the chemical shift. In many cases, the DEPT135 measurement alone is sufficient. If discrimination by DEPT135 alone is difficult, measure DEPT90, in which only the signal of CH is detected.

                  Table 2 DEPT Signal Appearance Patterns

                  We will use the DEPT spectra to determine the atomic groups of the sample. As shown in Figure 2, we will discriminate the atomic groups of each signal by comparing the signal appearance patterns of the 1D-NMR spectrum of 13C and the DEPT spectrum.

                  -----
                  DEPT135・・・Upward signal: CH3 or CH, Downward signal: CH2
                  DEPT90・・・ Detectable signal : CH
                  Signal detected only in the 1D-NMR spectrum of 13C and not detected in the DEPT spectrum: quaternary carbon
                  -----

                  Using the information so far, we were able to determine that the atomic groups of each signal are, from right to left, A (CH3), B (CH3), C (CH2), D (CH), E (CH), and F (quaternary carbon).

                  Fig. 2 13C Spectra and DEPT Spectra of C6H10O2

                  The information so far is summarized in Table 3. This information is used to estimate the atomic groups and functional groups.
                  Signal Chemical Shift Atomic Group
                  A 14.1 ppm CH 3
                  B 17.6 ppm CH 3
                  C 59.8 ppm CH 2
                  D 122.8 ppm CH
                  E 144.0 ppm CH
                  F 166.2 ppm C

                  Table 3 13C Spectra Information (2)

                  Figure 3 shows the chemical shift table for 13C. At an approximate border of 100 ppm, the saturated carbon signals are appeared on the right and the unsaturated carbon signals on the left. We will compare the information summarized in Table 3 with the chemical shift table. First, if we look at D (122.8 ppm) and E (144.0 ppm), we see that they are in the region of unsaturated carbon, indicating that this CH is derived from unsaturated carbon. Next, if we look at F, the chemical shift value is 166.2 ppm, which is in the ester region. The molecular formula of this substance is C6H10O2, and since there are two Os, the quaternary carbon of F is presumed to be derived from the COO group.

                  Figure 3 13C Chemical Shift Table

                  The information so far is summarized in Table 4.
                  Signal Chemical Shift Atomic Group
                  A 14.1 ppm CH3
                  B 17.6 ppm CH3
                  C 59.8 ppm CH2
                  D 122.8 ppm CH=
                  E 144.0 ppm CH=
                  F 166.2 ppm COO

                  Table 4 13C Spectra Information (3)

                  Step 2 HMQC & 1H

                  In Step 2, we will use HMQC and 1D-NMR spectra of 1H to find directly bonded 13C and 1H combinations. HMQC will tell you the combination of 1H and 13C that are directly bonded. Spin couplings are written with a symbol, such as 1JCH. The number of bonds is written in the upper left corner of the J representing the spin coupling, and the nucleus to which it is bound is written in the lower right corner of the J.

                  Figure 4 shows an HMQC spectrum. In a 2D-NMR spectra, a high-resolution 1D-NMR spectrum is displayed at each axis; for HMQC, the 1H spectrum is displayed on the X-axis and the 13C spectrum on the Y-axis. In Step 2, the same symbols that were attached to each signal in the 13C spectrum in Step 1 are attached to the signals in the 13C spectrum on the Y-axis, with the upper side of the Y-axis representing the high-field side (small chemical shift) and the lower side representing the low-field side (large chemical shift).

                  Next, draw a line from the 13C signal on the Y-axis to the HMQC correlation signal and confirm which 1H is directly bonded to 13C. For example, if we focus on the 13C signal of C, we draw a line toward the side, and when the line hits the correlation signal, we draw a line up from there. The 1H signal that we have reached here is the counterpart directly bonded to signal C of 13C. When the corresponding 1H is found in this way, the 1H is marked with the same symbol as the counterpart 13C. Since it is the counterpart of the signal C of 13C, we will also put the symbol C on this 1H. All correlated combinations will be given a similar symbolization.

                  Fig.4 HMQC Spectra

                  Step 3 1H-1H COSY

                  In Step 3, we will use 1H-1H COSY to see which are the neighboring 1Hs. COSY shows the spin-coupled 1H connections. What can be observed mainly is the correlation between 1Hs via three couplings, as shown in Figure 5. In symbols, we denote this as 3JHH. As shown in Fig. 5, if 1Hs in a 3JHH relationship are lined up, we can follow the 1H connections one after another.

                  In COSY, in addition to the 3JHH, a 2JHH through two couplings and a remote 4JHH can also be observed.

                  However, the most important and necessary information is the correlation between 1Hs at the neighboring 13C, 3JHH.

                  Fig. 5 Correlation of 1Hs via Three Bonds

                  Fig. 6 shows the actual COSY spectra. COSY shows 1H spectra both on the X-axis and Y-axis.

                  In Step 1, we assigned a symbol to each 13C signal. In Step 2, we assigned a symbol to each 1H signal that is directly coupled to 13C using HMQC. In Step 3, we first assigned the same symbols to the signals in the 1H spectrum on the X and Y axes as we did in Step 2. We looked at the HMQC spectra we used earlier (Figure 4) and copied the symbols attached to the signals in the 1H spectra on the X-axis as they were.

                  Note that in Figure 6, the symbols are alphabetically ordered from the high-field side, but this just happened to be the case for this sample. The symbols on the 1H signal are not always in alphabetical order.

                  Also, in the COSY spectra, signals line up on the diagonal line (called diagonal signals) when the diagonal line is drawn. But these are not used as information for structural analysis. The off-diagonal signals are the COSY correlation signals.

                  We draw a line from the correlated signal toward the X- and Y-axes spectra and find the 1Hs that are spin-coupled to each other. For example, if we focus on the correlation signal circled in green, we find the 1H signal C on the X-axis and the 1H signal A on the Y-axis. Therefore, we can see that signals C and A are spin-coupled (neighboring) to each other. Once the counterpart is found, we add a symbol to the correlated signal. For example, C/A, to specify that they are 1H signals in a 3JHH relationship. Since the correlated signals of COSY appear in a line symmetric position with respect to the diagonal, we find the 3JHH counterpart in the same way for all correlated signals.

                  Fig. 6 COSY Spectra

                  Once the information on the correlated signals of COSY is available, a correlation table for each signal is created.

                  Table 5 is the correlation table for COSY. Write the symbols for the 1H signals in vertical and horizontal order, as per the spectrum of the data on the 1H-1HCOSY axis. (In the case of this sample, they happen to be arranged alphabetically, but you should look at the COSY spectra and list them in chemical shift order.) For example, if the correlated signals are C and A, mark the intersection of C and A. In this way, all correlated signals are entered in the COSY correlation table.

                  Table 5 COSY Correlation Table

                  Fig.7 shows the diagram of correlation signal of COSY.

                  In this sample, COSY correlation signal was observed between 1H of C and 1H of A.

                  The HMQC spectra also indicated that 1H of C and 13C of C are directly coupled. In the same way, 1H of A and 13C of A are directly coupled.

                  Therefore, COSY correlation signals between C and A can induce that 13C of C and 13C of A are neighboring. In other words, using the COSY information, we can indirectly find the neighboring 13C connections from the neighboring 1H connections.

                  Fig. 7 COSY Correlation Signals

                  The information that we have so far is the 13C spectrum information (Table 4) and the COSY correlation table (Table 5). From the COSY correlation table, we can see that the carbon atoms derived from the 13C signals A-C, B-E, and D-E are neighboring to each other. Combined with the information from the 13C spectrum, when we rewrite the symbols as atomic groups, we have A-C : "CH3-CH2-", B-E-D : "CH3-CH=CH-", and F : "COO" in Step 1. Therefore, we know that this compound is composed of the following three substructures.

                  ----
                  Substructure 1：CH3-CH2-　・・・ A-C
                  Substructure 2： CH3-CH=CH-　・・・ B-E-D
                  Substructure 3： COO　・・・ F
                  ----

                  Next, we will consider what kind of molecule these will make by connecting each substructure (Figure 8). We will list all possible molecular structures from the combination of the three substructures. When considering molecular structures, it is easier to focus on the substructure containing CH3 because CH3 is located at the end of the structure. In this case, there are two possible structures. Firstly, Substructures 1 and 2 are found to be the ends of the molecular structure because they contain CH3.And since 1 and 2 are located at the ends, we can predict that substructure 3 is sandwiched between 1 and 2. The different orientations of substructure 3 allowed us to create two different inferred structures (I, II). The orientation of the COO can be used to determine which inferred structure is more reasonable. Therefore, HMBC measurements are performed to confirm the long-range spin coupling with respect to the COO.

                  Fig. 8 Combination of Three Substructures

                  Step 4 HMBC

                  In Step 4, we will consider long-range spin coupling between 13C and 1H by using HMBC.

                  In HMBC, we can observe the correlations of 2JCH through two bonds or 3JCH through three bonds, as shown in Figure 9.

                  Fig. 9 CH Correlation through 2 or 3 Bonds

                  Fig. 10 is the actual spectra of HMBC. The HMBC axes are the same as HMQC's case, 1H spectra on X-axis and 13C spectra on Y-axis. In Step 4, we will put the same symbol that we assigned for HMQC spectra in Step 2, for each signal of a 1D-NMR spectrum on the X and Y axes.

                  Next, we draw lines from the correlation signals to the X- and Y-axis spectra to find the spin-coupled 13C and 1H combinations. Here, the two horizontally-lined up signals circled in orange are the signals of 1JCH, a direct coupling of 1H and 13C. Since these are remnant signals, they are not observed in all direct couplings. As the direct couplings have already been observed by HMQC, it is not necessary to focus on them here. In the HMBC spectrum, only the long-range information is read, ignoring the direct coupling signal. For example, if we focus on the correlation signal circled in green, we can see that 13C of C and 1H of A are long-range spin coupled to each other, since tracing to Y-axis results in C and to X-axis results in A.

                  Once the counterpart is known, add a symbol to the correlation signal, e.g., A/C, to indicate that it is a long-range spin-coupled 1H and 13C of 2JCH or 3JCH. For all correlation signals, do the same to find a long-range spin-coupling counterpart and mark the correlation signal with a symbol. Once you have written out the information for the HMBC correlation signals, create a correlation table.

                  Fig. 10 HMBC Spectra

                  Table 6 is the correlation table for HMBC. We write the symbol for the 1H signal horizontally and the symbol for the 13C signal vertically, as per the spectrum. (Note that the symbols for the 1H signals are not necessarily in alphabetical order.) Correlation signals for the HMBC spectra will be filled in. For example, if the correlation signal is 13C for C and 1H for A, mark the intersection of C for 13C and A for 1H in the correlation table. In this way, all correlation signals are entered in the HMBC correlation table.

                  Table 6 HMBC Correlation Table
                  We use the information in the HMBC to connect the substructures.
                  Look at the HMBC correlation table (Table 7) that you filled out earlier. In the correlation signal marks, bonds that have already been analyzed by COSY in Step 3 are marked with ○, and bonds that were found for the first time in HMBC are marked with ●. The bond that was found for the first time in HMBC is the COO correlation for F. This indicates that F is a long-range spin couplings with C, D, and E.
                  Table 7 HMBC Correlation Table (2)

                  We will look at the long-range correlations of F-C, F-D, and F-E to consider which direction is correct for the COO to be attached, among the inferred structures I and II. (Figure 11).

                  First, in inferred structure I, F's 13C and C's 1H have three bonds "3JCH", ; F's 13C and D's 1H have two bonds "2JCH", ; and F's 13C and E's 1H have three bonds "3JCH".

                  Next, let us look at the inferred structure II. The 1H of 13C and C in F is "2JCH" with two bonds, the 1H of 13C and D in F is "3JCH" with three bonds, and the 1H of 13C and E in F is "4JCH" with four bonds.

                  Since 4JCH is not likely to be observed, we can expect that the inferred structure I is a reasonable structure.

                  Fig. 11 Comparison between Inferred Structures I and II

                  Finally, the inferred structure I is checked against the information in the 1D-NMR spectrum of 13C to confirm if it is really correct. In the inferred structure I, CH2 of the symbol C is bonded to oxygen. And the 13C chemical shift of this C was 59.8 ppm (Table 1).

                  The 13C chemical shift table for CH2 (Table 8) shows that normal CH2 is observed at 20-45 ppm, while CH2 bonded to oxygen is observed at 40-70 ppm with a lower field shift.

                  From this fact, we can conclude that "Structure I is correct".

                  Chemical Shift
                  - CH2 - 20 -45 ppm
                  - CH2O - 40 - 70 ppm

                  Table 8 13C Chemical Shift for CH2
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