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High‐speed 4‐dimensional scanning transmission electron microscopy using compressive sensing techniques

Abstract Here we show that compressive sensing allows 4‐dimensional (4‐D) STEM data to be obtained and accurately reconstructed with both high‐speed and reduced electron fluence. The methodology needed to achieve these results compared to conventional 4‐D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide dataset shows that it is possible to recover over 25 dB peak signal‐to‐noise ratio in the recovered phase using 0.3% of the total data. Lay abstract : Four‐dimensional scanning transmission electron microscopy (4‐D STEM) is a powerful technique for characterizing complex nanoscale structures. In this method, a convergent beam electron diffraction pattern (CBED) is acquired at each probe location during the scan of the sample. This means that a 2‐dimensional signal is acquired at each 2‐D probe location, equating to a 4‐D dataset. Despite the recent development of fast direct electron detectors, some capable of 100kHz frame rates, the limiting factor for 4‐D STEM is acquisition times in the majority of cases, where cameras will typically operate on the order of 2kHz. This means that a raster scan containing 256^2 probe locations can take on the order of 30s, approximately 100‐1000 times longer than a conventional STEM imaging technique using monolithic radial detectors. As a result, 4‐D STEM acquisitions can be subject to adverse effects such as drift, beam damage, and sample contamination. Recent advances in computational imaging techniques for STEM have allowed for faster acquisition speeds by way of acquiring only a random subset of probe locations from the field of view. By doing this, the acquisition time is significantly reduced, in some cases by a factor of 10‐100 times. The acquired data is then processed to fill‐in or inpaint the missing data, taking advantage of the inherently low‐complex signals which can be linearly combined to recover the information. In this work, similar methods are demonstrated for the acquisition of 4‐D STEM data, where only a random subset of CBED patterns are acquired over the raster scan. We simulate the compressive sensing acquisition method for 4‐D STEM and present our findings for a variety of analysis techniques such as ptychography and differential phase contrast. Our results show that acquisition times can be significantly reduced on the order of 100‐300 times, therefore improving existing frame rates, as well as further reducing the electron fluence beyond just using a faster camera.

Robinson, Alex W.↗

Critical Evaluation of a Novel Analysis Technique for Assessment of Printed Circuit Heat Exchangers in High-Temperature Nuclear Service

Application of printed circuit heat exchangers (PCHEs) to very high-temperature reactors (VHTRs) requires mechanical performance assessment methodologies. The PCHE morphology consists of thousands of millimeter-scale channels, for enhanced thermal efficiency, enclosed in a meter-scale PCHE core. PCHE geometry under thermomechanical creep-fatigue transients results in multi-axial interactions between its different segments, such as channeled core, walls, and headers. These global-level interactions influence the local channel-level responses. Hence, developing a PCHE performance assessment methodology, following the ASME Code, Section III, Division 5 provisions, is a critical gap to be filled. There is no analysis or design methodology available in ASME Code to assess a PCHE for its global and local level performances under high temperature and pressure loadings. This paper critically evaluates a recently proposed two-step analysis technique to estimate global interactions and local channel-level responses of PCHEs. In this novel analysis technique, the channeled PCHE core is replaced with orthotropic solid blocks of representative stiffness properties for the global thermomechanical analysis. Here, subsequent channel scale submodel analysis with detailed channel geometry, loading, and elastic-perfectly plastic (EPP) material model estimates the local responses for PCHE performance assessment. This paper critically evaluates this novel technique for its effectiveness in PCHE performance assessment. Finite element (FE) models imitating various analysis issues are developed, and FE analysis results are scrutinized. An important outcome of this study is the validation of the novel two-step PCHE analysis technique for application to the performance assessment of PCHEs in VHTRs.

42 ENGINEERING↗

Instrumentation and Techniques in High Energy Physics

This book provides an introduction of some of the technology and techniques of modern particle physics. Each chapter is a deep dive into the relevant subject, which includes silicon pixel detectors, plastic scintillator in a high radiation environment, Cerenkov detectors, particle jet identification, noble gas neutrino detectors, and machine learning. The target audience is graduate students and more senior researchers who wish to learn a new technology or technique. The text pedagogical in nature and each chapter is a standalone treatment of a specific topic. The coverage focuses on state-of-the-art techniques, rather than describing the technology's history. Written by acknowledged experts in the subject matter, Instrumentation and Techniques in High Energy Physics, is an important addition to the library of any particle physicist.

Lincoln, Don↗

The Application of Machine Learning Techniques to Meteorological Forecasting

Fog and inland-penetrating sea-breezes occur often at SRS and have a strong impact on site operations. Site personnel therefore require accurate forecasts of these events, but both are difficult to forecast using traditional techniques. Our goal is to apply machine learning (ML) techniques to the problem of forecasting fog and the sea breeze at the Savannah River Site. We apply several such techniques - decision trees, regression, and a series of classification/regression techniques – and train them using the large datasets collected by our group at SRS and from external organizations that maintain databases of regional meteorological variables.

54 ENVIRONMENTAL SCIENCES↗

Uniform Beam Simulation Technique for Beam Scans and Machine Learning Studies at Fermilab

Fermilab's neutrino facilities, including NuMI and the upcoming LBNF, use proton beams to produce positively and negatively charged pions and kaons. Detailed simulations are necessary to study particle interactions and beam propagation. To efficiently analyze beam scan effects, we propose a technique to generate multiple simulation samples with high statistics. These samples can be used to develop beamline simulation based machine learning applications. In this technique, we generate a uniformly distributed single simulation data sample. We calculate Gaussian weights for each beam configurations and apply them to post-processing measurements. In this poster, we demonstrate the proposed simulation technique. This technique reduces simulation time and computing resources significantly.

Wickremasinghe, Athula↗

In-Process Monitoring and Structural Health Monitoring of Large-Scale Additive Manufacturing Using Acoustic Emission Technique

ORNL collaborated with MISTRAS Group, Inc. to investigate acoustic emission (AE) as a structural health monitoring (SHM) method for large-scale additive manufacturing (AM). Large-scale AM is being adapted as method of producing large structures in a short lead time and cost-effective way. With the growing advancement in AM techniques and application, machine monitoring and part qualification is highly needed. There has been leading research focused on the manufacturing, feedstock material but minimum research on the SHM, defect detection, and nondestructive evaluation (NDE) for AM. Scanning large structure using conventional nondestructive testing (NDT) techniques, such as ultrasound or X-ray, and searching for potential defects can be very time consuming, challenging and cost prohibitive. AE is a passive technique that can be used to monitor and locate defect progression in large structure by distributing group of sensors around the part. This project utilized AE technique and system manufactured/designed by MISTRAS Group to monitor large-scale AM equipment (i.e. Big Area Additive Manufacturing (BAAM) system located at the Oak Ridge National Laboratory – Manufacturing Demonstration Facility (ORNL-MDF) and the printed parts it produces. The AE system provided valuable insight on defect development/progression during and post-printing process.

36 MATERIALS SCIENCE↗

Synchrotron-based techniques for characterizing STCH water-splitting materials

Understanding the role of oxygen vacancy–induced atomic and electronic structural changes to complex metal oxides during water-splitting processes is paramount to advancing the field of solar thermochemical hydrogen production (STCH). The formulation and confirmation of a mechanism for these types of chemical reactions necessitate a multifaceted experimental approach, featuring advanced structural characterization methods. Synchrotron X-ray techniques are essential to the rapidly advancing field of STCH in part due to properties such as high brilliance, high coherence, and variable energy that provide sensitivity, resolution, and rapid data acquisition times required for the characterization of complex metal oxides during water-splitting cycles. X-ray diffraction (XRD) is commonly used for determining the structures and phase purity of new materials synthesized by solid-state techniques and monitoring the structural integrity of oxides during water-splitting processes (e.g., oxygen vacancy–induced lattice expansion). X-ray absorption spectroscopy (XAS) is an element-specific technique and is sensitive to local atomic and electronic changes encountered around metal coordination centers during redox. While in operando measurements are desirable, the experimental conditions required for such measurements (high temperatures, controlled oxygen partial pressures, and H 2 O) practically necessitate in situ measurements that do not meet all operating conditions or ex situ measurements. Here, we highlight the application of synchrotron X-ray scattering and spectroscopic techniques using both in situ and ex situ measurements, emphasizing the advantages and limitations of each method as they relate to water-splitting processes. The best practices are discussed for preparing quenched states of reduction and performing synchrotron measurements, which focus on XRD and XAS at soft (e.g., oxygen K-edge, transition metal L-edges, and lanthanide M-edges) and hard (e.g., transition metal K-edges and lanthanide L-edges) X-ray energies. The X-ray absorption spectra of these complex oxides are a convolution of multiple contributions with accurate interpretation being contingent on computational methods. The state-of-the-art methods are discussed that enable peak positions and intensities to be related to material electronic and structural properties. Through careful experimental design, these studies can elucidate complex structure–property relationships as they pertain to nonstoichiometric water splitting. A survey of modern approaches for the evaluation of water-splitting materials at synchrotron sources under various experimental conditions is provided, and available software for data analysis is discussed.

08 HYDROGEN↗

A Review of Basic Energy Reconstruction Techniques in Liquid Xenon and Argon Detectors for Dark Matter and Neutrino Physics Using NEST

Detectors based upon the noble elements, especially liquid xenon as well as liquid argon, as both single- and dual-phase types, require reconstruction of the energies of interacting particles, both in the field of direct detection of dark matter (weakly interacting massive particles WIMPs, axions, etc.) and in neutrino physics. Experimentalists, as well as theorists who reanalyze/reinterpret experimental data, have used a few different techniques over the past few decades. In this paper, we review techniques based on solely the primary scintillation channel, the ionization or secondary channel available at non-zero drift electric fields, and combined techniques that include a simple linear combination and weighted averages, with a brief discussion of the application of profile likelihood, maximum likelihood, and machine learning. Comparing results for electron recoils (beta and gamma interactions) and nuclear recoils (primarily from neutrons) from the Noble Element Simulation Technique (NEST) simulation to available data, we confirm that combining all available information generates higher-precision means, lower widths (energy resolution), and more symmetric shapes (approximately Gaussian) especially at keV-scale energies, with the symmetry even greater when thresholding is addressed. Near thresholds, bias from upward fluctuations matters. For MeV-GeV scales, if only one channel is utilized, an ionization-only-based energy scale outperforms scintillation; channel combination remains beneficial. We discuss here what major collaborations use.

argon↗

Advanced Characterization of Solid-State Battery Materials Using Neutron Scattering Techniques

Advanced batteries require advanced characterization techniques, and neutron scattering is one of the most powerful experimental methods available for studying next-generation battery materials. Neutron scattering offers a non-destructive method to probe the complex structural and chemical processes occurring in batteries during operation in truly in situ/in operando measurements with a high sensitivity to battery-relevant elements such as lithium. Neutrons have energies comparable to the energies of excitations in materials and wavelengths comparable to atomic distances in the solid state, thus giving access to study structural and dynamical properties of materials on an atomic scale. In this review, a broad overview of selected neutron scattering techniques is presented to illustrate how neutron scattering can be used to gain invaluable information of solid-state battery materials, with a focus on in situ/in operando methods. These techniques span multiple decades of length and time scales to uncover the complex processes taking place fundamentally on the atomic scale and to determine how these processes impact the macroscale properties and performance of functional battery systems. This review serves the solid-state battery research community by examining how the unique capabilities of neutron scattering can be applied to answer critical and unresolved questions of materials research in this field. A thorough and broad perspective is provided with numerous practical examples showing these techniques in action for battery research.

25 ENERGY STORAGE↗

ARCANE Reweighting: A Monte Carlo Technique to Tackle the Negative Weights Problem in Collider Event Generation

Negatively weighted events, which appear in the Monte Carlo (MC) simulation of particle collisions, significantly increases the computational resource requirements of current and future collider experiments. This paper introduces and theoretically discusses an MC technique called ARCANE reweighting for reducing or eliminating negatively weighted events. The technique works by redistributing (via an additive reweighting) the contributions of different pathways within an event generator that lead to the same final event. The technique is exact and does not introduce any biases in the distributions of physical observables. A companion paper demonstrates the technique for a physics example.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Techniques for improving operand caching

A technique for determining whether a register value should be written to an operand cache or whether the register value should remain in and not be evicted from the operand cache is provided. The technique includes executing an instruction that accesses an operand that comprises the register value, performing one or both of a lookahead technique and a prediction technique to determine whether the register value should be written to an operand cache or whether the register value should remain in and not be evicted from the operand cache, and based on the determining, updating the operand cache.

97 MATHEMATICS AND COMPUTING↗

Preliminary report on applications of machine learning techniques to the Nevada play fairway analysis

We are applying machine learning (ML) techniques, including training set augmentation and artificial neural networks, to mitigate key challenges in the Nevada play fairway project. The study area includes ~85 active geothermal systems as potential training sites and >12 geologic, geophysical, and geochemical features. The main goal is to develop an algorithmic approach to identify new geothermal systems in the Great Basin region. Major objectives include: 1) integrate ML techniques into the geothermal community; 2) develop open community datasets, whereby all play fairway and ML datasets and algorithms are publicly released and available for modification by various user groups; 3) identify data acquisition targets with high value for future work; 4) identify new signatures to detect blind geothermal systems; and 5) foster new capabilities for characterizing subsurface temperature and permeability. Initially, ML techniques are being applied to the same play fairway datasets and workflow. ML will then be applied to both enhanced and additional datasets, with modification of the PFA workflow to incorporate the new datasets. Finally, ML will be applied to define new workflows using the enhanced and additional datasets. An algorithmic approach that empirically learns to estimate weights of influence for diverse parameters can potentially scale and perform better than the play fairway analysis. Initial work on this project has involved 1) evaluating potential positive and negative training sites, 2) transformation of datasets into formats suitable for ML, and 3) initial development and testing of ML techniques.

58 GEOSCIENCES↗

Molten Salt Sampling Techniques and Analytical Approaches

Recent global interest in pyroprocessing and molten salt reactors has brought salt sampling methods and techniques back to the forefront of nuclear safeguards concerns. Issues with uranium supplies have also encouraged various countries to pursue advanced nuclear fuel cycles. Tracking nuclear material in molten salt has proven to be a challenge and updating molten salt sampling will greatly help in this endeavor. Molten salt is problematic to sample due to salt stratification, lack of homogeneity, solids, and difficulty with hot cell adaptations. Various salt sampling techniques have been used since before the 1960s including surface, spoon/spatula, and bar solidification. Since then, new types of sampling techniques have been developed to improve sampling results. These include rod/dip, pipet, suction, filtered sampling along with devices such as the Valve Core Sampler and the Multi-Level Sampler. These different approaches are being analyzed and improved upon along with developing requirements for an improved salt sampling device. Work continues to develop salt samplers that are more robust, easier to segment, collect at a specific depth, can work with filters, and can collect fines. Sampling parameters are also being narrowed in terms of stirring, settling time, filtration, depth, etc. In the future, we hope to address deficiencies for process control and nuclear material accountancy control by determining the best way to collect samples that minimizes contaminants and is representative. A compilation of salt sampling approaches, analyses techniques, and an evaluation of findings will be presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Novel Technique for Distributed Measuring of Strain in the Vadose Zone

Characterizing water content and pressure changes in the vadose zone is important to understanding a variety of geologic processes, ranging from permeability, to evapotranspiration, and aquifer recharge. Changes in water content, or pressure, cause strain in the solid porous medium of the vadose zone, and it is possible that measuring those strains could be used a characterization tool. The Coherence-length-gated Microwave Photonics Interferometry (CMPI) technique measures strain at high resolution along many intervals defined by pairs of reflectors distributed along an optical fiber. This technique has recently been developed at Clemson University, and it has the spatial, and temporal resolution to characterize the strains that are expected to occur with hydrologic changes in the vadose zone. However, the technique has never been used to measure strain in porous media, so its capabilities remain uncertain. The objective of this thesis is to evaluate the ability of using CMPI to measure strain changes in the vadose zone. The research approach consists of conducting laboratory tests using a column filled with sand that was subjected to changes in water content and pressure. An optical fiber with CMPI reflectors was deployed in a high surface area ribbon and used to measure strain along the axis of the column. The column was made from 8-inch, Schedule 40 PVC pipe (75 cm tall, 20 cm inner diameter) and filled with medium-grained sand (K = 2.5x10-6 m/s, porosity = 0.28, Coefficient of Uniformity = 2, van Genuchten (n = 4.34 and  = 0.00039 m-1), Young’s Modulus = 18 – 47 MPa). Five pressure and four temperature sensors attached to probes inserted into the wall. The optical fiber includes five reflectors spaced 10 cm apart on the inside and outside of the column along the vertical axis. Strain measurements are made between pairs of reflectors. The reflectors are created in 250-micron-diameter acrylate-coated single mode Corning SMF28e+ optical fiber using a femtosecond laser. The optical fiber was laminated between two pieces of polyester film creating a large surface area to transfer strain from the porous media to the optical fiber. The experiments were conducted by filling the column from the bottom or infiltrating water from the top. The water was allowed to equilibrate to room temperature prior to each test in order to limit thermoelastic strain. Five injection tests with a rate of 250 ml/min and three infiltration tests at varying rates were conducted, and the results show patterns of strain and pressure are generally similar. Hydrologic conditions define three zones based on the pressure magnitude and distribution. 1.) Ambient Zone where the pressure heads are quasi-static and the pressure gradient is roughly unity (head gradient of zero). This is the uppermost zone and is characterized by negative pressures. 2.) Transition Zone where the pressures increase from ambient to zero, are changing relatively rapidly and the pressure gradient is relatively steep (pressure head gradients of 2). The Transition zone is 10 to 15 cm thick. 3.) Positive Pressure Zone where the pressure is positive, the rate of change is slower than in the transition zone and the gradient is flatter (pressure head gradient 1.1 to 1.2). This is the lowest zone in the column. Injection of water causes the pressure to increase and the three zones to move upward. The Transition zone moves at a rate of approximately 0.0002 m/s +/- .00005, according to analyses of pressure profiles. This is the same as the average velocity of the water calculated as volumetric flux/effective porosity =5.4x10-5 m/s/0.28. Strain signals in the range of 10s  were observed with a noise level of generally less than 0.1  (signal to noise ratio of greater than 100) during injection and drainage. The spatial and temporal distributions of strain caused by injection depend on the location of the moving pressure zones. The locations of the different pressure zones were determined from pressure profiles at different times and these data were transferred to strain time series. This showed that strain in the Ambient pressure zone is either unchanged or slightly compressive, whereas strain in Transition zone is tensile and roughly proportional to the pressure change, and strain ranges from tensile to compressive in the Positive Pressure zone. In general, the strain is variable at the top of the Positive Pressure zone, but it appears to be consistently tensile lower in the zone. The spatial distribution of strain causes three distinct stages in the strain times series measured between pairs of CMPI reflectors. The strain is unchanged or slightly compressive during Stage 1, it increases (positive strain is tensile) approximately linearly at a rate of 0.02 to 0.03 μ/s during the Stage 2, and then flattens out in Stage 3. The strain increases again during Stage 4 of the time series. The pressure also changes in stages. It is unchanged during Stage 1 and then increases relatively rapidly at a rate of between 4 and 10 Pa/s during Stage 2 and continues to increase during Stages 3 and 4, but at a rate slightly slower than during Stage 2 (from 2.5 to 3.5 Pa/s). The rates of pressure and strain change are consistent with basic analyses. The rate of pressurization is similar to the calculated velocity of flow in the saturated zone, and this is similar to the measured velocity of the strain increase. The ratio of the pressurization rate and strain rate during Stage 2 (2.5 (Pa/s) /0.03 (μ/s)) is 80 MPa, which is approximately equal to the upper range expected considering the uniaxial compression and the Young’s Modulus of the sand. An interesting effect occurs when the upper surface of the sand becomes saturated. Significant compression (several 10s of ) occurs as the pressure and saturation increase at the upper surface. Compression occurs throughout the column, but the effect is greatest at the top of the column. The rate of compression is fastest slightly before ponding occurs, but it slows markedly and nearly stops when water starts to accumulate at the surface (ponding). This effect reverses when the surface of the sand is drained, resulting in tension throughout the column. The compression caused by this effect can be as large or larger than the tensile strain that accumulated during filling. This effect was unexpected because increasing pressure is normally associated with tensile strain. Nevertheless, this effect was observed consistently in all tests where the pressure changes at the upper surface, including tests where water was injected from below or infiltrated from above. This effect behaves as if the pore pressure at the upper surface of the sand exerts a normal force on the boundary (increasing pore pressure exerts a downward compression on the boundary). The results of these laboratory experiments indicate that CMPI can measure strain caused by fluid pressure changes in the vadose zone with a signal to noise ratio of 100 or more. Injection and drainage cause a strain signal that is complex, but repeatable. The magnitudes of the strain signal are consistent with magnitudes that are expected based on poroelastic calculations using independently measured properties of the sand. These results indicate that the CMPI technique with an optical fiber laminated in a polyester ribbon generates data that represent the strain distribution during hydrologic processes of imbibition and drainage in variably saturated sand. This suggests that distributed strain measurements using CMPI could be a viable approach for evaluating processes in the vadose zone, laying the groundwork for future field implementation.

47 OTHER INSTRUMENTATION↗

Advanced control techniques for modern inertia based inverters

In this research three artificial intelligent (AI)-based techniques are proposed to regulate the voltage and frequency of a grid-connected inverter. The increase in the penetration of renewable energy sources (RESs) into the power grid has led to the increase in the penetration of fast-responding inertia-less power converters. The increase in the penetration of these power electronics converters changes the nature of the conventional grid, in which the existing kinetic inertia in the rotating parts of the enormous generators plays a vital role. The concept of virtual inertia control scheme is proposed to make the behavior of grid connected inverters more similar to the synchronous generators, by mimicking the mechanical behavior of a synchronous generator. Conventional control techniques lack to perform optimally in nonlinear, uncertain, inaccurate power grids. Besides, the decoupled control assumption in conventional VSGs makes them nonoptimal in resistive grids. The neural network predictive controller, the heuristic dynamic programming, and the dual heuristic dynamic programming techniques are presented in this research to overcome the draw backs of conventional VSGs. The nonlinear characteristics of neural networks, and the online training enable the proposed methods to perform as robust and optimal controllers. The simulation and the experimental laboratory prototype results are provided to demonstrate the effectiveness of the proposed techniques.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Smaller and faster: a review of conventional and nanocalorimetry techniques for determining thermophysical properties of nuclear materials

Thermal analysis of nuclear materials is critical for the advancement of nuclear technology. The heat effects associated with heat capacity, phase transformation, and radiation damage can be measured with conventional calorimeters. However, conventional calorimetric techniques are often restricted in terms of heating rate and sample mass, especially when studying the limited amounts of materials subject to extreme conditions. In this review, we summarize conventional calorimetric studies of critical thermophysical and thermochemical properties of pure actinide metals (U, Np, Am, Pu), fast reactor metallic fuel alloy systems (U–Zr, U–Pu–Zr, Pu–U, Pu–Zr), and actinide oxides that are primary constituents or transmutation products in light water reactor fuel rods (U–O, Np–O, Am–O, Pu–O, Pu–U–O). Adiabatic and drop calorimetry have been the primary techniques used for these studies, however the development of fast scanning calorimetry using micro-electro-mechanical-based systems allows determination of thermodynamic properties from smaller sample masses. We report recent investigations that leverage the fast heating rates of nanocalorimetry by itself or combined with other characterization techniques. Furthermore, we then discuss opportunities for nanocalorimetry to provide solutions to some of the technical challenges inherent in thermal analysis of nuclear materials, namely a reduction in sample activity, emulating heating transients, investigation of phase evolution in irradiated samples, and characterization of radiation damage evolution. Nanocalorimetry has the potential to significantly advance the understanding of thermophysical properties in nuclear materials and thus accelerate the development of nuclear technology.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Unlocking the secret of lignin-enzyme interactions: Recent advances in developing state-of-the-art analytical techniques

Bioconversion of renewable lignocellulosics to produce liquid fuels and chemicals is one of the most effective ways to solve the problem of fossil resource shortage, energy security, and environmental challenges. Among the many biorefinery pathways, hydrolysis of lignocellulosics to fermentable monosaccharides by cellulase is arguably the most critical step of lignocellulose bioconversion. In the process of enzymatic hydrolysis, the direct physical contact between enzymes and cellulose is an essential prerequisite for the hydrolysis to occur. However, lignin is considered one of the most recalcitrant factors hindering the accessibility of cellulose by binding to cellulase unproductively, which reduces the saccharification rate and yield of sugars. This results in high costs for the saccharification of carbohydrates. The various interactions between enzymes and lignin have been explored from different perspectives in literature, and a basic lignin inhibition mechanism has been proposed. However, the exact interaction between lignin and enzyme as well as the recently reported promotion of some types of lignin on enzymatic hydrolysis is still unclear at the molecular level. Multiple analytical techniques have been developed, and fully unlocking the secret of lignin-enzyme interactions would require a continuous improvement of the currently available analytical techniques. This review summarizes the current commonly used advanced research analytical techniques for investigating the interaction between lignin and enzyme, including quartz crystal microbalance with dissipation (QCM-D), surface plasmon resonance (SPR), attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, atomic force microscopy (AFM), nuclear magnetic resonance (NMR) spectroscopy, fluorescence spectroscopy (FLS), and molecular dynamics (MD) simulations. Interdisciplinary integration of these analytical methods is pursued to provide new insight into the interactions between lignin and enzymes. Finally, this review will serve as a resource for future research seeking to develop new methodologies for a better understanding of the basic mechanism of lignin-enzyme binding during the critical hydrolysis process.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring battery material failure mechanisms through synchrotron X-ray characterization techniques

Rechargeable battery cycling performance and related safety have been persistent concerns. Here, it is crucial to decipher the capacity fading induced by electrode material failure via a range of techniques. Among these, synchrotron-based X-ray techniques with high flux and brightness play a key role in understanding degradation mechanisms. In this comprehensive review, we summarized recent advancements in degradation modes and mechanisms that revealed by synchrotron X-ray methodologies. Subsequently, an overview of X-ray absorption spectroscopy and X-ray scattering techniques are introduced for the characterizing failure phenomena at local coordination atomic environment and long-range order crystal structure scale, respectively. At last, we envision the future of material failure mechanism exploration.

25 ENERGY STORAGE↗