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DOE OSTI2021

In Operando Angle‐Resolved Photoemission Spectroscopy with Nanoscale Spatial Resolution: Spatial Mapping of the Electronic Structure of Twisted Bilayer Graphene

To pinpoint the electronic and structural mechanisms that affect intrinsic and extrinsic performance limits of 2D material devices, it is of critical importance to resolve the electronic properties on the mesoscopic length scale of such devices under operating conditions. Herein, angle‐resolved photoemission spectroscopy with nanoscale spatial resolution (nanoARPES) is used to map the quasiparticle electronic structure of a twisted bilayer graphene device. The dispersion and linewidth of the Dirac cones associated with top and bottom graphene layers are determined as a function of spatial position on the device under both static and operating conditions. The analysis reveals that microscopic rotational domains in the two graphene layers establish a range of twist angles from 9.8° to 12.7°. Application of current and electrostatic gating lead to strong electric fields with peak strengths of 0.75 V/μm at the rotational domain boundaries in the device. These proof‐of‐principle results demonstrate the potential of nanoARPES to link mesoscale structural variations with electronic states in operating device conditions and to disentangle such extrinsic factors from the intrinsic quasiparticle dispersion.

Majchrzak, Paulina↗

DOE OSTI2022

The bamboo delignification saturation point in alkaline hydrogen peroxide pretreatment and its association with enzymatic hydrolysis

A delignification saturation point (DSP) was observed for bamboo alkaline hydrogen peroxide pretreatment (AHP). Lignin removal was increased from 52.23% to ~70% when increasing H 2 O 2 dosage from 0% to 2% at the optimum pH, but it cannot be further reinforced as increasing the H 2 O 2 . With partial lignin preserved, the glucan hydrolysis yield was found to have a ceiling of ~80%. This work indicated a strong association between enzymatic digestibility and lignin removal. Anatomical analysis by fluorescence microscope and confocal Raman microscope revealed that the undegradable lignin was mainly existing in the cell corner of sclerenchyma fibers, causing the DSP in the bamboo AHP. Finally, the residual lignin in pretreated bamboo was characterized with GPC, HSQC NMR, and 31 P NMR, which revealed the nature of DSP. This study could help to understand the lignin modification during the AHP and further contribute to the establishment of a chemical-saving biorefinery.

09 BIOMASS FUELS↗

DOE OSTI2026

Physics-informed machine learning exploration of Na storage mechanisms in disordered carbon

Sodium-ion batteries are a cost-effective, sustainable alternative to lithium-ion systems for large-scale energy storage. However, optimizing sodium storage in carbon-based anodes with microstructural complexity and atomic disorder remains a major challenge. The intrinsic inhomogeneity of these materials produces diverse local environments, making it difficult for conventional methods to predict and control ion dynamics. Hard carbon (HC) anodes, composed of ranges of ordered-to-disordered graphitic and amorphous nanodomains, offer tunable ion storage and rate capacity, yet rationale design remains a challenge due to poorly understood correlation between local atomic feature and ion transport mechanism. Here, to address this challenge, we introduce a data-driven framework that integrates validated machine-learned interatomic potentials, large-scale molecular dynamics simulations, and machine learning to elucidate sodium transport mechanisms as a function of carbon and sodium loading densities. By computing per-ion structural descriptors and applying unsupervised learning, we identify distinct diffusion modes governed by microscopic features. Supervised analysis and correlation mapping then establish quantitative links between these transport regimes and processing variables such as bulk carbon density and sodium content. This physics-informed approach establishes quantitative structure–transport relationships and offers actionable design principles for engineering high-performance HC anodes.

Data-driven framework↗

DOE OSTI2022

Local conformations and heterogeneities in structures and dynamics of isotactic polypropylene adsorbed onto carbon fiber

Carbon fiber (CF) reinforced polymers (CFRPs) have experienced widespread use in various industries. One of the most important parameters that controls the macroscopic property of CFRPs is the interface between a polymer matrix and CF. There is growing evidence to suggest the formation of a bound polymer layer (BPL), i.e., polymer chains that physically adsorb on a filler surface. However, this interface is always in contact with the thicker part of a polymer matrix, rendering its understanding a difficult task. Therein, we use CF-reinforced isotactic polypropylene (iPP) as a rational CFRP. To characterize the BPL on the CF surface, we extracted it from the CFRP using solvent-rinsing with p-xylene. The physical and thermal properties of the BPL were characterized by differential scanning calorimetry and thermogravimetric analysis, while its microscopic structures and dynamics were probed by small-angle neutron scattering and quasi-elastic neutron scattering (QENS) techniques. Subsequently, we employed atomistic molecular dynamics (MD) simulations to complement the QENS results above the bulk melting temperature and reveal details that were experimentally inaccessible. In this work, we observed that the degree of crystallinity of the BPL was quite lower than the bulk, while the melting temperature of the BPL remained the same as the bulks. Within the given length and time scales probed by QENS and MD, we also observed that most of the bound chains were mobile, with the formation of a high-density region (less than 1 nm in thickness) near the CF surface. The segmental dynamics of the bound chains probed by both QENS and MD were also much faster than those of the free chains, possibly due to the presence of a free surface region at the topmost surface of the BPL. Furthermore, the MD results demonstrated that the backbone chains and side groups lie nearly flat on the CF surface, which is the driving force for the flattening process of the iPP BPL to overcome the conformational entropy loss in the total free energy.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Subtle Molecular Changes Largely Modulate Chiral Helical Assemblies of Achiral Conjugated Polymers by Tuning Solution-State Aggregation

Understanding the solution-state aggregate structure and the consequent hierarchical assembly of conjugated polymers is crucial for controlling multiscale morphologies during solid thin-film deposition and the resultant electronic properties. However, it remains challenging to comprehend detailed solution aggregate structures of conjugated polymers, let alone their chiral assembly due to the complex aggregation behavior. Herein, we present solution-state aggregate structures and their impact on hierarchical chiral helical assembly using an achiral diketopyrrolopyrrole-quaterthiophene (DPP-T4) copolymer and its two close structural analogues wherein the bithiophene is functionalized with methyl groups (DPP-T2M2) or fluorine atoms (DPP-T2F2). Combining in-depth small-angle X-ray scattering analysis with various microscopic solution imaging techniques, we find distinct aggregate in each DPP solution: (i) semicrystalline 1D fiber aggregates of DPP-T2F2 with a strongly bound internal structure, (ii) semicrystalline 1D fiber aggregates of DPP-T2M2 with a weakly bound internal structure, and (iii) highly crystalline 2D sheet aggregates of DPP-T4. These nanoscopic aggregates develop into lyotropic chiral helical liquid crystal (LC) mesophases at high solution concentrations. Intriguingly, the dimensionality of solution aggregates largely modulates hierarchical chiral helical pitches across nanoscopic to micrometer scales, with the more rigid 2D sheet aggregate of DPP-T4 creating much larger pitch length than the more flexible 1D fiber aggregates. Combining relatively small helical pitch with long-range order, the striped twist-bent mesophase of DPP-T2F2 composed of highly ordered, more rigid 1D fiber aggregate exhibits an anisotropic dissymmetry factor (g-factor) as high as 0.09. This study can be a prominent addition to our knowledge on a solution-state hierarchical assembly of conjugated polymers and, in particular, chiral helical assembly of achiral organic semiconductors that can catalyze an emerging field of chiral (opto)electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Machine-learning-informed scattering correlation analysis of sheared colloids

We have carried out theoretical analysis, Monte Carlo simulations and machine-learning analysis to quantify microscopic rearrangements of dilute dispersions of spherical colloidal particles from coherent scattering intensity. Both monodisperse and polydisperse dispersions of colloids were created and underwent a rearrangement consisting of an affine simple shear and non-affine rearrangement using the Monte Carlo method. We calculated the coherent scattering intensity of the dispersions and the correlation function of intensity before and after the rearrangement and generated a large data set of angular correlation functions for varying system parameters, including number density, polydispersity, shear strain and non-affine rearrangement. Singular value decomposition of the data set shows the feasibility of machine-learning inversion from the correlation function for the polydispersity, shear strain and non-affine rearrangement using only three parameters. A Gaussian process regressor is then trained on the data set and can retrieve the affine shear strain, non-affine rearrangement and polydispersity with relative errors of 3%, 1% and 6%, respectively. Altogether, our model provides a framework for quantitative studies of both steady and non-steady microscopic dynamics of colloidal dispersions using coherent scattering methods.

Gaussian process regression↗

DOE OSTI2023

The collaborative effects of intrinsic and extrinsic impurities in low RRR SRF cavities

The superconducting radio-frequency (SRF) community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurity profile of niobium with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing and material analysis reveals a microscopic picture of why low RRR cavities experience low temperature-dependent BCS resistance behavior more prominently than their high RRR counterparts. We performed surface treatments, low temperature baking and nitrogen-doping, on low RRR cavities to evaluate how the intentional addition of oxygen and nitrogen to the RF layer further improves performance through changes in the mean free path and impurity profile. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of SRF surface treatments.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

The Collaborative Effects of Intrinsic and Extrinsic Impurities in Low RRR SRF Cavities

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

The Collaborative Effects of Intrinsic and Extrinsic Impurities in Low RRR SRF Cavities

The SRF community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurity profile of niobium coupons with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing and material analysis reveals a microscopic picture of why low RRR cavities experience low BCS resistance behavior more prominently than their high RRR counterparts. We performed surface treatments, low temperature baking and nitrogen-doping, on low RRR cavities to evaluate how the intentional addition of oxygen and nitrogen to the RF layer further improves performance through changes in the mean free path and impurity profile. Th e results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

Howard, K.↗

DOE OSTI2023

The Collaborative Effects of Intrinsic and Extrinsic Impurities in Low RRR SRF Cavities

The SRF community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurity profile of niobium coupons with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing and material analysis reveals a microscopic picture of why low RRR cavities experience low BCS resistance behavior more prominently than their high RRR counterparts. We performed surface treatments, low temperature baking and nitrogen-doping, on low RRR cavities to evaluate how the intentional addition of oxygen and nitrogen to the RF layer further improves performance through changes in the mean free path and impurity profile. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Proposed Analytical Methods for Determining Filter Media Properties

High Efficiency Particulate Air (HEPA) filters, commonly used in nuclear filtration applications, are an integral part of the waste management processes in nuclear plants. HEPA filters are 99.97% efficient filtration devices characterized by their high resistance to air flow, or pressure drop. From theoretical models, the initial pressure drop across a clean filter is proven to be a function of the filter media fiber diameters and porosity of the media. These filter properties are relatively difficult to obtain with traditional manual methods; therefore, there is a need to develop analytical methods to find the fiber diameter and porosity to determine the pressure drop. Typically, these values can be found by substituting a calculated representative value based upon measured values, such as equivalent fiber diameter based upon a clean pressure drop. However, these values may also be directly recorded and measured by incorporating Scanning Electron Microscope (SEM) image analysis and other measurement methods to analyze the filter media and determine its physical properties without the need for media testing. DiameterJ, an open source Java plug-in, used with ImageJ, can process images of filter media taken by an SEM to find statistical data such as mean fiber diameter and porosity. To produce the raw data, SEM images of two filter media type samples are taken and segmented in DiameterJ using the traditional and statistical region merging segmentation algorithms. Manual segmentation is necessary after the initial segmentation by the algorithms as the images tend to be too complex for the algorithms to output with the necessary accuracy. However, complications exist in the manual segmentation process as these methods can be time intensive and prone to the individual bias of the user. This in turn can skew the final mean fiber diameter result, and lead to either an over or under prediction of the pressure drop. It was also discovered that the porosity data produced by DiameterJ is inaccurate, as the SEM analyzes the three-dimensional filter media by projecting its geometry onto a plane and analyzing it as a two-dimensional binary image. Thus, the porosity is artificially inflated through the segmentation process, rendering this result incorrect. Alternatively, density determination, gravimetric analysis, and thickness testing of the filter media is collectively used to determine the filter fiber porosity. Together, the SEM image analysis and analytical lab methods produce results through direct measurements which allow for the prediction of the initial pressure drop from clean filter media without the need for prior media testing to collect pressure data. By improving upon this proposed analytical method in the future, there is potential to streamline the process of finding these filter properties into a more direct methodology for determining the pressure drop across HEPA filters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Neutron skin systematics from microscopic equations of state

This paper presents an analysis of neutron skins based on fully microscopic equations of state, including chiral two- and three-nucleon forces consistently at N 3 LO. Other theoretical predictions and recent constraints are also addressed, such as those from the PREX II experiment and the latest parity-violating electron scattering measurement of the 27 Al neutron skin.

Equation of State↗

DOE OSTI2025

Enhancing traffic safety analysis with digital twin technology: integrating vehicle dynamics and environmental factors into microscopic traffic simulation

Traffic safety is a critical concern in transportation engineering and urban planning. Traditional traffic safety analysis requires trained observers to collect data in the field, which is time-consuming, labor-intensive, and sometimes inaccurate. In recent years, microscopic traffic simulation, which simulates individual vehicles’ movements within a transportation network, have been utilized to study traffic safety. However, microscopic traffic simulation only focuses on traffic-related factors, such as traffic volume, traffic signals, and lane configurations, neglecting vehicle dynamics and environment-related factors like weather and lighting conditions, which can significantly impact traffic safety. In light of this, this paper explores the application of digital twin technology in traffic safety analysis, integrating vehicle simulators, which consider vehicle dynamics and environmental factors, and microscopic traffic simulators, which simulate the operations of traffic flow, for enhanced safety evaluations. Various scenarios, including different weather conditions and visibility levels, are simulated using a digital twin of a road segment in Tuscaloosa, Alabama. The simulations employ Surrogate Safety Measures (SSMs) like Time to Collision (TTC) and Deceleration Rate to Avoid a Crash (DRAC) to assess safety under varying conditions. The results demonstrate that traffic digital twin can identify potential safety issues that traditional microscopic simulation cannot, providing insights for improving traffic control strategies and transportation infrastructure to enhance traffic safety.

Civil engineering↗

DOE OSTI2023

Towards a heat- and mass-balanced kinetic model of TATB decomposition

We report TATB (1,3,5-triamino-2,4,6-trinitrobenzene) was thermally degraded by two small-scale analytical methods – simultaneous differential scanning calorimetry and thermogravimetric analysis (SDT) and a hot-stage microscope with Fourier Transform Infrared (FTIR) analysis capabilities. SDT used ramped heating, isothermal soaking, and thermal pretreatment at various conditions. The heat flow and mass loss were monitored during various treatment conditions to derive chemical decomposition kinetics and Arrhenius parameters. FTIR experiments used isothermal heating, and changes were monitored spectroscopically. Solid samples generated at specific conditions were collected from both methods and were analyzed by DMSO extraction followed by chemical speciation by optical and mass spectrometric methods. Characterization provided the following reaction insights: TATB decreases in a sigmoidal pattern in isothermally heated samples. Other soluble products gradually increase in concentration and then abruptly decline in concentration during the second exotherm, such as diamino-dinitro-benzofurazan and amino-nitro-benzodifurazan. FTIR showed gradual changes in the amino and nitro functionality, shifting positions and decreasing intensity for the first 40 min. Then the solid gradually appeared more like an amorphous C with N incorporated, similar to previous studies on thermally degraded TATB-type materials. Extracted residues (DMSO-soluble components removed) examined by FTIR showed an abrupt change in chemical composition between 40- and 45-min isothermal treatment, indicating early forming solids are different than later forming residues. A reliable mass- and energy-balanced global reaction network must include at least two autocatalytic reactions, either in parallel or series, and at least one must have an explicit initiation reaction having a low activation energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Morphology and particle size (MaPS) exercise: testing the applications of image analysis and morphology descriptions for nuclear forensics

Image analysis techniques have been applied and shown to be a valuable tool in nuclear forensics analysis. The interlaboratory exercise reported here has tested quantitative and qualitative approaches for characterizing nuclear materials. Particle size, surface features and morphology descriptions were compared by four laboratories on a common image set generated by Scanning Electron Microscopy and Digital Light Microscopy. Quantitative analysis of the image sets through the Morphological Analysis for MAterials software highlighted the strength of image analysis, but also that the application of the software alone can introduce significant bias in the analysis. Qualitative morphology descriptions following the process outlined by Tamasi et al. (J Radioanal Nuclear Chem 307:1611–1619, 2015) were compared with a discussion on the robustness and reproducibility of the results. Finally, future work should continue to focus on proficiency and standardization of image analysis through continued exercises within the extended nuclear forensics community.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

TXM-Sandbox : an open-source software for transmission X-ray microscopy data analysis

A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook . Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Multi-element isotopic analysis of hot particles from Chornobyl

Microscopic fuel fragments, so-called “hot particles”, were released during the 1986 accident at the Chornobyl nuclear powerplant and continue to contaminate the exclusion zone in northern Ukraine. Isotopic analysis can provide vital information about sample origin, history and contamination of the environment, though it has been underutilized due to the destructive nature of most mass spectrometric techniques, and inability to remove isobaric interference. Recent developments have diversified the range of elements that can be investigated through resonance ionization mass spectrometry (RIMS), notably in the fission products. The purpose of this study is to demonstrate the application of multi-element analysis on hot particles as relates to their burnup, particle formation in the accident, and weathering. The particles were analysed with two RIMS instruments: resonant-laser secondary neutral mass spectrometry (rL-SNMS) at the Institute for Radiation Protection and Radioecology (IRS) in Hannover, Germany, and laser ionization of neutrals (LION) at Lawrence Livermore National Laboratory (LLNL) in Livermore, USA. Comparable results across instruments show a range of burnup dependent isotope ratios for U and Pu and Cs, characteristic of RBMK-type reactors. Results for Rb, Ba and Sr show the influence of the environment, retention of Cs in the particles and time passed since fuel discharge.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Machine Learning for Predictive Performance Analysis in Charged Particle Beam Tools

Imaging methods driven by probes, electrons, and ions have played a dominant role in modern science and engineering. Opportunities for machine vision and AI that focus on consumer problems like driving and feature recognition, are now presenting themselves for automating aspects of the scientific processes. This proposal aims to enable and drive discovery in ultra-low energy implantation by taking advantage of faster processing, flexible control and detection methods, and architecture-agnostic workflows that will result in higher efficiency and shorter scientific development cycles. Custom microscope control, collection and analysis hardware will provide a framework for conducting novel in situ experiments revealing unprecedented insight into surface dynamics at the nanoscale. Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low energy ion implants can be achieved by either lowering the column voltage, or decelerating ions using bias – while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found that is due to lattice enrichment with high stopping power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way to much lower implantation energies, while maintaining high spatial resolution.

47 OTHER INSTRUMENTATION↗