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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Many-body expansion for light nuclear systems

Here we extend the many-body expansion (MBE), previously applied to hydrogen bonded and molecular systems, to the light nuclear systems 3 H and 3 He by considering the nucleonic degrees of freedom as fundamental in the expansion. The analysis is based on the Pauli nucleonic dynamics (PND) model, a simple antisymmetrized dynamical code, inspired by the sophisticated constrained molecular dynamics (CoMD) model. The total energy of the 2 H nucleus is calculated with this model at -2.312 MeV, which is within 4% of the experimental value of -2.225 MeV. The application of the MBE yields results for the three-body term in the 3 H nucleus that is comparable with previous estimates, while it is reported for the first time for the nucleus of 3 He . The energies of 3 H and 3 He that include the sum of the one- and two-body terms with the model are - 6.97 ± 0.21 MeV and - 6.19 ± 0.21 MeV and the three-body terms, estimated from the difference of the sum of the one- and two-body terms from the experimentally measured energies, are -1.51 ± 0.21 MeV and -1.53 ± 0.21 MeV, respectively. The MBE for the 3 H and 3 He nuclei is qualitatively similar to the one previously reported for the water trimer: the two- and three-body terms are negative with the latter amounting to ~3% of the former. Additionally, the three-body terms correspond to about 16–23% of the total energy of the bound systems, a percentage that is also comparable to the one in the water trimer (17%). In this manner, the MBE analysis can be applied to light nuclear systems following the same protocol as the one that has been previously extensively used for hydrogen bonded molecular systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Light-Driven Depolymerization of Native Lignin Enabled by Proton-Coupled Electron Transfer

In this work, we report a catalytic, light-driven method for the redox-neutral depolymerization of native lignin biomass at ambient temperature. This transformation proceeds via a proton-coupled electron-transfer (PCET) activation of an alcohol O–H bond to generate a key alkoxy radical intermediate, which then facilitates the β-scission of a vicinal C–C bond. Of significance, this single-step depolymerization is driven solely by visible-light irradiation, requires no stoichiometric chemical reagents, and produces no stoichiometric waste. This method exhibits good efficiency and excellent selectivity for the activation and fragmentation of the β-O-4 linkage in the polymer backbone, even in the presence of numerous other PCET-active functional groups. The feasibility of this protocol in enabling the cleavage of the β-1 linkage in model lignin dimers was also demonstrated. These results provide further evidence that visible-light photocatalysis can serve as a viable method for the direct conversion of lignin biomass into valuable arene feedstocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lifetime and Degradation Study of Poly(Methyl Methacrylate) via a Data-Driven Study Protocol Approach

We report to optimize and extend the service life of polymeric materials in outdoor environments, a domain knowledge-based and data-driven approach was utilized to quantitatively investigate the temporal evolution of degradation modes, mechanisms, and rates under various stepwise accelerated exposure conditions. Six formulations of poly(methyl methacrylate) (PMMA) with different combinations of stabilizing additives, including one unstabilized formulation, were exposed in three accelerated weathering conditions. Degradation was dependent on wavelength as samples in UV light at 340 nm (UVA) exposure showed the most yellowing. The unstabilized PMMA formulation showed much higher yellowness index values (59.5) than stabilized PMMA formulations (2–12). Urbach edge analysis shows a shift toward longer wavelength from 285 to 500 nm with increasing exposure time and an increased absorbance around 400 nm of visible region as the unstabilized samples increase in yellowing. The degradation mechanisms of PMMA were tracked using induced absorbance to dose at specific wavelengths that correspond to known degradation mechanisms. The degradation pathway of PMMA was modeled in a framework using network structural equation modeling (netSEM). netSEM showed changes in degradation pathway as PMMA transition stages of degradation.

36 MATERIALS SCIENCE↗

Benchmarking Microscale Ductility Measurements (Final Report of the Project DE-NE0008799)

Conventional macroscale experimentation is generally considered to be straightforward with few limitations. Conversely, micro/nanoscale experimentation presents numerous challenges in loading device design, sample preparation and handling, as well as accurate understanding of grain size and local texture effects on recorded measurements. Despite these challenges, nanopillar compression, MEMs based micro-tension, and nanoindentation approaches have been able to provide fundamental contributions to the understanding of material behavior at small lengthscales. However, the overarching shortcoming of these micro/nanoscale experimentation approaches, is the inability to directly translate measurements evaluated at the nm and µm length scales (e.g., hardness) to macroscale tensile material behavior (i.e., elastic modulus, yield strength, and ductility). The objectives of the proposed study are, 1) to establish best practices for obtaining tensile microscale ductility measurements, and 2) to validate methodologies to for comparing microscale ductility measurements to macroscale ductility measurements. In order to achieve these objectives, a multi-lengthscale, multi-temperature testing protocol and simulation framework are executed first on copper as a model material to validate the following approach, and second on reactor grade Zircaloy-2. Experiments are conducted on specimens extracted from the same test piece to ensure nominally identical grain size and texture from specimens to specimen. Motivated by the need to isolate the contribution of size-effects on obtained mechanical property measurements, specimens are manufactured with thicknesses at the micro- (1-10 µm), meso- (10-100's µm), and macroscales (sub-sized ASTM E8). In-situ full-field deformation techniques (scanning electron microscopy (SEM) grid methods and optical DIC) are incorporated into testing at each specimen length-scale to capture plasticity localization and evolution. Experimental testing for all specimens is conducted at both room temperature and elevated temperatures to probe the role of thermal activation on plastic deformation accommodation processes. Simulation efforts focus on examining the mechanical behavior of microscale specimens using a finite element approach with explicitly resolved grain morphologies, and an embedded crystal plasticity model. The cost-efficient implementation method allows for the modeling of a statistically significant number of both real (i.e., digital twin) and generated microstructures to obtain an understanding of the interrelationships between specimen microstructure and geometric variables (grain size, texture, specimen geometry, etc.) on microscale mechanical behavior.

36 MATERIALS SCIENCE↗

Vacuum-assisted carbon molecular sieve membrane reactor for non-oxidative ethane dehydrogenation

Non-oxidative ethane dehydrogenation (EDH) is equilibrium-limited and endothermic. Selective hydrogen removal using a gas-permeable membrane within the EDH reaction zone can overcome the thermodynamic equilibrium, enabling higher ethane conversions. Employing vacuum as the permeation driving force, rather than a sweep gas, enhances the industrial viability of membrane reactors by eliminating additional post-reaction separation units. This study presents a membrane reactor that integrates H 2 -permeable carbon molecular sieve (CMS) hollow fiber membranes embedded in a fixed bed of cobalt in a dealuminated beta zeolite (Co@DeAl-BEA) catalyst, utilizing a vacuum to remove hydrogen efficiently. The CMS membrane exhibits high hydrogen permeance and an excellent H 2 /C 2 H 6 separation factor. The membrane reactor significantly enhanced the ethane conversion under reaction conditions comparable to those reported in the literature. A Langmuir-Hinshelwood kinetic rate expression was developed and incorporated into a one-dimensional steady-state reactor model. The experimentally validated model indicates that increasing the number of hollow fibers improves ethane conversion, although ethane loss to the permeate limits the benefit. The contact area between the catalyst and the membrane limits the reactor performance more than the catalytic throughput. Furthermore, we find that the location of the catalyst packing relative to the hollow fiber membranes influences ethane loss and conversion. Higher reactor pressures and inlet ethane flow rates improve space-time yield at the expense of lower ethane conversion. Increasing reactor temperature or packing length promotes both performance metrics. The EDH membrane reactor demonstrated durability over 200 h of continuous operation, maintaining record-low deactivation rates and high ethylene selectivity. Protocols for catalyst regeneration were developed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Predicting and Controlling Corrosion (Abbreviated Final Report)

Corrosion accumulates significant replacement costs in the transportation, utility, manufacturing, and infrastructure sectors. It also underpins several of LLNL’s core missions in stockpile stewardship, defense, and energy security. Whereas most corrosion and aging models are empirically parameterized to describe well-defined conditions late in the reaction, the factors that determine the early stages of corrosion—during which mitigation could be most impactful— are poorly understood. This project addressed the critical need for new approaches to predict the kinetics of corrosion initiation based on firm physical and chemical understanding. The activities encompassed degradation of relevant metals in both hydrogen-rich and environmental corrosion scenarios. The team integrated state-of-the-art multiscale simulation, in situ characterization, and data science within three technical thrusts: hydriding of Ti alloys; aqueous corrosion of Al and Ni-Cr alloys; and degradation of additively manufactured 316L stainless steel. In each case, novel capabilities were developed to identify and track the impacts of key atomistic, compositional, and microstructural features on the metal systems. For hydriding, protocols were developed to tightly integrate multiscale models, advanced multimodal characterization, and machine learning to determine how hydrogen interacts with native passivating surface oxides and nucleates new undesired phases, shedding new light on the critical role of grain boundaries, interfaces, and atomically disordered regions. For aqueous corrosion, the project demonstrated methods to predict dissolution rates of metal surfaces in corrosive solutions, to measure and understand microstructural and grain orientation effects on corrosion susceptibility, and to investigate competing growth and dissolution kinetics of surface oxides. For additively manufactured metals, analysis using state-of-the-art microscopy techniques revealed the role of specific heterogeneities invoked during laser processing, including cellular structure, dislocations, and precipitates, on corrosion susceptibility. In addition to new capabilities and understanding, the project provided an avenue for workforce development, as well as key partnerships with stakeholders in corrosion science.

08 HYDROGEN↗

Quantum computation of stopping power for inertial fusion target design

Stopping power is the rate at which a material absorbs the kinetic energy of a charged particle passing through it—one of many properties needed over a wide range of thermodynamic conditions in modeling inertial fusion implosions. First-principles stopping calculations are classically challenging because they involve the dynamics of large electronic systems far from equilibrium, with accuracies that are particularly difficult to constrain and assess in the warm-dense conditions preceding ignition. Here, we describe a protocol for using a fault-tolerant quantum computer to calculate stopping power from a first-quantized representation of the electrons and projectile. Our approach builds upon the electronic structure block encodings of Su et al. [ PRX Quant. 2 , 040332 (2021)], adapting and optimizing those algorithms to estimate observables of interest from the non-Born–Oppenheimer dynamics of multiple particle species at finite temperature. We also work out the constant factors associated with an implementation of a high-order Trotter approach to simulating a grid representation of these systems. Ultimately, we report logical qubit requirements and leading-order Toffoli costs for computing the stopping power of various projectile/target combinations relevant to interpreting and designing inertial fusion experiments. We estimate that scientifically interesting and classically intractable stopping power calculations can be quantum simulated with roughly the same number of logical qubits and about one hundred times more Toffoli gates than is required for state-of-the-art quantum simulations of industrially relevant molecules such as FeMoco or P450.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Data-Driven Approach to Real-World Degradation of Backsheets

The objectives of this project are as follows: • The population behavior of fielded modules in various conditions of use • Predictions of materials in specific climatic zones • Understanding of a module’s local environment in the field on its degradation It aims to understand how and what backsheet materials of photovoltaic modules degrade in the real world field. • Field Survey Protocol This project is started from the protocol, because all the data, information, domain knowledge are from experience of the real world field surveys, which is based on the protocol. The Protocol is explored from the experience of the field survey observations. With the increasing of the field surveys, it is refined for three versions, which are Task 1.0 (Section 3.1), Task 6.0 (Section 3.6), Task 10.0 (Section 3.10) respectively. It includes a document and a training video, which is able to direct other teams to follow the same procedure with the sites surveyed during this project. The documents include the detailed information but is not limited to the terminology definition, instruments SOP, preparation items for the surveys, form for the data collections, the order of the information collection. The final version of the protocol can be found at Appendix A, see Section 5. Additional, It can also be found at Open Science Framework (OSF), see Section 3.18 for detail. • Written Waiver Request Before staring the field surveys, the request of the waiver for international surveys is completed, because the limitation of climate zone in the United States, see Appendix B in Section 6 for the request documents. Unfortunately, only 1 international site from Taiwan, China can be finished, due to the COVID-19. • Field Survey According to the protocol we built in Section 3.1, 3.6 and 3.10, 41 sites have been surveyed across seven different climate zones (Cfa, Csa, Csb, BSk, Dfa, Dfb, Am). A variety of materials, including Polyethylene Naphthalate (PEN), Polyethylene Terephthalate (PET), Polyvinyl Fluoride (PVF), Polyvinylidene Fluoride (PVDF), Acrylic PVDF, Fluoroethylene Vinyl Ether (FEVE), and Glass, were identified. These sites are located in various states including California, South Carolina, New Mexico, Maryland, Ohio, Tennessee, Florida, Massachusetts, Illinois, Minnesota, Oregon, Colorado, and Taiwan, Republic of China. The ages of the sites ranged from 2 - 38 years in service and the field size varied from 1 MW - 25 MW. All requirements for the modeling have been satisfied. Some observations like ’Edge Effect’ for the rows and Junction box heating will also be a useful knowledge to build the model. Section 3.7 provides detailed information on the sites visited during this reporting period.

14 SOLAR ENERGY↗

Understanding Evolution of Lithium Trivanadate Cathodes During Cycling via Reformulated Physics-Based Models and Experiments

Degradation of lithium trivanadate ( Li x V 3 O 8 ) cathodes has been widely reported in the literature, but studies have offered little insight towards developing a detailed understanding of the evolution of the active material, and have been inconclusive as to the root cause of degradation. Here, we refit a validated physics-based model to discharge curves over the course of cycling at C/5, and use the evolution of the model parameters to track evolution of the cathode. A regularization penalty for adjusting model parameters from the validated model is introduced as a framework to identify which model parameters can explain a significant portion of the observed change in the voltage profile over the course of cycling. SEM reveals that lithium trivandate particles fracture upon cycling at C/5, consistent with the results of the parameter estimation, deactivation of lithium trivanadate and faster diffusion of lithium within the active particles. The physics-based model is then used to design modified cycling protocols which identify the phase transformation during discharge of lithium trivanadate as the driver of the particle fracture and capacity fade.

25 ENERGY STORAGE↗

Stress Relaxation Cracking of Alloys at Temperatures Higher Than 540°C

Type 347H stainless steel (347H SS), used in commercial concentrating solar power (CSP) thermal energy storage to store solar-salt at a temperature of 565°C, has been reported in the literature to be susceptible to stress-relaxation cracking (SRC). The welded heat-affected zone (HAZ) and fusion zone (FZ) of 347H SS, particularly in thick sections, are known to be susceptible to failure during post-weld heat treatment (reheat cracking). SRC could also occur after months or years under an elevated-temperature service environment. Two conditions must be present for failure to occur in the HAZ and/or FZ: 1) a modified or sensitized microstructure and 2) sufficiently high tensile residual stresses present at the elevated service temperature. The overarching goal of this project is to recommend SRC mitigation protocols to avoid susceptibility to fail through SRC at temperatures relevant for CSP. Post weld heat treatment conditions and alternative alloys are investigated as potential mitigation solutions to SRC. We used Gleeble thermomechanical simulation tests and finite element (FE) models to understand the susceptibility of 347H SS to SRC as a function of temperature, stress, and microstructure. We started with a literature review of weldability issues with 347H SS and techniques to mitigate SRC in 347H SS weldments. Next, we used Gleeble experiments to determine reheat cracking susceptibility in the simulated HAZ of 347SS weldments and an alternative alloy, 316L SS (NUCL 167 SPH) with boron added. We also performed Gleeble experiments to compare the reheat cracking susceptibility of 347H cross welded with two different fillers: E347, which is used in some commercial CSP TES tanks, and E16.8.2. We validated the experimental results with FE models of the residual stresses. We found that although the 316L (NUCL 167 SPH) is less susceptible to reheat cracking, it is slightly weaker than 347H and ASME BP&V codes limit its use to a service condition of 565°C. We also found that welds using E16.8.2 as the weld filler are less susceptible to failure than those using E347, likely due to the higher creep ductility of E16.8.2, and that it may be used as an alternative filler for repair welding of 347H welds or as the primary choice of filler for newly developed weld joints. We also found that post weld heat treatment could be a viable solution for mitigating stress in E347-347H SS thick, constrained welds, like those found in CSP tanks, and propose several options for mitigating SRC in existing and future TES tanks.

14 SOLAR ENERGY↗

Reticular Materials and AI-Driven Computer Simulations for Seawater Mining of Valuable Metals (Final Technical Report)

This Final Technical Report describes our exploratory efforts that combine reticular materials synthesis (hydrolytically robust metal–organic frameworks, MOFs) with AI‑enabled molecular simulations to develop mechanistic, quantitative design rules for recovering lithium and other alkali-metal ions from highly dilute, competitive aqueous resources (e.g., seawater). The central outcome is a joint experimental–computational study of ion uptake in MOF‑808 (Chemical Science, 2025) that quantifies both thermodynamics and kinetics of Li + , Na + , and K + uptake and identifies how pore size, pore hydration state, dehydration penalties, and pore-window transport barriers govern selectivity. Guided by these insights, we synthesized and tested functionalized MOF‑808 and multivariate MOFs incorporating ion-recognition motifs (including carboxylates and crown-ether linkers) and evaluated uptake in synthetic seawater, highlighting framework topology and pore chemistry as levers for improved Li + /Na + discrimination. We also developed transferable simulation models, enhanced-sampling protocols, and automated workflows that enable systematic screening of porous sorbents.

42 ENGINEERING↗

Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics

The importance of data curation has been recognized in multiple areas of research; however, the discussion of this important issue is only beginning to emerge in materials science. In this Perspective, we highlight the benefits of using the standardized data curation protocols in materials science and discuss current gaps in accurate and reproducible data reporting using case studies drawn from high-impact materials science papers and well-known databases such as the Crystallography Open Database (COD) and the Cambridge Structural Database (CSD). We argue that both experimental and computational materials scientists need to embrace a culture of rigorous data curation as part of modern research data management. We propose a sample data curation pipeline for materials chemistry and illustrate its use by creating two new materials chemistry databases. Here, we hope that this perspective will serve to catalyze further discussion and promote the continuous development of rigorous data curation practices within the materials science research community. We posit that adherence to best practices of data curation will promote and enhance the reliability, reproducibility, and integrity of materials research and enable the development of reliable AI and machine learning models that critically depend on the use of quality data.

Chemical structure↗

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗

NeuDiff Agent: a governed AI workflow for single-crystal neutron crystallography

Large-scale facilities increasingly face analysis and reporting latency as a limiting step in scientific throughput, particularly for structural studies that require iterative reduction, integration, refinement and validation. To improve the time to result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source. NeuDiff Agent takes instrument data through reduction, integration, refinement and validation to a validated crystal structure and a publication-ready CIF. NeuDiff Agent coordinates established crystallographic tools under explicit governance by restricting actions to allowlisted tools, enforcing fail-closed verification gates at key workflow boundaries, and capturing complete provenance for inspection, auditing and controlled replay. The present benchmark is limited to structural crystallography for periodic structures; magnetic structure analysis and incommensurate or superspace refinement are outside the scope of the current workflow. Performance is assessed using a fixed prompt protocol and repeated end-to-end runs with two large language model backends, with user and machine time partitioned and intervention burden and recovery behaviors quantified under gating. In a reference-case benchmark, NeuDiff Agent reduces wall time from 435 min (manual) to 86.5 ± 4.7 to 94.4 ± 3.5 min (4.6–5.0× faster) while producing a validated CIF with no checkCIF level A or B alerts. These results establish a practical route to deploy agentic AI in facility crystallography while preserving traceability and publication-facing validation requirements.

Xiao, Zhongcan [ORNL] (ORCID:0000000220761961)↗

Recommendations for Distributed Energy Resource Access Control

Cybersecurity for internet - connected Distributed Energy Resources (DER) is essential for the safe and reliable operation of the US power system. Many facets of DER cybersecurity are currently being investigated within different standards development organizations, research communities, and industry committees to address this critical need. This report covers DER access control guidance compiled by the Access Controls Subgroup of the SunSpec/Sandia DER Cybersecurity Workgroup. The goal of the group was to create a consensus - based technical framework to minimize the risk of unauthorized access to DER systems. The subgroup set out to define a strict control environment where users are authorized to access DER monitoring and control features through three steps: (a) user is identified using a proof-of-identity, (b) the user is authenticated by a managed database, (c) and the user is authorized for a specific level of access. DER access control also provides accountability and nonrepudiation within the power system control environment that can be used for forensic analysis and attribution in the event of a cyber-attack. This paper covers foundational requirements for a DER access control environment as well as offering a collection of possible policy, model, and mechanism implementation approaches for IEEE 1547-mandated communication protocols.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Methanediol from cloud-processed formaldehyde is only a minor source of atmospheric formic acid

Atmospheric formic acid is severely underpredicted by models. A recent study proposed that this discrepancy can be resolved by abundant formic acid production from the reaction ( 1 ) between hydroxyl radical and methanediol derived from in-cloud formaldehyde processing and provided a chamber-experiment-derived rate constant, k 1 = 7.5 × 10 −12 cm 3 s −1 . High-level accuracy coupled cluster calculations in combination with E,J -resolved two-dimensional master equation analyses yield k 1 = (2.4 ± 0.5) × 10 −12 cm 3 s −1 for relevant atmospheric conditions ( T = 260–310 K and P = 0–1 atm). We attribute this significant discrepancy to HCOOH formation from other molecules in the chamber experiments. More importantly, we show that reversible aqueous processes result indirectly in the equilibration on a 10 min. time scale of the gas-phase reaction HCHO + H 2 O ⇌ HOCH 2 OH (2) with a HOCH 2 OH to HCHO ratio of only ca . 2%. Although HOCH 2 OH outgassing upon cloud evaporation typically increases this ratio by a factor of 1.5–5, as determined by numerical simulations, its in-cloud reprocessing is shown using a global model to strongly limit the gas-phase sink and the resulting production of formic acid. Based on the combined findings in this work, we derive a range of 1.2–8.5 Tg/y for the global HCOOH production from cloud-derived HOCH 2 OH reacting with OH. The best estimate, 3.3 Tg/y, is about 30 times less than recently reported. The theoretical equilibrium constant K eq (2) determined in this work also allows us to estimate the Henry’s law constant of methanediol (8.1 × 10 5 M atm −1 at 280 K).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The performance of ensemble-based free energy protocols in computing binding affinities to ROS1 kinase

Optimization of binding affinities for compounds to their target protein is a primary objective in drug discovery. Herein we report on a collaborative study that evaluates a set of compounds binding to ROS1 kinase. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to rank the binding free energies. The predicted binding free energies from ESMACS simulations show good correlations with experimental data for subsets of the compounds. Consistent binding free energy differences are generated for TIES and ESMACS. Although an unexplained overestimation exists, we obtain excellent statistical rankings across the set of compounds from the TIES protocol, with a Pearson correlation coefficient of 0.90 between calculated and experimental activities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of Arsenic and Selenium in Coal Fly Ash to Improve Evaluations for Disposal and Reuse Potential (Final Technical Report)

Coal fly ash is a high volume waste material that is discarded in landfills and surface water impoundments across the U.S. and is also widely recycled for a variety of applications. The leaching of potential of contaminants of concern, such as arsenic (As) and selenium (Se), is often the driver of risk assessments for coal ash disposal and reuse. The extent of leachable As and Se depends on several factors related to environmental conditions and fly ash characteristics. Previous studies employed various methods to delineate the concentration, chemical form, and distribution of As and Se in fly ash materials. However, few studies have attempted to directly correlate these properties to mobilization parameters relevant to disposal and reuse. Instead, the coal residuals industries often rely upon standardized leaching protocols that can be laborious or involve hazardous chemicals. The goals of the project were to: 1) Develop and evaluate a characterization protocol that can be used to screen fly ash samples for leachability of As and Se; 2) Characterize As, Se, and associated constituents of fly ash particles at multiple length scales (nanometer to micrometer) to determine if elemental associations differ as a function of the resolution of characterization; and 3) Establish a predictive model for the chemical composition of coal ash produced annually at major U.S. coal fired power facilities on 50-year national coal supply records. For the first objective, we performed leaching experiments with 52 fly ash samples collected from 15 different U.S. power plants and representing coal feedstocks from the three major domestic coal regions. For this work, we assessed the mobilization potential of As and Se in fly ash based on standardized leaching protocols and performed multivariate and lasso regression analyses to explore correlations of leachable As and Se contents with characteristics such as major element contents, loss on ignition (LOI) and pH. The results of regression models indicated that major elements (Fe, Ca, Al) for a wide range of fly ashes can serve as predictor variables for the leaching potential of As, but not for Se. LOI and pH were not important predictive variables in the models. Both regression approaches resulted in relatively strong fits for leachable As (correlation coefficient R 2 = 0.78 for both models) compared to models for leachable Se (R 2 = 0.49). Overall, these results suggest that correlation models combined with on-site elemental analysis with portable analyzers may enable a screening method for leachable As in coal ash. For the second objective, we utilized nanoscale 2-D imaging (30-50 nm spot size) with the Hard X-ray Nanoprobe (HXN) in combination with microprobe X-ray capabilities (~5 µm resolution) to determine As and Se elemental associations in fly ash particles. Speciation of As and Se was also measured at the nano- to microscale with X-ray absorption spectroscopy. The enhanced resolution of HXN showed As and Se that were diffusely located around or comingled with Ca- and Fe-rich particles. The results also showed nanoparticles of Se attached to the surface of fly ash grains. Overall, a comparison of As and Se species across scales highlights the heterogeneity and complexity of chemical associations for these trace elements of concern in coal fly ash. For the final objective, we developed a predictive model for major element composition of coal ash in reserve at disposal sites of major U.S. coal fired power plants. This model was constructed from coal purchase records of 705 power stations from 1973-2022 and was trained on coal ash composition data showing that coal ash elemental composition is strongly associated with the source of feedstock coal. The model showed regional shifts in the major element contents of ash produced by power plants in the last 50 years, particularly for calcium and iron (expressed as %CaO and %Fe 2 O 3 ), as coal-fired power stations changed their source of coal over this time frame. Our approach enables an estimation of coal ash chemical composition that is stored in waste impoundments at individual power stations. Such information can help delineate the regional market potential for material applications that would utilize coal ash harvested from disposal sites across the U.S.

01 COAL, LIGNITE, AND PEAT↗