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DOE OSTI2022

Electronic Structure of Molecular Cobalt Catalysts for H 2 Production Revealed by Multifrequency EPR

Improving the design of hydrogen evolution reaction (HER) catalysts requires a detailed understanding of the catalyst's structure and environment. Here wwe have used multifrequency electron paramagnetic resonance (EPR) spectroscopy (X-band, Q-band, and D-band) in combination with density functional theory (DFT) modeling to elucidate the electronic structure of three Co(II) molecular catalysts for H 2 evolution to determine correlations of electronic structure parameters with catalytic activity and stability. The Co(II) coordination complexes investigated here are representative of two types of H 2 -evolving molecular catalysts: cobaloximes, formed from cobalt coordination to two glyoxime ligands, and cobalt poly(pyridyl) complexes, which commonly have either four or five pyridyl ligands coordinating a single Co(II) ion. These Co(II) complexes were studied in a variety of solvents with a range of polarities and stoichiometric amounts of potential ligands to the cobalt ion to assess the strength and nature of ligand- cobalt interactions. Using magnetic resonance parameters obtained by EPR spectroscopy as reference data, we reconstructed the electronic structure of the Co(II) complexes with the help of DFT modeling. For all three catalysts, we uncovered a linear correlation between the Co(II) A z value and the g x value that is dependent on the strength of the axial ligands. The correlations that we have established between the electronic structure and metal coordination environment provide insight into the structural and electronic factors underpinning the observed trends in HER catalysis activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2020

Ultrafast Melting at Metal-Semiconductor Interfaces: A Molecular Dynamics Study

Quantifying the thermodynamics of interfacial melting is important for several applications such as laser machining and designing radiation hardened electronic devices. Due to the short time and length scales that are involved in the process, molecular simulations provide an ideal path for understating the interfacial melting phenomena. In this work we investigate tungsten (W) – silicon carbide (SiC) interfaces which are relevant in modern high-power electronic devices. Classical molecular dynamics simulations along with the two-temperature model (TTM) were used to study the radiation induced melting of the interface while a neural network-based machine learning framework was used to track the transient re-crystallization process. The damage endured by the semiconductor at the interface following the radiation event is discussed in detail while the re-crystallization of the metal is described in terms of the classical nucleation theory.

Ashwin Ravichandran↗

DOE OSTI2026

Extending SLUSCHI for Automated Diffusion Calculations

We present an extension of the SLUSCHI package (Solid and Liquid in Ultra Small Coexistence with Hovering Interfaces) to enable automated diffusion calculations from first-principles molecular dynamics. While the original SLUSCHI workflow was designed for melting temperature estimation via solid-liquid coexistence, we adapt its input and output handling to isolate the volume search stage and generate one production trajectory suitable for diffusion analysis. Post-processing tools parse VASP outputs, compute mean-square displacements (MSD), and extract tracer diffusivities using the Einstein relation with robust error estimates through block averaging. Diagnostic plots, including MSD curves, running slopes, and velocity autocorrelations, are produced automatically to help identify diffusive regimes. The method has been validated through representative case studies: self-diffusion in Al-Cu liquid alloys, sublattice melting in Li7La3Zr2O12 and Er2O3, interstitial oxygen transport in bcc and fcc Fe, and oxygen diffusivity in Fe-O liquids with variable Si and Al contents. Viscosity and diffusivity are linked through the Stokes-Einstein relation, with composition dependence assessed via simple linear mixing. This capability broadens SLUSCHI from melting-point predictions to transport property evaluation, enabling high-throughput, fully first-principles datasets of diffusion coefficients and viscosities across metals and oxides.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Gas Stopper Developments for Improved Purity and Intensity of Low-Energy, Rare Isotope Ion Beams (Final Technical Report)

This final technical report summarizes the work of the Michigan State University (MSU) team supported by grant # DE-SC0021423 awarded by the Office of Nuclear Physics, Department of Energy. Objectives: The successful fulfillment of the FRIB science mission hinges on ensuring the availability of fast, stopped, and reaccelerated beams consisting of rare isotopes. This project's research and development focus was dedicated to supporting the advancement and creation of a cutting-edge linear gas stopper. The primary aim is to efficiently convert the high-intensity fast beams of rare isotopes provided by FRIB into high-quality, low-energy beams. These beams are essential for conducting stopped beam experiments or for subsequent reacceleration. The overarching goal is to advance technology, aiming to increase the beam rate capability of the linear gas stopper for medium-to-heavy-mass rare isotopes by more than tenfold compared to the currently most effective gas stopper in operation, and to improve the purity of the delivered beams. Project Description: The existing technology employed in gas stopping devices designed for low-energy, rare-isotope beams presents limitations in both the purity of extracted beams and the intensities of injected beams. These limitations are incompatible with the requirements of the recently commissioned rare isotope beam facility, FRIB. Our research and development efforts, aligned with the previously outlined objectives, focused on addressing the most critical aspects for enhancing beam-rate capability and purity. Specifically, advanced particle-in-cell simulations were developed and integrated into a simulation pipeline to explore the efficacy of multi-layer RF carpets on increasing ion transport efficiency with high incoming beam rates that generate space charge fields which can limit it. We also explored the possibility of using a collision-induced-dissociation (CID) gas cell to break up molecular contaminant ions that are generated during the stopping process. A prototype CID gas cell was constructed and tested with beams from an offline ion source, validating the concept with the successful demonstration of breaking of molecular ions. The outcome of this research enabled the formulation a conceptual design for a next-generation linear gas stopping device specifically tailored for FRIB. This device is envisioned to deliver rare-isotope-ion beams at a rate of 10 8 particles per second or higher, accompanied by advancements in purity. Methods employed: This project leverages advancements in technologies initially designed for the Advanced Cryogenic Gas Stopper (ACGS), the current state-of-the-art linear gas stopper, through the use of new simulations and beam purification via collision-induced-dissociation. The methods include: 1. Development of a prototype low-energy, low-pressure CID gas stopper. This prototype features a thin, approximately 20 nm, Si 3 N 4 entrance window designed for dissociating stable and rare-isotope molecular ions. The goal is to enhance beam purification and overall efficiency. 2. Creation of Particle-in-cell (PIC) simulations to assess the advantages of multi-layer RF carpets and multi-point extraction for ion transport efficiency. These simulations rely on the 3DCylPIC package, specifically designed for studying devices of this nature. The goal is to quantify and mitigate ion transport losses due to space charge generated in the stopping process of large numbers of ions. 3. Perform ion transport simulations across an RF carpet using an 8-phase travelling wave and evaluate its performance. Compared to the 4-phase RF carpets used in ACGS, the 8-phase carpets will double the wavelength of the generated traveling wave allowing for larger maximum RF amplitudes that could result in improved ion transport efficiency for high-intensity incoming beams when large space charge fields are present. Impact: Tackling the primary challenges associated with transforming high-energy projectile fragment beams into low-energy beams—specifically, addressing efficiency and purity—holds significant promise for advancing FRIB science. This advancement will particularly impact precision mass measurements, laser spectroscopy of short-lived nuclei, and studies in astrophysics and nuclear reactions using reaccelerated beams. These domains play a crucial role in addressing key questions outlined in the 2023 NSAC long-range plan, spanning nuclear structure, nuclear astrophysics, and fundamental symmetries. Additionally, they contribute to addressing 10 out of the 17 benchmarks identified by the NRC RISAC. The development of a next-generation gas stopping device capable of delivering low-energy, rare-isotope beams at a rate of 10 8 particles per second, or more, with high purity holds the potential to unlock experiments that would otherwise be unfeasible. Furthermore, it is expected to reduce the time required for experiments at FRIB, thereby maximizing scientific output. The research and development activities performed as part of this project bolstered essential competencies at FRIB in beam physics and ion source technologies, provided valuable training opportunities for junior scientists.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Prediction of Reactive Nitrous Acid Formation in Rare‐Earth MOFs via ab initio Molecular Dynamics

Abstract Reactive gas formation in pores of metal–organic frameworks (MOFs) is a known mechanism of framework destruction; understanding those mechanisms for future durability design is key to next generation adsorbents. Herein, an extensive set of ab initio molecular dynamics (AIMD) simulations are used for the first time to predict competitive adsorption of mixed acid gases (NO 2 and H 2 O) and the in‐pore reaction mechanisms for a series of rare earth (RE)‐DOBDC MOFs. Spontaneous formation of nitrous acid (HONO) is identified as a result of deprotonation of the MOF organic linker, DOBDC. The unique DOBDC coordination to the metal clusters allows for proton transfer from the linker to the NO 2 without the presence of H 2 O and may be a factor in DOBDC MOF durability. This is a previously unreported mechanisms of HONO formation in MOFs. With the presented methodology, prediction of future gas interactions in new nanoporous materials can be achieved.

Vogel, Dayton J.↗

DOE OSTI2021

Prediction of Reactive Nitrous Acid Formation in Rare‐Earth MOFs via ab initio Molecular Dynamics

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Excess Density as a Descriptor for Electrolyte Solvent Design

Electrolytes mediate interactions between the cathode and anode and determine performance characteristics of batteries. Mixtures of multiple solvents are often used in electrolytes to achieve desired properties, such as viscosity, dielectric constant, boiling point, and melting point. Conventionally, multi-component electrolyte properties are approximated with linear mixing, but in practice, significant deviations are observed. Excess quantities can provide insights into the molecular behavior of the mixture and could form the basis for designing high-performance electrolytes. Here we investigate the excess density of commonly used Li-ion battery solvents such as cyclic carbonates, linear carbonates, ethers, and nitriles with molecular dynamics simulations. We additionally investigate electrolytes consisting of these solvents and a salt. The results smoothly vary with mole percent and are fit to permutation-invariant Redlich-Kister polynomials. Mixtures of similar solvents, such as cyclic-cyclic carbonate mixtures, tend to have excess properties that are lower in magnitude compared to mixtures of dissimilar substances, such as carbonate-nitrile mixtures. We perform experimental testing using our automated test stand, Clio, to provide validation to the observed simulation trends. We quantify the structure similarity using SOAP fingerprints to create a descriptor for excess density, enabling the design of electrolyte properties. To a first approximation, this will allow us to estimate the deviation of a mixture from ideal behavior based solely upon the structural dissimilarity of the components.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS2012

Development and Testing of Molecular Adsorber Coatings

The effect of on-orbit molecular contamination has the potential to degrade the performance of spaceflight hardware and diminish the lifetime of the spacecraft. For example, sensitive surfaces, such as optical surfaces, electronics, detectors, and thermal control surfaces, are vulnerable to the damaging effects of contamination from outgassed materials. The current solution to protect these surfaces is through the use of zeolite coated ceramic adsorber pucks. However, these pucks and its additional complex mounting hardware requirements result in several disadvantages, such as size, weight, and cost related concerns, that impact the spacecraft design and the integration and test schedule. As a result, a new innovative molecular adsorber coating was developed as a sprayable alternative to mitigate the risk of on-orbit molecular contamination. In this study, the formulation for molecular adsorber coatings was optimized using various binders, pigment treatment methods, binder to pigment ratios, thicknesses, and spray application techniques. The formulations that passed coating adhesion and vacuum thermal cycling tests were further tested for its adsorptive capacity. Accelerated molecular capacitance tests were performed in an innovatively designed multi-unit system containing idealized contaminant sources. This novel system significantly increased the productivity of the testing phase for the various formulations that were developed. Work performed during the development and testing phases has demonstrated successful application of molecular adsorber coatings onto metallic substrates, as well as, very promising results for the adhesion performance and the molecular capacitance of the coating. Continued testing will assist in the qualification of molecular adsorber coatings for use on future contamination sensitive spaceflight missions.

Abraham, Nithin↗

DOE OSTI2025

The design space of E(3)-equivariant atom-centred interatomic potentials

Abstract Molecular dynamics simulation is an important tool in computational materials science and chemistry, and in the past decade it has been revolutionized by machine learning. This rapid progress in machine learning interatomic potentials has produced a number of new architectures in just the past few years. Particularly notable among these are the atomic cluster expansion, which unified many of the earlier ideas around atom-density-based descriptors, and Neural Equivariant Interatomic Potentials (NequIP), a message-passing neural network with equivariant features that exhibited state-of-the-art accuracy at the time. Here we construct a mathematical framework that unifies these models: atomic cluster expansion is extended and recast as one layer of a multi-layer architecture, while the linearized version of NequIP is understood as a particular sparsification of a much larger polynomial model. Our framework also provides a practical tool for systematically probing different choices in this unified design space. An ablation study of NequIP, via a set of experiments looking at in- and out-of-domain accuracy and smooth extrapolation very far from the training data, sheds some light on which design choices are critical to achieving high accuracy. A much-simplified version of NequIP, which we call BOTnet (for body-ordered tensor network), has an interpretable architecture and maintains its accuracy on benchmark datasets.

Computer Science↗

NASA NTRS2003

Diagnostics of Carbon Nanotube Formation in a Laser Produced Plume: An Investigation of the Metal Catalyst by Laser Ablation Atomic Fluorescence Spectroscopy

Carbon nanotubes, elongated molecular tubes with diameters of nanometers and lengths in microns, hold great promise for material science. Hopes for super strong light-weight material to be used in spacecraft design is the driving force behind nanotube work at JSC. The molecular nature of these materials requires the appropriate tools for investigation of their structure, properties, and formation. The mechanism of nanotube formation is of particular interest because it may hold keys to controlling the formation of different types of nanotubes and allow them to be produced in much greater quantities at less cost than is currently available. This summer's work involved the interpretation of data taken last summer and analyzed over the academic year. The work involved diagnostic studies of carbon nanotube formation processes occurring in a laser-produced plume. Laser ablation of metal doped graphite to produce a plasma plume in which carbon nanotubes self assemble is one method of making carbon nanotube. The laser ablation method is amenable to applying the techniques of laser spectroscopy, a powerful tool for probing the energies and dynamics of atomic and molecular species. The experimental work performed last summer involved probing one of the metal catalysts, nickel, by laser induced fluorescence. The nickel atom was studied as a function of oven temperature, probe laser wavelength, time after ablation, and position in the laser produced plume. This data along with previously obtained data on carbon was analyzed over the academic year. Interpretations of the data were developed this summer along with discussions of future work. The temperature of the oven in which the target is ablated greatly influences the amount of material ablated and the propagation of the plume. The ablation conditions and the time scale of atomic and molecular lifetimes suggest that initial ablation of the metal doped carbon target results in atomic and small molecular species. The metal atoms survive for several milliseconds while the gaseous carbon atoms and small molecules nucleate more rapidly. Additional experiments and the development of in situ methods for carbon nanotube detection would allow these results to be interpreted from the perspective of carbon nanotube formation.

deBoer, Gary↗

DOE OSTI2022

Mechanistic study of chemical looping reactions between solid carbon fuels and CuO

Copper (Cu) based chemical-looping combustion (CLC) is a promising process that utilizes solid carbon fuel such as coal and biomass. Understanding the reaction kinetics in this process can facilitate the industrial design of CLC units. Here, in this work, molecular dynamics (MD) simulations were performed to investigate the reaction kinetics of n-butane and two simplified solid carbon fuels (lignite and anthracite) with/without copper oxide (CuO) nanoparticle. In addition, experiments were conducted on the thermal characteristics, flammability, and flame speeds of CuO and solid carbon mixtures. For n-butane, oxidation on the CuO surface is the primary reaction since the activation energy of the surface reaction is much lower than that of oxygen (O 2 ) combustion (9.2 vs. 53.3 kcal/mol). On the other hand, for lignite, there is a smaller difference in the activation energy of O 2 combustion and surface reaction (23.04 vs. 6.34 kcal/mol). We hypothesize that some solid carbon fuels can have different reaction kinetics dependent upon temperature. This is proven by the case of a simplified anthracite coal: an Arrhenius plot shows that this solid carbon fuel has two different reaction kinetic regimes and the critical temperature for the change in kinetics is related to the oxygen uncoupling of the CuO nanoparticle. Like the modeling simulations, a change in activation energy is observed in the experimental results, where desorption of molecular oxygen from CuO becomes important.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Water, Solute, and Ion Transport in De Novo-Designed Membrane Protein Channels

Biological organisms engineer peptide sequences to fold into membrane pore proteins capable of performing a wide variety of transport functions. Synthetic de novo-designed membrane pores can mimic this approach to achieve a potentially even larger set of functions. Here, in this work, we explore water, solute, and ion transport in three de novo designed β-barrel membrane channels in the 5–10 Å pore size range. We show that these proteins form passive membrane pores with high water transport efficiencies and size rejection characteristics consistent with the pore size encoded in the protein structure. Ion conductance and ion selectivity measurements also show trends consistent with the pore size, with the two larger pores showing weak cation selectivity. MD simulations of water and ion transport and solute size exclusion are consistent with the experimental trends and provide further insights into structure–function correlations in these membrane pores.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Structural mechanisms of TRPV6 inhibition by ruthenium red and econazole

TRPV6 is a calcium-selective ion channel implicated in epithelial Ca 2+ uptake. TRPV6 inhibitors are needed for the treatment of a broad range of diseases associated with disturbed calcium homeostasis, including cancers. Here we combine cryo-EM, calcium imaging, and mutagenesis to explore molecular bases of human TRPV6 inhibition by the antifungal drug econazole and the universal ion channel blocker ruthenium red (RR). Econazole binds to an allosteric site at the channel’s periphery, where it replaces a lipid. In contrast, RR inhibits TRPV6 by binding in the middle of the ion channel’s selectivity filter and plugging its pore like a bottle cork. Despite different binding site locations, both inhibitors induce similar conformational changes in the channel resulting in closure of the gate formed by S6 helices bundle crossing. The uncovered molecular mechanisms of TRPV6 inhibition can guide the design of a new generation of clinically useful inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Probing multi-dimensional composition spaces in search of strong metallic alloys

Refractory complex concentrated alloys (RCCA) offer exceptionally high-temperature strength compared to pure metals and dilute alloys, but predictive theory for RCCA design is lacking. We present large-scale molecular Dynamics (MD) simulations of crystal plasticity to explore alloy compositions for maximum mechanical strength, focusing on Fe-Ta-W and Nb-Ta-Mo-W alloy families modeled with Embedded Atom Model (EAM) and Spectral Neighbor Analysis Potentials (SNAP). To efficiently guide the search for strong alloy compositions, we employ iterative optimization using Gaussian process regression. Many simulated RCCA compositions exhibit pronounced cocktail strengthening, with strengths surpassing their strongest constituent metal, tungsten. Contrary to expectations, the highest strength is found on binary edges of the RCCA composition space. Detailed analyses of atomistic simulations reveal that, similar to pure BCC metals, plastic response in RCCA is primarily governed by screw dislocations. However, at large strains, dislocation multiplication and interactions (Taylor hardening) become the dominant mechanisms contributing to RCCA strength.

Materials science↗

DOE OSTI2021

Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning- and physics-based simulations on high-performance computers

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods, in this case, developed for linear accelerators, and physics-based methods. The two in silico methods, each have their own advantages and limitations which, interestingly, complement each other. Here, we present an innovative infrastructural development that combines both approaches to accelerate drug discovery. The scale of the potential resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput. We have demonstrated the viability of this workflow for the study of inhibitors for four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead antiviral compounds through repurposing on a variety of supercomputers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Diffraction-quality, ultraflexible protein single crystals engineered with DNA

DNA-functionalized colloidal nanoparticles assemble through flexible, nanoscale DNA hybridization interactions that limit atomic-level structural order. Here, we report a valence-centric strategy that enables DNA-bonded, protein single crystals with unconventional mechanical properties. An octameric enzyme, glutarate L-2-hydroxylase, was site- and number-selectively conjugated with eight self-complementary single-stranded DNA, yielding octavalent molecular bonds. The resulting conjugate assembled into the designed body-centered tetragonal crystals that diffracted to 1.42- to 2.61-angstrom resolution, with contacts mediated by B-form DNA helices spanning 17 to 25 angstroms. Increasing oligonucleotide length induces anisotropic lattice expansion while preserving atomic periodicity, even with partial DNA occupancy. Mechanistic studies suggest that the dynamic motion of unhybridized DNA facilitates crystallization, analogous to fluctuating electron clouds in atomic bonding. Compared with native protein crystals, DNA-hybridized crystals are 23-fold softer. These results challenge the assumption that flexibility is incompatible with structural order and establish a programmable framework for biomolecular crystallization and nanomaterials engineering with atomic precision.

Han, Zhenyu [Department of Chemistry, Northwestern↗

DOE OSTI2025

Understanding and controlling the fundamental photochemistry of protonic solar energy conversion (Final Scientific/Technical Report)

The selectivity and activity of most fuel-forming reactions are tunable by the concentration of electrons, holes, protons, and/or hydroxides. That is one reason why traditional solar energy conversion processes are used to drive these reactions, where light directly increases the concentration of electrons and holes. We, instead, took a different approach, using light to increase the concentration of protons and/or hydroxides. For this, we leveraged photophysical and solid-state physics theories, techniques, and design strategies previously developed for the study of traditional solar energy conversion processes. We designed and fabricated several materials platforms based on molecular photoacid and photobase dyes coupled with ion-exchange polymer membranes and assessed their fundamental photoelectrochemistry. We demonstrated control over built-in electric potentials, photovoltages, proton-transfer kinetics, and efficiency limits to our approach. Understanding the basic science of these dye-sensitized protonic membranes and their photochemical mechanisms is of use to the DOE-relevant processes of solar photochemical fuel formation, solar photodialytic desalination, and solar cells. Moreover, functional materials that we developed from this project may be of use to several broad-reaching fields and may provide the foundation for a completely new, inexpensive, and robust solar energy conversion technology.

14 SOLAR ENERGY↗

DOE OSTI2025

Advanced Modeling and Process-Materials Co-Optimization Strategies for Swing Adsorption Based Gas Separations

This project devised a computational framework for simultaneously co-optimizing pressure swing adsorption process designs along with the sorbent materials (specifically, metal-organic frameworks) to be employed in the associated packed bed columns. The materials optimization aspect involved search over a design space that can describe the material’s molecular structure, while the process optimization aspect considered various process degrees of freedom for steps arising in various cycle configurations. This framework was demonstrated on the separation of nitrogen and carbon dioxide, which arises ubiquitously in a multitude of post-combustion carbon capture and “blue” hydrogen production applications. Our results led to metal-organic framework molecular descriptor choices that are predicted to outperform standard structures used in practice, providing guidance for future metal-organic framework synthesis efforts.

20 FOSSIL-FUELED POWER PLANTS↗