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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Thermochemistry of Layered and Two-Dimensional Niobium Carbo-Chalcogenides

Two-dimensional transition metal carbo-chalcogenides (TMCCs) represent a novel class of layered materials with tunable electronic structures and high chemical versatility, making them promising candidates for energy and environmental applications. In this work, the structural and thermochemical properties of a series of TMCCs are investigated. High-temperature oxidative solution calorimetry, conducted at 800 °C in molten sodium molybdate (3Na2O·4MoO3), was used to determine the enthalpies of oxidation and formation from the elements at 25 °C, enabling a comprehensive thermodynamic assessment. Comparison of these enthalpies reveals distinct stability trends across the series. Cu0.67Nb2S2C exhibits the most exothermic oxidation enthalpy, indicating a strong thermodynamic driving force for oxidation and reduced resistance to oxidative degradation. Its positive enthalpy of formation from the elements suggests lower thermodynamic stabilization relative to the other compositions, consistent with the energetic influence of Cu and residual Fe within the Nb–S–C framework. In contrast, delaminated Nb2S2C exhibits poor oxidative stability but a highly exothermic enthalpy of formation, consistent with a defect-rich, metastable structural state rather than enhanced lattice stability. These findings establish correlations between crystal structure and energetic stability, providing insights into the design of robust TMCC-based materials for advanced energy and environmental technologies.

Cassell, Nakeshma [Clemson University]↗
DOE OSTI2024

Pairing a Global Optimization Algorithm with EXAFS to Characterize Lanthanide Structure in Solution

Ensemble-average sampling of structures from ab initio molecular dynamics (AIMD) simulations can be used to predict theoretical extended X-ray absorption fine structure (EXAFS) signals that closely match experimental spectra. However, AIMD simulations are time-consuming and resource-intensive, particularly for solvated lanthanide ions, which often form multiple nonrigid geometries with high coordination numbers. Here, to accelerate the characterization of lanthanide structures in solution, we employed the Northwest Potential Energy Surface Search Engine (NWPEsSe), an adaptive-learning global optimization algorithm, to efficiently screen first-shell structures. As case studies, we examine two systems: Eu(NO 3 ) 3 dissolved in acetonitrile with a terpyridine ligand (terpyNO 2 ), and Nd(NO 3 ) 3 dissolved in acetonitrile. The theoretical spectra for structures identified by NWPEsSe were compared to both experimental and AIMD-derived EXAFS spectra. The NWPEsSe algorithm successfully identified the proper solvation structure for both Eu(NO 3 ) 3 (terpyNO 2 ) and Nd(NO 3 )(acetonitrile) 3 , with the calculated EXAFS signals closely matching the experimental spectra for the Eu-ligand complex and showing good similarity for the Nd salt; the better agreement with the ligand-containing structure is attributed to a less dynamic coordination environment due to the rigid ligand. The key advantage of the global optimization algorithm lies in its ability to sample the coordination environment across the potential energy surface and reduce the time required to identify structures from generally a month to within a week. Additionally, this approach is versatile and can be adapted to characterize main-group metal complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

HEPOM: Using Graph Neural Networks for the Accelerated Predictions of Hydrolysis Free Energies in Different pH Conditions

Hydrolysis is a fundamental family of chemical reactions where water facilitates the cleavage of bonds. The process is ubiquitous in biological and chemical systems, owing to water’s remarkable versatility as a solvent. However, accurately predicting the feasibility of hydrolysis through computational techniques is a difficult task, as subtle changes in reactant structure like heteroatom substitutions or neighboring functional groups can influence the reaction outcome. Furthermore, hydrolysis is sensitive to the pH of the aqueous medium, and the same reaction can have different reaction properties at different pH conditions. In this work, we have combined reaction templates and high-throughput ab initio calculations to construct a diverse data set of hydrolysis free energies. The developed framework automatically identifies reaction centers, generates hydrolysis products, and utilizes a trained graph neural network (GNN) model to predict ΔG values for all potential hydrolysis reactions in a given molecule. The long-term goal of the work is to develop a data-driven, computational tool for high-throughput screening of pH-specific hydrolytic stability and the rapid prediction of reaction products, which can then be applied in a wide array of applications including chemical recycling of polymers and ion-conducting membranes for clean energy generation and storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

RLMolLM: Reinforcement Learning-Enhanced Language Model Framework for Inverse Molecular Design

Inverse molecular design faces significant challenges due to vast chemical space and complex property requirements. While language models show promise for molecular generation, they struggle with validity, multi-property optimization, and structural constraints. This work presents RLMolLM, a reinforcement learning framework combining Proximal Policy Optimization (PPO) with genetic algorithms to address these limitations. Our approach optimizes multiple user-specified properties including quantitative estimates of drug-likeness (QED), synthetic accessibility (SA), and ADMET (absorption, distribution, metabolism, excretion, and toxicity) endpoints without requiring complete model retraining, while maintaining capability for scaffold-constrained generation where specific substructures must be preserved. We outperform state-of-the-art methods for molecular optimization, achieving best QED scores across GDB13, Moses, and Zinc datasets with up to 31% improvement over previous methods while maintaining excellent validity, uniqueness, and novelty metrics. For simultaneous multi-property optimization, our framework achieves substantial improvements in ADMET properties including 4.5-fold reduction in hERG toxicity and enhanced Caco-2 permeability compared to Moses dataset. Under structural constraints, the framework significantly improves molecular validity while preserving scaffolds and effectively optimizing properties. In conclusion, this versatile solution advances pharmaceutical and materials molecular design through effective integration of reinforcement learning and genetic algorithms with multi-property optimization and scaffold preservation.

Genetic algorithms↗
DOE OSTI2025

Quantum Electrodynamics Coupled-Cluster at Scale: High-Performance Implementation for Complex Systems

Coupled-cluster theory (CC) is a highly accurate and versatile method for simulating complex interactions within quantum systems. The extension of CC theory to model mixed electron-photon processes with quantum electrodynamics (QED) has improved our capability to predict cavity-modified chemistry, a field where photons are used as cost-effective and eco-friendly alternatives to catalyze/inhibit chemical reactions. However, calculations with CC methods, even without incorporating QED effects, are often prohibitively expensive. Simulations of larger systems require scalable infrastructures that exist for traditional CC methods but not for QED-CC methods. As such, we present a GPU-enabled, high-performance, open-source implementation of the quantum electrodynamics coupled-cluster method with single and double excitations (QED-CCSD) within the ExaChem quantum chemistry software package. ExaChem relies on the Tensor Algebra for Many-body Methods (TAMM) infrastructure: a parallel heterogeneous tensor library designed to achieve scalable performance on modern heterogeneous supercomputing platforms. Furthermore, we discuss theoretical foundations, algorithmic details, and numerical benchmarks to showcase the larger systems that ExaChem can simulate and how the integration of photonic degrees-of-freedom alters their ground-state properties.

Basis sets↗
DOE OSTI2025

How Thermodynamic, Electronic, and Steric Factors Influence Mesitylcopper Oligomers

Mesitylcopper (CuMes) is a highly versatile organocopper reagent used in both organic and inorganic syntheses. It has previously been shown that CuMes exists as a tetrameric or pentameric cyclic oligomer [CuMes] n (n = 4, 5), both in solution and in the solid state. The bonding arrangement between the [CuMes] units has qualitatively been described as localized three-center twoelectron (3c-2e) bonds. However, the electronic, structural, and thermodynamic forces driving this aggregation are still not well understood. For this reason, we employed density functional theory (DFT) calculations to study mesitylcopper as a monomeric [CuMes] unit and [CuMes]n oligomers with n = 2 to n = 7. We found that there is a strong electronic driving force for aggregation caused by strong mixing between the Cu’s d orbitals and Mes’s π orbitals in oligomers larger than the dimer. This mixing is only optimized in oligomers with n ≥ 3, where the mesityl group is no longer bonded to a single copper center but instead becomes a bridging ligand. Beyond the trimer, steric and entropic factors become relevant for determining the relative stabilities of the different aggregates, with midsized oligomers (n = 4−5) having the optimal balance between the electronic Cu−C bonding character, Cu···Cu attractive forces, entropy, reduced internal ring strain, and reduced steric interactions between the mesityl groups.

Copper↗
DOE OSTI2026

Directed Gas-Phase Formation of The Propargyl Family of Resonance-Stabilized Radicals in The Reactions of Ground-State Carbon Atoms (C; 3 P j ) with Butene Isomers (C 4 H 8 ): Dimethylpropargyl and Ethylpropargyl

The propargyl radical (C 3 H 3 ) is the simplest resonance-stabilized free radical (RSFR), but how does stepwise methyl substitution in the alkene reactant affect its dynamics of their formation? We report a crossed molecular beam study of the reactions of atomic carbon (C, 3 P j ) with four butene isomers (C 4 H 8 ) under single collision conditions at a collision energy of 28 ± 2 kJ mol −1 . Barrierless addition of atomic carbon to the alkene C=C bond triggers ring opening to triplet substituted allenes—a de facto insertion mechanism—followed by unimolecular decomposition via atomic hydrogen (H), methyl (CH 3 ) or ethyl (C 2 H 5 ) loss, yielding a family of propargyl‑type RSFRs. RRKM calculations reveal that the branching ratios are highly sensitive to the alkene structure. While the methyl loss channel, affording 1‑methylpropargyl, dominates for 2 butenes (80–90%), the predicted hydrogen atom loss channel (≈10%) leading to 1,3 dimethylpropargyl is identified in the experiment by comparison with theoretical energetics. For isobutene, a near‑equal competition is seen, with the reaction producing 3‑methylpropargyl (≈50%) and 1,1‑dimethylpropargyl (≈40%), along with 2‑vinylallyl (≈5%), whose formation is supported by the experimental data. Most notably, the reaction with 1 butene uniquely favors an enthalpically driven hydrogen shift, eventually producing 1 vinylallyl (≈38%), which is assigned based on the excellent agreement between the measured and calculated reaction exothermicity. Rapid entropically favored fragmentation channels yield ≈40% of propargyl type species (propargyl, 1- and 3-ethylpropargyls), slightly outcompeting the allyl type product. Furthermore, these results establish a systematic progression from C 2 H 4 to C 4 H 8 , where the increasing alkyl substitution unlocks new fragmentation channels, providing a versatile gas phase route to alkylated RSFRs—key intermediates in the growth of methylated and ethylated PAHs and aliphatic chains in combustion and cold interstellar environments (molecular clouds).

Alkyls↗
DOE OSTI2024

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations toward the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Charge Tethering Drives Intermediate-Range Order and Slow Dynamics in Zwitterionic Liquids

We have synthesized and characterized a family of zwitterionic liquids (ZwLs) based on the poly(ethylene oxide) imidazolium cation and the alkyl sulfonate anion. To better rationalize ZwLs′ structural behavior and networkforming properties, we have computationally studied them in contrast to isostructural but chemically untethered ionic liquid (IL) analogues. Perhaps surprisingly, it is the molecular liquids and not the ILs that show the most selfassembly and intermediate-range order associated with scattering prepeaks; the ZwLs display also the slowest dynamics. This is consistent with prior work showing the importance of networks in considering the viscoelastic relaxation of liquids. We find that, because of their significantly large molecular dipoles, these zwitterions are versatile network-building blocks that result in highly viscous liquids. From a structural perspective, networks in these ZwLs sit somewhere in between what would be true chemical connectivity and the Coulombic networks observed in ionic liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

New Dimension in Ab Initio Electronic Structure Theory: Temperature, Pressure, and Chemical Potential

Ab initio electronic structure theory has transformed gas-phase molecular science with its predictive ability. In the attempt to bring such predictive ability to macroscopic systems and condensed matter, the theory must integrate quantum mechanics with statistical thermodynamics, so that thermodynamic functions such as free energy, internal energy, entropy, and chemical potentials are computed as functions of temperature in a systematically converging series of approximations. Here, a general, versatile strategy of elevating ab initio electronic structure theory to nonzero temperatures is introduced and discussed.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Intrinsic Layer-Dependent Surface Energy and Exfoliation Energy of van der Waals Materials

Stacking and twisting 2D van der Waals (vdW) layers have become versatile platforms to tune the electron correlation. These platforms rely on exfoliating vdW materials down to a single vdW layer and a few vdW layers. We calculate the intrinsic layer-dependent surface and exfoliation energies of typical vdW materials such as graphite, h-BN, black P, MX 2 (M = Mo or W; X = S, Se, or Te), MX (M = Ga or In; X = S, Se, or Te), Bi 2 Te 3 , and MnBi 2 Te 4 using density functional theory. For exchange-correlation functionals with explicit vdW interaction, a single vdW layer always has the smallest surface energy, giving a surface energy reduction when compared to that of thicker vdW layers. Furthermore, the magnitude of this surface energy reduction quickly decreases with an increase in the number of atomic layers inside the single vdW layer for different vdW materials. Such atomic-layer dependence in surface energy reduction helps explain the different effectiveness of exfoliation for different vdW materials down to a single vdW layer.

Anode materials↗
DOE OSTI2024

Recent Advances in Immobilizing and Benchmarking Molecular Catalysts for Artificial Photosynthesis

Transition metal complexes have been widely used as catalysts or chromophores in artificial photosynthesis. Traditionally, they are employed in homogeneous settings. Despite their functional versatility and structural tunability, broad industrial applications of these catalysts are impeded by the limitations of homogeneous catalysis such as poor catalyst recyclability, solvent constraints (mostly organic solvents), and catalyst durability. Over the past few decades, researchers have developed various methods for molecular catalyst heterogenization to overcome these limitations. Here, in this review, we summarize recent developments in heterogenization strategies, with a focus on describing methods employed in the heterogenization process and their effects on catalytic performances. Alongside the in-depth discussion of heterogenization strategies, this review aims to provide a concise overview of the key metrics associated with heterogenized systems. We hope this review will aid researchers who are new to this research field in gaining a better understanding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Induced Chirality in QDs Using Thermoresponsive Elastin-like Polypeptides

Circular dichroism (CD) spectroscopy has emerged as a potent tool for probing chiral small-molecule ligand exchange on natively achiral quantum dots (QDs). In this study, we report a novel approach to identifying QD–biomolecule interactions by inducing chirality in CdS QDs using thermoresponsive elastin-like polypeptides (ELPs) engineered with C-terminal cysteine residues. Our method is based on a versatile two-step ligand exchange process starting from monodisperse oleate-capped QDs in nonpolar media and proceeding through an easily accessed achiral glycine-capped QD intermediate. Successful conjugation of the ELPs onto the QDs is confirmed by the diagnostic CD response corresponding to the QD electronic transitions in the visible range. The resulting ELP:CdS conjugates demonstrate thermally reversible coacervation, as observed through dynamic light scattering, small-angle X-ray scattering, and electron microscopy. Furthermore, this research provides a foundation for using induced chirality in QD electronic transitions to probe QD conjugation to complex peptides and proteins, opening pathways for designing dynamic, stimuli-responsive hybrid nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Implementation of Genetic Algorithms to Optimize Metal–Organic Frameworks for CO 2 Capture

Metal-organic frameworks (MOFs) are promising materials for CO 2 capture with the potential to use less energy than current industrial CO 2 capture methods. MOFs are highly versatile sorbents, and there is an almost unlimited number of MOFs that could be synthesized. In this work, we used a genetic algorithm (GA) and grand canonical Monte Carlo (GCMC) simulations to efficiently search for high-performing MOFs for CO 2 capture. We analyzed the effects of important GA parameters, including the mutation probability, the number of MOFs per generation and the number of GA generations, on the GA performance. Here, we performed GCMC simulations on-the-fly during the GA procedure to determine the performance of proposed MOFs and optimized their structures using multiple objective functions across different topologies. The GA was able to determine top-performing MOFs balancing CO 2 selectivity versus working capacity and reduced the cost of molecular simulations by a factor of 25 versus brute-force screening of an entire database of structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Renewable and Biodegradable Polyurethane Foams with Aliphatic Diisocyanates

The transition to renewable plastics will require the development of substitutes with existing industrial standards and manufacturing processes. Polyurethanes (PU), versatile plastics, are traditionally dominated by aromatic diisocyanates, which are challenging to derive from renewable sources. However, for higher biocontent, it is crucial to utilize aliphatic diisocyanates, which can be sourced from renewable plant or algae waste streams. Historically, PU foams relied on aromatic diisocyanates for essential hard segments, resulting in desired physical properties. Here, we report the generation of high-performance renewable and biodegradable PU foams utilizing aliphatic diisocyanates and aromatic polyols, translating hard segments into the polyester polyol component using biosourced furan dicarboxylic acid (FDCA) monomers. We demonstrate that an FDCA-based PU is suitable for foams with performance characteristics that meet commercial tolerances and can biodegrade under backyard compost conditions. Here, this demonstrates steps toward redesigning traditional petrochemical-based polymers to accommodate new biological monomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dual-Responsive Macromolecular Surfaces with Binary Patterns

The development of nanopatterned interfaces incorporating multiple stimuli-responsive polymers has great potential for advancing smart sensors and molecular capture devices, yet it remains challenging due to limitations in patterning techniques and “grafting from” methods. Here, we present a binary-patterned surface featuring honeycomb-shaped photothermal polypyrrole (PPy) and thermally responsive poly(ethylene glycol methyl ether acrylate-co-poly(ethylene glycol) methyl ether acrylate) [poly(EGMEA-co-PEGMEA)] brushes within the cavities, fabricated using colloidal lithography and surface-initiated photoinduced electron transfer-reversible addition–fragmentation chain transfer (SI-PET-RAFT) polymerization. The morphology of the surface can be precisely tuned by adjusting the height of each domain. This design integrates unique topographical features with the stimuli-responsiveness of the polymer, enabling the collapse of the copolymer brushes through direct heating or photothermal conversion of PPy under near-IR light. In conclusion, this innovative system offers potential capture-release functionality, providing versatility for diverse applications and enhancing adaptability across different functional scenarios.

Copolymers↗
DOE OSTI2025

Backbone Dynamics of Bottlebrush Polymers Studied by Neutron Scattering

Bottlebrush polymers have a versatile architecture that is highly customizable due to the combination of a linear backbone and side chains. As a result of the chemical tethering of the side chains, both parts cannot be easily be separated. Huge effort is seen regarding the dynamical behavior of the side chains or the entire bottlebrush polymer, whereas few studies are available considering the backbone. Here, isotopic labeling in combination with quasi-elastic neutron scattering was used to compare the dynamical behavior of the bottlebrush’s backbone with the side chain dynamics. Keeping the side chains deuterated, (h-PNB)- g -(d-PPO), leads to the scattering signal dominated by backbone dynamics, while the fully protonated sample, (h-PNB)- g -(h-PPO), gives side chain dynamics. Both results reveal slower dynamics associated with the backbone with less heterogeneity, as seen for the side chains. Additionally, a plasticizer effect for the backbone dynamics is confirmed by extracting the glass transition temperature and comparing it with pure linear PNB.

neutron scattering↗
DOE OSTI2025

Polyhalohydrins: Investigating Vicinal Functionalities by Ring-Opening of Epoxides on Polyolefins

Halohydrins are functional groups that are underexplored in polymer science. This study synthesized and examined structure–property relationships of halohydrin-functionalized polymers derived from polycyclooctene (PCOE), which was obtained via ring-opening metathesis polymerization (ROMP). The polyhalohydrins, including polychlorohydrin, polybromohydrin, and polyiodohydrin, were produced through a two-step process involving epoxidation of PCOE followed by epoxide ring-opening using hydrochloric, hydrobromic, or hydroiodic acid. These stereoirregular and regioirregular polymers are amorphous as measured by differential scanning calorimetry and X-ray scattering. Lap joint shear testing revealed an enhanced adhesive performance in polychlorohydrin and polybromohydrin, with the former demonstrating nearly three times the ultimate shear stress compared to a model polyethylene, hydrogenated PCOE. Additionally, contact angle measurements and surface free energy analysis showed an increase in hydrophilicity and polarity from iodine- to bromine- to chlorine-functionalized polyhalohydrins, aligning with trends in adhesion strength. Furthermore, these results underscore the potential of halohydrin functionalization as a versatile approach for tuning surface properties, offering new opportunities for polymer-to-polymer transformations.

Functional groups↗