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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Acid Catalysis over Low-Silica Faujasite Zeolites

We report low-silica faujasite (FAU) zeolites (with Si/Al ratio of ca. 1.2–1.8) sustain framework integrity and porosity upon moderate ion exchange (0.01 M NH 4 NO 3 solution for 1 h at ambient temperature), which introduces two kinds of protons, distinctive in reactivity and coordination to the zeolite framework, within supercages (H SUP ). Moderate ion exchange limited within supercages transpires while maintaining full occupancy of Na + cations within associated sodalite cages; this in turn helps stabilize the framework of low-silica H-FAU zeolites. Protons located on site II (H 3630 ) and site III (H 3650 ) within supercages on low-silica FAU zeolites can be classified and enumerated by virtue of infrared spectroscopy, providing an opportunity to compare reactivities of these distinct protons for monomolecular protolytic reactions of propane. Protons on site II exhibit prominently higher reactivity for monomolecular propane dehydrogenation and cracking than protons on site III. Low-silica proton-form FAU zeolites (zeolite X) upon moderate ion exchange possess protons on site III that are unavailable on high-silica FAU zeolites (zeolite Y) and limit ion exchange within supercages, providing unprecedented high-temperature structural and chemical stability (>773 K) and enabling their application as solid-acid catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structure and Site Evolution of Framework Ni Species in MIL-127 MOFs for Propylene Oligomerization Catalysis

A mixed-valence oxotrimer metal–organic framework (MOF), Ni-MIL-127, with a fully coordinated nickel atom and two iron atoms in the inorganic node, generates a missing linker defect upon thermal treatment in helium (>473 K) to engender an open coordination site on nickel which catalyzes propylene oligomerization devoid of any cocatalysts or initiators. This catalyst is stable for ~20 h on stream at 500 kPa and 473 K, unprecedented for this chemistry. The number of missing linkers on synthesized and activated Ni-MIL-127 MOFs is quantified using temperature-programmed oxidation, 1 H nuclear magnetic resonance spectroscopy, and X-ray absorption spectroscopy to be ~0.7 missing linkers per nickel; thus, a majority of Ni species in the MOF framework catalyze propylene oligomerization. In situ NO titrations under reaction conditions enumerate ~62% of the nickel atoms as catalytically relevant to validate the defect density upon thermal treatment. Propylene oligomerization rates on Ni-MIL-127 measured at steady state have activation energies of 55–67 kJ mol –1 from 448 to 493 K and are first-order in propylene pressures from 5 to 550 kPa. Density functional theory calculations on cluster models of Ni-MIL-127 are employed to validate the plausibility of the missing linker defect and the Cossee–Arlman mechanism for propylene oligomerization through comparisons between apparent activation energies from steady-state kinetics and computation. Here this study illustrates how MOF precatalysts engender defective Ni species which exhibit reactivity and stability characteristics that are distinct and can be engineered to improve catalytic activity for olefin oligomerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Sum over Histories Representation for Chemical Kinetics

A new representation for chemical kinetics is introduced that is based on a sum over histories formulation that employs chemical pathways defined at a molecular level. The time evolution of a chemically reactive system is described by enumerating the most important pathways followed by a chemical moiety. An explicit formula for the pathway probabilities is derived and takes the form of an integral over a time-ordered product. When evaluating long pathways, the time-ordered product has a simple Monte Carlo representation that is computationally efficient. A small numerical stochastic simulation was used to identify the most important paths to include in the representation. The method was applied to a realistic H-2/O-2 combustion problem and is shown to yield accurate results.

Bai, Shirong↗
DOE OSTI2017

Grape pomace compost harbors organohalide-respiring Dehalogenimonas species with novel reductive dehalogenase genes

Here, organohalide-respiring bacteria play key roles in the natural chlorine cycle; however, most of the current knowledge is based on cultures from contaminated environments. We demonstrate that grape pomace compost without prior exposure to chlorinated solvents harbors a Dehalogenimonas ( Dhgm ) species capable of using chlorinated ethenes, including the human carcinogen and common groundwater pollutant vinyl chloride (VC) as electron acceptors. Grape pomace microcosms and derived solid-free enrichment cultures were able to dechlorinate trichloroethene (TCE) to less chlorinated daughter products including ethene. 16S rRNA gene amplicon and qPCR analyses revealed the predominance of Dhgm sequences, but no Dehalococcoides mccartyi ( Dhc ) biomarker genes were detected. The enumeration of Dhgm 16S rRNA genes demonstrated VC-dependent growth, and 6.55 ± 0.64 x 10 8 cells were produced per µmole of chloride released. Metagenome sequencing enabled the assembly of a Dhgm draft genome, and 52 putative reductive dehalogenase (RDase) genes were identified. Proteomic workflows identified a putative VC RDase with 49% and 56.1% amino acid similarity to the known VC RDases VcrA and BvcA, respectively. A survey of 1,173 groundwater samples collected from 111 chlorinated solvent-contaminated sites revealed that Dhgm 16S rRNA genes were frequently detected and outnumbered Dhc in 65% of the samples. Dhgm may be more relevant contributors to chlorinated solvent reductive dechlorination in contaminated aquifers than is currently recognized, and non-polluted environments are a source of strictly organohalide-respiring bacteria with novel RDase genes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Computational design of self-assembling cyclic protein homo-oligomers

Self-assembling cyclic protein homo-oligomers play important roles in biology, and the ability to generate custom homo-oligomeric structures could enable new approaches to probe biological function. Here we report a general approach to design cyclic homo-oligomers that employs a new residue-pair-transform method to assess the designability of a protein–protein interface. Here, this method is sufficiently rapid to enable the systematic enumeration of cyclically docked arrangements of a monomer followed by sequence design of the newly formed interfaces. We use this method to design interfaces onto idealized repeat proteins that direct their assembly into complexes that possess cyclic symmetry. Of 96 designs that were characterized experimentally, 21 were found to form stable monodisperse homo-oligomers in solution, and 15 (four homodimers, six homotrimers, six homotetramers and one homopentamer) had solution small-angle X-ray scattering data consistent with the design models. X-ray crystal structures were obtained for five of the designs and each is very close to their corresponding computational model.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Discovery of a weak topological insulating state and van Hove singularity in triclinic RhBi2

Abstract Time reversal symmetric (TRS) invariant topological insulators (TIs) fullfil a paradigmatic role in the field of topological materials, standing at the origin of its development. Apart from TRS protected strong TIs, it was realized early on that more confounding weak topological insulators (WTI) exist. WTIs depend on translational symmetry and exhibit topological surface states only in certain directions making it significantly more difficult to match the experimental success of strong TIs. We here report on the discovery of a WTI state in RhBi 2 that belongs to the optimal space group P $$\bar{1}$$ 1 ¯ , which is the only space group where symmetry indicated eigenvalues enumerate all possible invariants due to absence of additional constraining crystalline symmetries. Our ARPES, DFT calculations, and effective model reveal topological surface states with saddle points that are located in the vicinity of a Dirac point resulting in a van Hove singularity (VHS) along the (100) direction close to the Fermi energy ( E F ). Due to the combination of exotic features, this material offers great potential as a material platform for novel quantum effects.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning stochastic dynamics and predicting emergent behavior using transformers

We show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of the system, and can accurately predict its emergent behavior under conditions not observed during training. We consider a lattice model of active matter undergoing continuous-time Monte Carlo dynamics, simulated at a density at which its steady state comprises small, dispersed clusters. We train a neural network called a transformer on a single trajectory of the model. The transformer, which we show has the capacity to represent dynamical rules that are numerous and nonlocal, learns that the dynamics of this model consists of a small number of processes. Forward-propagated trajectories of the trained transformer, at densities not encountered during training, exhibit motility-induced phase separation and so predict the existence of a nonequilibrium phase transition. Transformers have the flexibility to learn dynamical rules from observation without explicit enumeration of rates or coarse-graining of configuration space, and so the procedure used here can be applied to a wide range of physical systems, including those with large and complex dynamical generators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

High-throughput methods leveraging robotics and computer vision for the development of therapeutic phage cocktails

We present the high-throughput automated screening techniques that are being used to develop bacteriophage-based therapeutic products currently under investigation in human clinical trials to combat urinary tract infections. By integrating modern liquid handling robotics, standardized phenotypic assays, and computer vision-based enumeration, we established a platform capable of reproducibly screening large collections of phages against clinically derived bacterial strain panels. This approach enabled systematic assessment of phage-bacteria interactions at scale, facilitating the identification and optimization of phage cocktails with broad in vitro activity. Although bacteriophage therapy has long been investigated as a strategy for treating bacterial infections, few frameworks exist for developing phage combinations in a reproducible and scalable manner. The methods outlined here address this gap and aim to support the broader development of therapeutic assets available to combat antibiotic resistance.

Penke, Taylor J. R. [Locus Biosciences, Morrisvill↗
DOE OSTI2020

Automated calculation and convergence of defect transport tensors

Defect diffusion is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end-user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewide sampling completeness, to build atomistic kinetic Monte Carlo models on a state-space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for drift and diffusion coefficients, providing a convergence metric by calculating the Kullback–Leibler divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and Hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantum mechanical dataset of 836k neutral closed-shell molecules with up to 5 heavy atoms from C, N, O, F, Si, P, S, Cl, Br

Abstract We introduce the Vector-QM24 (VQM24) dataset comprehensively covering all possible neutral closed-shell small organic and inorganic molecules with up to five heavy (p-block) atoms: C, N, O, F, Si, P, S, Cl, Br. All valid stoichiometries, Lewis-rule-consistent graphs, and stable conformers (identified via GFN2-xTB) were enumerated combinatorially, yielding 577k conformational isomers spanning 258k constitutional isomers and 5,599 unique stoichiometries. DFT (ωB97X-D3/cc-pVDZ) optimizations were performed for all, and diffusion quantum Monte Carlo (DMC@PBE0(ccECP/cc-pVQZ)) energies are provided for 10,793 lowest-energy conformers with up to 4 heavy atoms. VQM24 includes structures, vibrational modes, rotational constants, thermodynamic properties (Gibbs free energies, enthalpies, ZPVEs, entropies, heat capacities), and electronic properties such as atomization, electron interaction, exchange-correlation, dispersion energies, multipole moments (dipole to hexadecapole), alchemical potentials, Mulliken charges, and wavefunctions. Machine learning models of atomization energies on this dataset reveal significantly higher complexity than QM9, with none achieving chemical accuracy. VQM24 offers a rigorous, high-fidelity benchmark for evaluating quantum machine learning models.

Science & Technology - Other Topics↗
DOE OSTI2022

Unveiling the complex configurational landscape of the intralayer cavities in a crystalline carbon nitride

The in-depth understanding of the reported photoelectrochemical properties of the layered carbon nitride, poly(triazine imide)/LiCl (PTI/LiCl), has been limited by the apparent disorder of the Li/H atoms within its framework. To understand and resolve the current structural ambiguities, an optimized one-step flux synthesis (470 °C, 36 h, LiCl/KCl flux) was used to prepare PTI/LiCl and deuterated-PTI/LiCl in high purity. Its structure was characterized by a combination of neutron/X-ray diffraction and transmission electron microscopy. The range of possible Li/H atomic configurations was enumerated for the first time and, combined with total energy calculations, reveals a more complex energetic landscape than previously considered. Experimental data were fitted against all possible structural models, exhibiting the most consistency with a new orthorhombic model (Sp. Grp. Ama2) that also has the lowest total energy. In addition, a new Cu(I)-containing PTI (PTI/CuCl) was prepared with the more strongly scattering Cu(I) cations in place of Li, and most closely matching with the partially-disorder structure in Cmc2 1 . Thus, a complex configurational landscape of PTI is revealed to consist of a number of ordered crystalline structures that are new potential synthetic targets, such as with the use of metal-exchange reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Thermodynamic stability versus kinetic accessibility: Pareto fronts for programmable self-assembly

A challenge in designing self-assembling building blocks is to ensure the target state is both thermodynamically stable and kinetically accessible. These two objectives are known to be typically in competition, but it is not known how to simultaneously optimize them. We consider this problem through the lens of multi-objective optimization theory: we develop a genetic algorithm to compute the Pareto fronts characterizing the tradeoff between equilibrium probability and folding rate, for a model system of small polymers of colloids with tunable short-ranged interaction energies. We use a coarse-grained model for the particles' dynamics that allows us to efficiently search over parameters, for systems small enough to be enumerated. For most target states there is a tradeoff when the number of types of particles is small, with medium-weak bonds favouring fast folding, and strong bonds favouring high equilibrium probability. Additionally, the tradeoff disappears when the number of particle types reaches a value m *, that is usually much less than the total number of particles. This general approach of computing Pareto fronts allows one to identify the minimum number of design parameters to avoid a thermodynamic–kinetic tradeoff. However, we argue, by contrasting our coarse-grained model's predictions with those of Brownian dynamics simulations, that particles with short-ranged isotropic interactions should generically have a tradeoff, and avoiding it in larger systems will require orientation-dependent interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Active learning of chemical reaction networks via probabilistic graphical models and Boolean reaction circuits

Discerning networks of many reactions among multiple interconverting species is challenging. Here, we present a reaction network identification methodology. Our methodology enumerates all stoichiometrically and chemically feasible reactions and requires statistical evidence from effluent concentrations for the inclusion or exclusion of each from the reaction network, contrasting with the commonly seen incremental approach and other work of relying heavily upon chemical intuition and assuming the reactions occurring. Using graph theory alongside an active learning design of experiments that propose maximally informative feeds, we identify the underlying reaction network with minimal laboratory runs. Here, we introduce chemistry-probabilistic graphical modeling and Boolean reaction circuits to statistically quantify which reactions occur from effluent concentrations. Our methodology accurately discerns active reactions, as showcased upon a laboratory network of cross-ketonization of furoic and lauric acid and validated upon simulated networks of thermal and CO 2 -assisted ethane dehydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

“Freedom of design” in chemical compound space: towards rational in silico design of molecules with targeted quantum-mechanical properties

The rational design of molecules with targeted quantum-mechanical (QM) properties requires an advanced understanding of the structure–property/property–property relationships (SPR/PPR) that exist across chemical compound space (CCS). In this work, we analyze these fundamental relationships in the sector of CCS spanned by small (primarily organic) molecules using the recently developed QM7-X dataset, a systematic, extensive, and tightly converged collection of 42 QM properties corresponding to ≈4.2M equilibrium and non-equilibrium molecular structures containing up to seven heavy/non-hydrogen atoms (including C, N, O, S, and Cl). By characterizing and enumerating progressively more complex manifolds of molecular property space—the corresponding high-dimensional space defined by the properties of each molecule in this sector of CCS—our analysis reveals that one has a substantial degree of flexibility or “freedom of design” when searching for a single molecule with a desired pair of properties or a set of distinct molecules sharing an array of properties. To explore how this intrinsic flexibility manifests in the molecular design process, we used multi-objective optimization to search for molecules with simultaneously large polarizabilities and HOMO–LUMO gaps; analysis of the resulting Pareto fronts identified non-trivial paths through CCS consisting of sequential structural and/or compositional changes that yield molecules with optimal combinations of these properties.

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

Discovery of hybrid chemical synthesis pathways with DORAnet

Developing efficient tools for discovering novel synthesis pathways is essential to advance chemical production methods that maximize the use of resources and energy. We introduce DORAnet (Designing Optimal Reaction Avenues Network Enumeration Tool), an open-source computational framework that addresses key limitations in current computer-aided synthesis planning (CASP) tools. DORAnet integrates both chemical/chemocatalytic (i.e., non-enzymatic) and enzymatic transformations, enabling the discovery of hybrid synthesis pathways. With 390 expert-curated chemical/chemocatalytic reaction rules and 3606 enzymatic rules derived from MetaCyc, it provides extensive flexibility for synthetic chemists and biotechnologists. The framework features customizable network expansion strategies, advanced filtering, and pathway search, ranking, and visualization tools. Validated against known reaction data, DORAnet successfully identified both established and novel synthesis routes for key industrial chemicals. In a case study involving 51 high-volume targets, DORAnet frequently ranked known commercial pathways among the top three results, demonstrating its practical relevance and ranking accuracy, while also uncovering numerous alternative (hybrid) synthesis pathways that were highly ranked.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Matrix models and stochastic growth in Donaldson-Thomas theory

We show that the partition functions which enumerate Donaldson-Thomas invariants of local toric Calabi-Yau threefolds without compact divisors can be expressed in terms of specializations of the Schur measure. We also discuss the relevance of the Hall-Littlewood and Jack measures in the context of BPS state counting and study the partition functions at arbitrary points of the Kaehler moduli space. This rewriting in terms of symmetric functions leads to a unitary one-matrix model representation for Donaldson-Thomas theory. We describe explicitly how this result is related to the unitary matrix model description of Chern-Simons gauge theory. This representation is used to show that the generating functions for Donaldson-Thomas invariants are related to tau-functions of the integrable Toda and Toeplitz lattice hierarchies. The matrix model also leads to an interpretation of Donaldson-Thomas theory in terms of non-intersecting paths in the lock-step model of vicious walkers. We further show that these generating functions can be interpreted as normalization constants of a corner growth/last-passage stochastic model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

Non-Grassmann mechanical model of the Dirac equation

We construct a new example of the spinning-particle model without Grassmann variables. The spin degrees of freedom are described on the base of an inner anti-de Sitter space. This produces both {Gamma}{sup {mu}} and {Gamma}{sup {mu}{nu}}-matrices in the course of quantization. Canonical quantization of the model implies the Dirac equation. We present the detailed analysis of both the Lagrangian and the Hamiltonian formulations of the model and obtain the general solution to the classical equations of motion. Comparing Zitterbewegung of the spatial coordinate with the evolution of spin, we ask on the possibility of space-time interpretation for the inner space of spin. We enumerate similarities between our analogous model of the Dirac equation and the two-body system subject to confining potential which admits only the elliptic orbits of the order of de Broglie wavelength. The Dirac equation dictates the perpendicularity of the elliptic orbits to the direction of center-of-mass motion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Identifying Dirac cones in carbon allotropes with square symmetry

A theoretical study is conducted to search for Dirac cones in two-dimensional carbon allotropes with square symmetry. By enumerating the carbon atoms in a unit cell up to 12, an allotrope with octatomic rings is recognized to possess Dirac cones under a simple tight-binding approach. The obtained Dirac cones are accompanied by flat bands at the Fermi level, and the resulting massless Dirac-Weyl fermions are chiral particles with a pseudospin of S = 1, rather than the conventional S = 1/2 of graphene. The spin-1 Dirac cones are also predicted to exist in hexagonal graphene antidot lattices.

74 ATOMIC AND MOLECULAR PHYSICS↗