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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A [CoSiH 2 ] Silylene Synthon Provides Modular Access to Homo- and Heterobimetallic [Co=Si=M] (M = Co, Fe) Silicide Complexes

Base-stabilized [BP 3 iPr ](H) 2 CoSiH 2 (DMAP) (1, [BP 3 iPr ] = PhB(CH 2 P i Pr 2 ) 3 – ; DMAP = 4-dimethylaminopyridine) is a rare instance of a synthon for the simplest “parent” silylene complex (LM=SiH 2 ). Complex 1 was accessed in high yields via double Si–H bond activation in SiH 4 by [BP 3 iPr ]Co(DMAP), and in solution, it undergoes rapid exchange between bound and free DMAP by an associative mechanism (as determined by variable-temperature 1 H NMR dynamic studies). The DMAP ligand of 1 is readily displaced by metal-based fragments that bind silicon and cleave the Si–H bonds of the SiH 2 moiety to produce bimetallic [Co=Si=M] (M = Co, Fe) molecular silicides. Thus, treatment of 1 with 0.5 equiv of (LCo I ) 2 (μ-N 2 ) (L = a tripodal ligand) resulted in the spontaneous formation of [BP 3 iPr ](H) 2 Co=Si=Co(H) 2 L (L = [BP 2 tBu Pz], PhB(CH 2 P t Bu 2 ) 2 (pyrazolyl) - (3); Tp", HB(3,5-diisopropylpyrazolyl) 3 – (4)) with the concomitant release of DMAP. The symmetrical silicide [BP 3 iPr ](H) 2 Co=Si=Co(H) 2 [BP 3 iPr ] (5) was prepared by treatment of a mixture of 1 and [BP 3 iPr ]Co(DMAP) with 2 equiv of Ph 3 B, which in this case is required to sequester DMAP as the elimination product Ph 3 B-DMAP. A heterobimetallic silicide, [BP 3 iPr ](H) 2 Co=Si=Fe(H) 2 [SiP 3 iPr ] (7; [SiP 3 iPr ] = PhSi(CH 2 P i Pr 2 ) 3 ), was obtained via in situ KC 8 reduction of [SiP 3 iPr ]FeCl and subsequent addition of 1 and Ph 3 B. These transformations involving a metal–SiH 2 derivative demonstrate a fundamentally new type of reactivity for silylene complexes and provide a unique synthetic method for construction of molecular silicide complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Single- and multi-component chiral supraparticles as modular enantioselective catalysts

Nanoscale biological assemblies exemplified by exosomes, endosomes and capsids, play crucial roles in all living systems. Supraparticles (SP) from inorganic nanoparticles (NPs) replicate structural characteristics of these bioassemblies, but it is unknown whether they can mimic their biochemical functions. Here, we show that chiral ZnS NPs self-assemble into 70–100 nm SPs that display sub-nanoscale porosity associated with interstitial spaces between constituent NPs. Similarly to photosynthetic bacterial organelles, these SPs can serve as photocatalysts, enantioselectively converting L- or D-tyrosine (Tyr) into dityrosine (diTyr). Experimental data and molecular dynamic simulations indicate that the chiral bias of the photocatalytic reaction is associated with the chiral environment of interstitial spaces and preferential partitioning of enantiomers into SPs, which can be further enhanced by co-assembling ZnS with Au NPs. Besides replicating a specific function of biological nanoassemblies, these findings establish a path to enantioselective oxidative coupling of phenols for biomedical and other needs.

Science & Technology - Other Topics↗
DOE OSTI2020

Synthesis, modular composition, and electrochemical properties of lamellar iron sulfides

Transition metal chalcogenides with layered structures are promising materials for energy storage, catalysis, and electronics, among other areas. We have identified a new layered phase of iron sulfide containing interlayer solvated cations. We present an optimized synthesis for the Li + -containing material from an Fe(III) xanthate complex. Structure and composition data indicate the material consists of poorly-ordered iron sulfide layers separated by solvated cations. The lamellar spacing in these materials can be tuned by changing the identity of the cation. Furthermore, the lamellar spacing can also be reversibly tuned by the degree of solvation of the material. The material is electrically conductive and can serve as a pseudocapacitor with comparable performance to commercial materials such as MnO 2 . Finally, these materials also show promise as lithium or sodium ion battery cathodes with good capacity and reversibility.

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

Towards a modular architecture for science factories

Advances in robotic automation, high-performance computing, and artificial intelligence encourage us to propose large, general-purpose science factories with the scale needed to tackle large discovery problems and to support thousands of scientists.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Atomate2: modular workflows for materials science

High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of “universal” machine learning models. While several software frameworks have emerged to support these computational efforts, new developments such as machine learned force fields have increased demands for more flexible and programmable workflow solutions. This manuscript introduces atomate2, a comprehensive evolution of our original atomate framework, designed to address existing limitations in computational materials research infrastructure. Key features include the support for multiple electronic structure packages and interoperability between them, along with generalizable workflows that can be written in an abstract form irrespective of the DFT package or machine learning force field used within them. Our hope is that atomate2's improved usability and extensibility can reduce technical barriers for high-throughput research workflows and facilitate the rapid adoption of emerging methods in computational material science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted.

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

SQMBox: Interfacing a semiempirical integral library to modular ab initio electronic structure enables new semiempirical methods

Ab initio and semiempirical electronic structure methods are usually implemented in separate software packages or use entirely different code paths. As a result, it can be time-consuming to transfer an established ab initio electronic structure scheme to a semiempirical Hamiltonian. Here we present an approach to unify ab initio and semiempirical electronic structure code paths based on a separation of the wavefunction ansatz and the needed matrix representations of operators. With this separation, the Hamiltonian can refer to either an ab initio or semiempirical treatment of the resulting integrals. We built a semiempirical integral library and interfaced it to the GPU-accelerated electronic structure code TeraChem. Equivalency between ab initio and semiempirical tight-binding Hamiltonian terms is assigned according to their dependence on the one-electron density matrix. The new library provides semiempirical equivalents of the Hamiltonian matrix and gradient intermediates, corresponding to those provided by the ab initio integral library. This enables the straightforward combination of semiempirical Hamiltonians with the full pre-existing ground and excited state functionality of the ab initio electronic structure code. We demonstrate the capability of this approach by combining the extended tight-binding method GFN1-xTB with both spin-restricted ensemble-referenced Kohn–Sham and complete active space methods. We also present a highly efficient GPU implementation of the semiempirical Mulliken-approximated Fock exchange. The additional computational cost for this term becomes negligible even on consumer-grade GPUs, enabling Mulliken-approximated exchange in tight-binding methods for essentially no additional cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗