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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mediated Inner‐Sphere Electron Transfer Induces Homogeneous Reduction of CO 2 via Through‐Space Electronic Conjugation**

Abstract The electrocatalytic reduction of CO 2 is an appealing method for converting renewable energy sources into value‐added chemical feedstocks. We report a co‐electrocatalytic system for the reduction of CO 2 to CO comprised of a molecular Cr complex and dibenzothiophene‐5,5‐dioxide (DBTD) as a redox mediator, which achieves high activity (TOF=1.51–2.84×10 5 s −1 ) and quantitative selectivity. Under aprotic or protic conditions, DBTD produces a co‐electrocatalytic response with 1 by coordinating trans to the site of CO 2 binding and mediating electron transfer from the electrode with quantitative efficiency for CO. This assembly is reliant on through‐space electronic conjugation between the π frameworks of DBTD and the bpy fragment of the catalyst ligand, with contributions from dispersive interactions and weak sulfone coordination.

Hooe, Shelby L.↗
DOE OSTI2025

Revealing Parallel Inter‐ and Intra‐Ligand Charge Transfer Dynamics in [Ru(L) 2 (dppz)] 2+ Molecular Lightswitch with N K‐Edge X‐Ray Absorption Spectroscopy

In photoactive metal complexes the localization of photoexcited charges dictates the site of chemical reactivity, but few studies measure the charge redistribution in these systems with spatial precision. Herein, we track the inter- and intra-ligand charge transfer processes that underpin light-driven charge separation in the well-studied “molecular lightswitch” [Ru(bpy) 2 dppz] 2+ (aqueous [Ruthenium II (2,2′-bipyridine)2(dipyrido[3,2-a:2′,3′-c]phenazine)] 2+ [Cl − ] 2 ) by probing the electronic structure of ligand nitrogen atoms in real-time using ultrafast X-ray absorption spectroscopy and first principles calculations. We confirm the localization of excited electron density on the phenazine N atoms of dppz and we newly identify two parallel electron transfer pathways to populate this state. Sub-70 fs electron transfer to the phenazine portion of dppz is observed and attributed to intra-ligand electron transfer following Ru-to-dppz metal-to-ligand charge transfer (MLCT) excitation. This fast charge transfer was not reported in prior ultrafast studies. The slower (ca. 2 ps) charge transfer reported extensively in time-resolved optical absorption and emission studies is reassigned here to inter-ligand electron “hopping” between nearly isoenergetic ligand moieties following Ru-to-bpy MLCT excitation. In conclusion, the results demonstrate much faster charge separation than previously identified in this well-studied system, highlighting how extended azaacene ligand motifs promote the competitive charge transfer processes needed to drive light-driven electron transfer chemistry.

Donor-acceptor systems↗
DOE OSTI2024

Modeling Surface-Enhanced Raman Scattering of Au-Pyrazine and Au-Pyrazine-Au Nanorod Dimer Systems with the TD-DFTB Method

This study investigates Raman scattering from a pyrazine molecule adsorbed on gold nanorod surfaces using the time-dependent density functional tight-binding (TD-DFTB) method. We analyze surface enhanced Raman scattering (SERS) of the molecule for two configurations: one where the molecule is adsorbed on a single gold nanorod forming Au-pyrazine complex, and another where it forms a nano-junction Au-pyrazine-Au dimer system. These two configurations offer distinct chemical environments for the molecule and different local field enhancements, with the dimer systems generating enhanced hotspot regions at the junctions. We present results for nanojunction, Au-pyrazine-Au dimer structures, for variable nanogap sizes that lead to shift in the plasmon energy. The study identifies contributions to the SERS enhancements from chemical, electromagnetic, and resonance charge transfer mechanisms. Our results show that the chemical mechanism provides enhancement factors in the range of 10 2 –10 3 , while the electromagnetic enhancements are on the order of 10 3 –10 5 for monomer systems and 10 6 –10 8 for dimer structures. We present results for a nanorod with a length of 5.3 nm and a width of 0.52 nm, consisting of 121 gold atoms.

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

Modulating the Extent of Anisotropic Cuprophilicity via High Pressure with Piezochromic Luminescence Sensitization

We report metallophilicity has been widely studied as a fundamental supramolecular interaction. However, the extent and directionality thereof remain controversial. A major obstacle lies in the difficulty to separately control the geometry and chemical composition. Herein, we address this challenge by modulating metallophilicity with mechanical pressure. Using a multinuclear Cu(I) complex as model system, we report anomalous anisotropies of (supra)molecular structures, vibrations, and interaction energies upon isotropic compression as well as concomitant (essentially turn-on) piezochromic luminescence enhancement with ~10 3 modulation. The in situ characterizations indicate opposite behaviors of contact distances and cuprophilic interactions for intermolecular vs intramolecular Cu-Cu pairs under pressure. Theoretical calculations break down the attractive and repulsive forces associated with cuprophilicity, its spontaneous 4p-3d hybridization origin, and direction-dependent interaction strength. The use of isotropic mechanical force reveals the intrinsic anisotropy of metallophilicity in multinuclear systems.

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

Automated Nanocrystal Synthesis: Lessons from 25 Years of Robots, Microfluidics, and Machine Learning

Here, this perspective highlights the evolution of techniques for automating the synthesis of colloidal nanocrystals. Over the past 25 years, microfluidic reactors and robotic workflows have been developed to enhance the reproducibility of nanocrystal synthesis, facilitate rapid screening of reaction conditions, optimize material properties, and perform multistep syntheses of high-quality nanoparticles with complex heterostructures. Modern automated systems are now valued for their ability to generate robust data sets for validating physical models, supporting chemical mechanisms, training machine learning models, and for directing autonomous experimentation. We discuss the early challenges and limitations of these technologies and present key lessons for effectively utilizing automated and ML-guided tools to accelerate nanocrystal discovery for the next 25 years.

Nanocrystals↗
DOE OSTI2023

XFEL Microcrystallography of Self-Assembling Silver n -Alkanethiolates

New synthetic hybrid materials and their increasing complexity have placed growing demands on crystal growth for single-crystal X-ray diffraction analysis. Unfortunately, not all chemical systems are conducive to the isolation of single crystals for traditional characterization. Here, small-molecule serial femtosecond crystallography (smSFX) at atomic resolution (0.833 Å) is employed to characterize microcrystalline silver n-alkanethiolates with various alkyl chain lengths at X-ray free electron laser facilities, resolving long-standing controversies regarding the atomic connectivity and odd–even effects of layer stacking. smSFX provides high-quality crystal structures directly from the powder of the true unknowns, a capability that is particularly useful for systems having notoriously small or defective crystals. We present crystal structures of silver n-butanethiolate (C4), silver n-hexanethiolate (C6), and silver n-nonanethiolate (C9). We show that an odd–even effect originates from the orientation of the terminal methyl group and its role in packing efficiency. We also propose a secondary odd–even effect involving multiple mosaic blocks in the crystals containing even-numbered chains, identified by selected-area electron diffraction measurements. Finally, we conclude with a discussion of the merits of the synthetic preparation for the preparation of microdiffraction specimens and compare the long-range order in these crystals to that of self-assembled monolayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Chemically controlled shape-morphing of elastic sheets

Two-dimensional responsive materials that change shape into complex three-dimensional structures are valuable for creating systems ranging from wearable electronics to soft robotics. Typically, the final 3D structure is unique and predetermined through the materials’ processing. Here, we use theory and simulation to devise a distinctive approach for driving shape changes of 2D elastic sheets in fluid-filled microchambers. The sheets are coated with catalyst to generate controllable fluid flows, which transform the sheets into complex 3D shapes. A given shape can be achieved by patterning the arrangement of the catalytic domains on the sheet and introducing the appropriate reactant to initiate a specific catalytic reaction. Moreover, a single sheet that encompasses multiple catalytic domains can be transformed into a variety of 3D shapes through the addition of one or more reactants. Materials systems that morph on-demand into a variety of distinct structures can simplify manufacturing processes and broaden the utility of soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Chemical imaging of individual stratospheric particles sampled over North America

The increasing size, severity, and frequency of wildfires have led to dramatic increases in particulate matter concentrations in the troposphere. Severe wildfires can generate intense convective systems capable of transporting large quantities of biomass burning organic aerosols (BBOA) to the upper troposphere and lower stratosphere (UTLS). Chemically complex organic matter and light-absorbing carbonaceous material is introduced into stratospheric regions that were historically isolated from direct surface emissions. In this study, stratospheric particles were sampled over North America during the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) campaign, an aircraft-based research project designed to characterize convective perturbation in the UTLS. Particle samples collected from six research flights during summer 2022 were analyzed using Computer-Controlled Scanning Electron Microscopy and Scanning Transmission X-ray Microscopy to investigate particle size distributions, morphology, chemical composition, and mixing state of stratospheric particles along transects across the continental United States and adjacent Pacific Ocean airspace. Analysis revealed that all sampled particles contained detectable levels of carbon, with most exhibiting organic volume fractions of 0.37 ± 0.20. Notably, about 5% of the particles also contained soot inclusions, which indicates the presence of refractory black carbon transported to stratospheric altitudes and provides direct evidence of wildfire-derived black carbon reaching the UTLS. Typical particle morphology exhibits organic shells over soot and inorganic cores and suggests secondary processing and aging of BBOA during transport to and within the UTLS. These findings provide compelling evidence that wildfire emissions play a critical role in affecting the long-term composition and radiative properties of stratospheric particles.

Sharpe, Steven [Purdue Univ., West Lafayette, IN (↗
DOE OSTI2024

Compositionally complex carbide ceramics: A perspective on irradiation damage

Extensive experimental and computational studies have demonstrated outstanding physical and chemical properties of the novel materials of compositionally complex carbides (CCCs), enabling their promising applications in advanced fission and fusion energy systems. This perspective provides a comprehensive overview of radiation damage behavior reported in the literature to understand the fundamental mechanisms related to the impact of multi-principal metal components on phase stability, irradiation-induced defect clusters, irradiation hardening, and thermal conductivity of compositionally complex carbides. Several future research directions are recommended to critically evaluate the feasibility of designing and developing new ceramic materials for extreme environments using the transformative “multi-principal component” concept. Compared to the existing materials for nuclear applications including stainless steels, nickel alloys, ZrC, SiC, and potentially high-entropy alloys, as well as certain other compositionally complex ceramic families. CCCs appear to be more resistant to amorphization, growth of irradiation defect clusters, and void swelling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling Combustion Reaction ODEs with Neural Networks

The chemistry of combustion reactions is complex as it involves many species and reactions. In practice, such a system is often modeled computationally using an empirically derived chemical mechanism. Given the large range of reaction rates, the system is then time evolved using a stiff ODE solver. However, even when reduced chemical mechanisms are employed, the system can become computationally expensive for two-dimensional or three-dimensional systems. Such systems can also face problems with instability. As such, it is desirable to find a cheaper, stable alternative to solving the reaction system. Neural networks offer the potential to learn these reaction ODEs and time evolve a combustion reaction in a more cost-efficient manner than stiff ODE solvers. In this study, a variety of neural networks are trained on zero-dimensional Cantera simulations of methane combustion with varying initial conditions. Several predictive approaches as well as several neural network architectures (artificial neural network with dropout, ResNet, and Neural ODE) are compared in their ability to predict combustion trajectories. Promising models are then identified.

combustion kinetics↗
DOE OSTI2021

A Deep Learning Modeling Framework to Capture Mixing Patterns in Reactive-Transport Systems

Prediction and control of chemical mixing are vital for many scientific areas such as subsurface reactive transport, climate modeling, combustion, epidemiology, and pharmacology. Due to the complex nature of mixing in heterogeneous and anisotropic media, the mathematical models related to this phenomenon are not analytically tractable. Numerical simulations often provide a viable route to predict chemical mixing accurately. However, contemporary modeling approaches for mixing cannot utilize available spatial-temporal data to improve the accuracy of the future prediction and can be compute-intensive, especially when the spatial domain is large and for long-term temporal predictions. To address this knowledge gap, in this work we will present in this paper a deep learning (DL) modeling framework applied to predict the progress of chemical mixing under fast bimolecular reactions. This framework uses convolutional neural networks (CNN) for capturing spatial patterns and long short-term memory (LSTM) networks for forecasting temporal variations in mixing. By careful design of the framework—placement of non-negative constraint on the weights of the CNN and the selection of activation function, the framework ensures non-negativity of the chemical species at all spatial points and for all times. Our DL-based framework is fast, accurate, and requires minimal data for training. The time needed to obtain a forecast using the model is a fraction (≈ O(-6)) of the time needed to obtain the result using a high-fidelity simulation. To achieve an error of 10% (measured using the infinity norm) for capturing local-scale mixing features such as interfacial mixing, only 24% to 32% of the sequence data for model training is required. To achieve the same level of accuracy for capturing global-scale mixing features, the sequence data required for model training is 64% to 70% of the total spatial-temporal data. Hence, the proposed approach—a fast and accurate way to forecast long-time spatial-temporal mixing patterns in heterogeneous and anisotropic media—will be a valuable tool for modeling reactive-transport in a wide range of applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Interfacial properties in energy storage systems studied by soft x-ray absorption spectroscopy and resonant inelastic x-ray scattering

Interfacial behaviors and properties play critical roles in determining key practical parameters of electrochemical energy storage systems, such as lithium-ion and sodium-ion batteries. Soft x-ray spectroscopy features shallow penetration depth and demonstrates inherent surface sensitivity to characterize the interfacial behavior with elemental and chemical sensitivities. Here, we present a brief survey of modern synchrotron-based soft x-ray spectroscopy of the interface in electrochemical energy storage systems. The technical focus includes core-level spectroscopy of conventional x-ray absorption spectroscopy and resonant inelastic x-ray scattering (RIXS). We show that while conventional techniques remain powerful for probing the chemical species on the surface, today’s material research studies have triggered much more demanding chemical sensitivity that could only be offered by advanced techniques such as RIXS. Another direction in the field is the rapid development of various in situ/operando characterizations of complex electrochemical systems. Notably, the solid-state battery systems provide unique advantages for future studies of both the surface/interface and the bulk properties under operando conditions. We conclude with perspectives on the bright future of studying electrochemical systems through these advanced soft x-ray spectroscopic techniques.

25 ENERGY STORAGE↗
DOE OSTI2021

Mediated Inner–Sphere Electron Transfer Induces Homogeneous Reduction of CO 2 via Through–Space Electronic Conjugation

The electrocatalytic reduction of CO 2 is an appealing method for converting renewable energy sources into value-added chemical feedstocks. We report a co-electrocatalytic system for the reduction of CO 2 to CO comprised of a molecular Cr complex and dibenzothiophene-5,5-dioxide (DBTD) as a redox mediator, which achieves high activity (TOF=1.51–2.84×10 5 s –1 ) and quantitative selectivity. Under aprotic or protic conditions, DBTD produces a co-electrocatalytic response with 1 by coordinating trans to the site of CO 2 binding and mediating electron transfer from the electrode with quantitative efficiency for CO. Furthermore, this assembly is reliant on through-space electronic conjugation between the π frameworks of DBTD and the bpy fragment of the catalyst ligand, with contributions from dispersive interactions and weak sulfone coordination.

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

Ionic Liquid-Enhanced Interfaces to Boost Reactive C O2 Capture

The addition of ionic liquids (ILs) to a mixture containing a molecular solvent and other ionic species can induce the heterogeneous redistribution of cations and anions at the gas–liquid interface. This nonuniform redistribution of cations and anions driven by the differences in the solvophilicity of ions can improve the thermophysical and interfacial properties of such mixtures, creating a local chemical environment that is conducive to some reactions. In this work, ILs are added to a mixture of potassium hydroxide (KOH) and ethylene glycol (EG), used as a reactive absorbent and electrolyte in the migration-assisted moisture-gradient (MAMG) process for CO 2 capture. Molecular dynamics (MD) simulations are employed to probe into the effects of complex ion–ion and ion–solvent interactions and to examine the chemical composition at the gas–liquid interface. A total of 12 systems are investigated using molecular simulations to identify trends in the performance of IL additives based on the choice of cation, anion, and IL concentration. The cation effects are studied using IL additives based on 1-ethyl-3-methylimidazolium ([EMIM] + ) and 1-butyl-3-methylimidazolium ([BMIM] + ), while the impact of anions is examined using additives based on dicyanamide [DCA] − , triflate [TfO] − , bistriflimide [NTf 2 ] − , and hexafluorophosphate [PF 6 ] − anions, respectively. The influence of the IL concentration is also evaluated at molar concentrations between 1% and 4%. The simulation results indicate that the use of IL additives can affect the physical CO 2 solubility, surface tension, and the localization of CO 2 around the [OH] − ions at the gas–liquid interface. It is also evident that the choice of cations, anions, and IL concentration determines the extent to which the IL additives impact the local physicochemical properties. Physical dissolution, diffusive transport, and interaction with [OH] − are critical intermediate steps toward reactive CO 2 capture using a liquid absorbent. Hence, the improvement in one or more of these properties, aided by IL additives, is expected to improve the overall CO 2 capture performance. Experiments reaffirmed the impact of IL additives on CO 2 capture performance and the sensitivity to the choice of the cation, anion, and concentration of the IL additive.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

NWChem: Past, present, and future

Specialized computational chemistry packages have permanently reshaped the landscape of chemical sciences by providing tools to support and guide the experimental effort and for prediction of chemical and materials properties. In this regard, a special role has been played by electronic structure packages where complex chemical and materials processes can be modeled using first-principle-driven methodologies. Over the last few decades, the rapid development of computing technologies and a tremendous increase in computational power has offered a unique chance to study complex chemical transformations using sophisticated and predictive many-body techniques to describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, a critical role has been played by novel parallel algorithms capable of taking advantage of computational resources to address polynomial scaling of electronic structure methods. NWChem was among the first electronic structure codes that focused on delivering scalable performance for electronic structure simulations. Herein, we briefly review the NWChem suite of computational codes including its history, design principles, parallel tools, current capabilities, outreach and outlook.

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

X-ray Spectroscopy Characterization of Electronic Structure and Metal–Metal Bonding in Dicobalt Complexes

Developing multimetallic complexes with tunable metal–metal interactions has long been a target of synthetic inorganic chemistry efforts due to the unique properties that such compounds can exhibit. However, understanding relationships between metal–metal bonding and chemical properties is challenging due to system-dependent factors that influence metal–metal and metal–ligand interactions, including ligand identity, coordination geometry, and metal–metal distance. In this work, we apply X-ray absorption and emission spectroscopy and quantum chemical calculations to describe electronic structure and bonding in a series of dicobalt complexes. The compounds with silane ligands and pseudo-octahedral coordination geometry exhibit Co–Co σ and multicentered bonding character, which we characterize from both the occupied and vacant perspectives via their contributions to the Co X-ray emission and absorption spectra, respectively. In contrast, the dicobalt complexes with a pseudotetrahedral coordination environment do not exhibit Co–Co bonding due to symmetry constraints on orbital overlap. We extend these insights to the theoretical evaluation of related dicobalt complexes to explain how ligand coordination and symmetry dictate the presence or absence of a Co–Co bond. In conclusion, this work highlights how fundamental insights into electronic structure and bonding through X-ray spectroscopy uncover important factors governing metal–metal interactions and guide the rational design of multimetallic complexes with tunable metal–metal bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Improved chemical and isotopic labeling of biomembranes in Bacillus subtilis by leveraging CRISPRi inhibition of beta-ketoacyl-ACP synthase (fabF)

Assessing the structure of living microbial cell membranes is a challenging analytical goal. The cell membrane is defined by its transverse structure, an approximately 5 nm-thick selectively permeable bilayer that serves many important cellular functions. Compositionally complex, dynamic, and organized in both the transverse and lateral dimensions, understanding the cell membrane structure—and the role that structure plays in cellular function, communication, and environmental sensing is an active scientific effort. Previously, we have devised a novel isotopic labeling approach for membrane lipids to enable direct in vivo structural studies of the cell membrane in the Gram-positive bacterium, Bacillus subtilis , using small-angle neutron scattering. This was accomplished through a genetic inhibition of fatty acid (FA) degradation (Δ fadN ) and a chemical inhibition of FA biosynthesis using cerulenin, an irreversible inhibitor of type II fatty acid synthases. Here, we improve upon the previous system by introducing a dCas9/sgRNA- fabF complex that blocks transcription of the essential fabF gene when under xylose induction. This leads to greater sensitivity to cerulenin in the mutant strain (JEBS102) and more robust cell growth when supplementary FAs are introduced to the culture medium. A subtle change in FA uptake is noted when compared to the prior labeling strategy. This is seen in the gas chromatography/mass spectrometry (GC/MS) data as a higher ratio of n 16:0 to a 15:0, and manifests in an apparent increase in the membrane thickness determined via neutron scattering. This represents an improved method of isotopic labeling for the cell membrane of Bacillus subtilis; enabling improved investigations of cellular uptake and utilization of FAs, cell membrane structure and organization as a phenotypic response to metabolic and environmental changes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Rapid data-driven model reduction of nonlinear dynamical systems including chemical reaction networks using ℓ 1 -regularization

We develop a new data-driven paradigm for efficient model reduction of a broad class of nonlinear dynamical systems. Our model reduction method directly enables the interpretation of key components of the dynamical system, unlike traditional projection-based model reduction methods that focus on reducing computational complexity more than interpretability. Our method is not application specific and is simple to implement on nonlinear dynamical systems arising from a variety of different fields. It requires minimal parameterization using a single parameter to trade-off between model complexity and estimation error. We use a data-driven paradigm to formulate model reduction as an efficient convex optimization problem that scales polynomially in the original size of the complex system, enabling systems with as many as thousands of components to be reduced in a matter of minutes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗