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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High‐Performance and Stable Semi‐Transparent Perovskite Solar Cells through Composition Engineering

Abstract Semi‐transparent perovskite solar cells (ST‐PeSCs) have tremendous potential as solar windows owing to their higher efficiency and visible transmittance. However, studies toward this application are still nascent, particularly in unraveling the interplay between how the perovskite composition impacts the achievable device performance and stability. Here, the role of A‐ and X‐site modification in APbX 3 perovskites is studied to understand their influence on these factors. Through detailed experimental and simulation work, it is found that a perovskite composition consisting of cesium (Cs) and formamidinium (FA) at the A‐site delivers the best device performance over a range of band gaps, which are tuned by changes to the X‐site anion. Using this optimized perovskite composition, power conversion efficiencies of 15.5% and 4.1% are achieved for ST‐PeSCs with average visible transmittance values between 20.7% and 52.4%, respectively. Furthermore, the CsFA‐based ST‐PeSCs show excellent long‐term stability under continuous illumination and heating. The stability of the precursor solutions across each of the studied compositions has also been considered, showing dramatic differences in the structural properties of the perovskites and their device performance for all mixed A‐site compositions possessing the archetypal methyl ammonium species, while also confirming the superior stability of the CsFA precursor solutions.

14 SOLAR ENERGY↗
DOE OSTI2022

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗
DOE OSTI2025

Miscanthus × giganteus increases soil maximum water holding capacity compared to maize

Soil ecosystem services, like the ability to store water, have been depleted after a century of conventional, annual cropping, and perennial crops offer a solution to this and other agricultural environmental issues. We assessed the impact of Miscanthus × giganteus (miscanthus), a perennial biomass crop, on soil water holding capacity and structure compared to continuous maize (Zea mays L.) at two sites in Iowa. After three growing seasons, we measured the following: (1) maximum water holding capacity (MWHC) with and without soil structure, and (2) total porosity and pore size distribution (PSD) via micro-computed tomography (microCT). Miscanthus increased MWHC by 14.7% across both sites relative to maize (p = 0.002), and we attributed this to structural changes due to the lack of a crop effect when measured on structureless soils. No significant changes were detected in soil organic matter, texture, total porosity, or PSD that could explain the increase in MWHC under miscanthus. Our findings suggest that the increases in MWHC are primarily due to structural changes rather than increases in soil organic matter or porosity (at least porosity detectable by microCT). This study highlights miscanthus' potential to enhance soil water storage and underscores the need for further investigation to clarify the mechanisms through which this biomass crop influences soil structural properties.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Nickel(II) Bisporphyrin‐Fused Pentacenes Exhibiting Abnormal High Stability

Abstract A series of largely π‐extended multichromophoric molecules including cross‐conjugated, half cross‐conjugated, conjugation‐interrupted and linearly conjugated systems were synthesized and characterized. These multichromophoric molecular systems revealed interesting structural‐property relationships. Bisporphyrin‐fused pentacenes Pen‐1 b and Pen‐2 a showed rich redox chemistry with 7 and 8 observable redox states, respectively. The linearly‐conjugated bisporphyrin‐fused pentacenes ( Pen‐1 b and Pen‐2 a ) possess much narrower HOMO–LUMO gaps (1.65 and 1.42 eV redox, respectively) and higher HOMO energy levels than those of their pentacene analogues (2.23 and 2.01 eV redox, respectively), similar to those of much less stable hexacenes and heptacenes. An estimated half‐life of >945 h was obtained for bisporphyrin‐fused pentacene Pen‐2 a , which is much longer than that of its pentacene analogue ( BPE‐P , half‐life, 33 h).

Hu, Yi↗
DOE OSTI2021

Development of High Energy Density Diaminocyclopropenium‐Phenothiazine Hybrid Catholytes for Non‐Aqueous Redox Flow Batteries

Abstract This report describes the design of diaminocyclopropenium‐phenothiazine hybrid catholytes for non‐aqueous redox flow batteries. The molecules are synthesized in a rapid and modular fashion by appending a diaminocyclopropenium (DAC) substituent to the nitrogen of the phenothiazine. Combining a versatile C‐N coupling protocol (which provides access to diverse derivatives) with computation and structure‐property analysis enabled the identification of a catholyte that displays stable two‐electron cycling at potentials of 0.64 and 1.00 V vs. Fc/Fc + as well as high solubility in all oxidation states (≥0.45 M in TBAPF 6 /MeCN). This catholyte was deployed in a high energy density two‐electron RFB, exhibiting >90 % capacity retention over 266 hours of flow cell cycling at >0.5 M electron concentration.

Yan, Yichao↗
DOE OSTI2021

A Heteromeric Carboxylic Acid Based Single-Crystalline Crosslinked Organic Framework

The development of large pore single-crystalline covalently linked organic frameworks is critical in revealing the detailed structure-property relationship with substrates. One emergent approach is to photo-crosslink hydrogen-bonded molecular crystals. Introducing complementary hydrogen-bonded carboxylic acid building blocks is promising to construct large pore networks, but these molecules often form interpenetrated networks or non-porous solids. In this report we introduced heteromeric carboxylic acid dimers to construct a non-interpenetrated molecular crystal. Crosslinking this crystal precursor with dithiols afforded a large pore single-crystalline hydrogen-bonded crosslinked organic framework H C OF-101. X-ray diffraction analysis revealed H C OF-101 as an interlayer connected hexagonal network, which possesses flexible linkages and large porous channels to host a hydrazone photoswitch. Multicycle Z/E-isomerization of the hydrazone took place reversibly within H C OF-101, showcasing the potential use of H C OF-101 for optical information storage.

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

Development of High Energy Density Diaminocyclopropenium-Phenothiazine Hybrid Catholytes for Non-Aqueous Redox Flow Batteries

Our work describes the design of diaminocyclopropenium-phenothiazine hybrid catholytes for non-aqueous redox flow batteries. The molecules are synthesized in a rapid and modular fashion by appending a diaminocyclopropenium (DAC) substituent to the nitrogen of the phenothiazine. Combining a versatile C-N coupling protocol (which provides access to diverse derivatives) with computation and structure-property analysis enabled the identification of a catholyte that displays stable two-electron cycling at potentials of 0.64 and 1.00 V vs. Fc/Fc + as well as high solubility in all oxidation states (≥0.45 M in TBAPF 6 /MeCN). This catholyte was deployed in a high energy density two-electron RFB, exhibiting >90 % capacity retention over 266 hours of flow cell cycling at >0.5 M electron concentration.

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

Dissecting Critical Factors for Electrochemical CO 2 Reduction on Atomically Precise Au Nanoclusters

Here, this work investigates the critical factors impacting electrochemical CO 2 reduction reaction (CO 2 RR) using atomically precise Au nanoclusters (NCs) as electrocatalysts. First, the influence of size on CO 2 RR is studied by precisely controlling NC size in the 1–2.5 nm regime. We find that the electrocatalytic CO partial current density increases for smaller NCs, but the CO Faradaic efficiency (FE) is not directly associated with the NC size. This indicates that the surface-to-volume ratio, i.e. the population of active sites, is the dominant factor for determining the catalytic activity, but the selectivity is not directly impacted by size. Second, we compare the CO 2 RR performance of Au 38 isomers (Au 38 Q and Au 38 T) to reveal that structural rearrangement of identical size NCs can lead to significant changes in both CO 2 RR activity and selectivity. Au 38 Q shows higher activity and selectivity towards CO than Au 38 T, and density functional theory (DFT) calculations reveal that the average formation energy of the key *COOH intermediate on the proposed active sites is significantly lower on Au 38 Q than Au 38 T. These results demonstrate how the structural isomerism can impact stabilization of reaction intermediates as well as the overall CO 2 RR performance of identical size Au NCs. Overall, this work provides important structure–property relationships for tailoring the NCs for CO 2 RR.

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

Impacts of A‐Site Composition on the Cation Dissolution‐Mediated Surface Restructuring of Layered Nickelate Oxide Electrocatalysts During Alkaline Oxygen Evolution Reaction

The oxygen evolution reaction (OER) is a key anodic counter‐reaction for electrochemical production of fuels and chemicals. It is hindered by sluggish four‐electron transfer kinetics requiring highly oxidative operating potentials to achieve commercially relevant rates. NiFeO x H y electrocatalysts are among the most promising for OER in alkaline electrolytes. The Ni(OH) 2 /NiOOH redox couple has been reported as the active phase in Ni‐based electrocatalysts; however, its activity is often hindered by deactivation arising from the formation of OER‐inactive insulating species. Limited strategies exist for mitigating this deactivation. This study aims to address this by interrogating the evolution of OER active sites as a function of precatalyst composition and structural properties using a series of layered, crystalline Ni‐based Ruddlesden–Popper (RP) oxides (A 2 NiO 4+δ ). In situ evolution of the active NiO x H y surface is probed through Ni‐site OER turnover frequency analysis, and electrochemical impedance spectroscopy coupled with scanning transmission electron microscopy. We show that the stability of layered nickelate oxide electrocatalysts is governed by the dynamic competition between cation dissolution and Ni‐site reversibility, which can be tuned through the A‐site composition of RP oxides. These findings yield insights toward engineering OER oxide precatalysts that optimize the stability of in situ‐generated OER active phases.

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

Revealing the Influence of Diverse Secondary Metal Cations on Redox-Active Palladium Complexes

Incorporation of redox-inactive metals into redox-active complexes and catalysts attracts attention for engendering new reactivity modes, but this strategy has not been extensively investigated beyond the first-row of the transition metals. In this report the isolation and characterization of the first series of heterobimetallic complexes of palladium with mono-, di-, and tri-valent redox-inactive metal ions are reported. A Reinhoudt-type heteroditopic ligand with a salen-derived [N 2 ,O 2 ] binding site for Pd and a crown-ether-derived [O 6 ] site has been used to prepare isolable adducts of the Lewis acidic redox-inactive metal ions (M n+ ). Comprehensive data from single-crystal X-ray diffraction analysis reveal distinctive trends in the structural properties of the heterobimetallic species, including an uncommon dependence of the Pd … M distance on Lewis acidity. The reorganization energy associated with reduction of the heterobimetallic species is strongly modulated by Lewis acidity, with the slowest heterogeneous electron transfer kinetics associated with the strongest incorporated Lewis acids. This hitherto unexplored reorganization energy penalty for electron transfer contrasts with prior thermodynamic studies, revealing that kinetic parameters should be considered in studies of reactivity involving heterobimetallic species.

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

Accelerating the Structure Exploration of Diverse Bi–Pt Nanoclusters via Physics‐Informed Machine Learning Potential and Particle Swarm Optimization

Bimetallic Bi–Pt nanoclusters exhibit diverse structural motifs, including core-shell, Janus, and mixed alloy configurations, due to the unique bonding characteristics between Bi and Pt atoms. Using density functional theory refinements from ChIMES physically machine-learned potential and CALYPSO particle swarm optimization global searches, 34 Bi20-Pt20 nanoclusters are systematically classified. The results reveal that Bi atoms predominantly occupy surface sites, driven by charge transfer effects. Cohesive energy trends alone prove insufficient for structure differentiation, necessitating a data-driven approach employing principal component analysis and K-means clustering. Furthermore, vibrational, electronic, and infrared spectral analyses provide additional insights into structure-property relationships. The findings offer an original framework for the automated classification and analysis of bimetallic nanoclusters, enhancing the understanding of their stability and functional properties.

bimetallic nanoparticles↗
DOE OSTI2022

Local Structure Analysis and Modelling of Lignin‐Based Carbon Composites through the Hierarchical Decomposition of the Radial Distribution Function

Abstract Carbonized lignin has been proposed as a sustainable and domestic source of activated, amorphous, graphitic, and nanostructured carbon for many industrial applications as the structure can be tuned through processing conditions. However, the inherent variability of lignin and its complex physicochemical structure resulting from feedstock and pulping selection make the Process‐Structure‐Property‐Performance (PSPP) relationships hard to define. In this work, radial distribution functions (RDFs) from synchrotron X‐ray and neutron scattering of lignin‐based carbon composites (LBCCs) are investigated using the Hierarchical Decomposition of the Radial Distribution Function (HDRDF) modelling method to characterize the local atomic environment and develop quantitative PSPP relationships. PSPP relationships for LBCCs defined by this work include crystallite size dependence on lignin feedstock as well as increasing crystalline volume fraction, nanoscale composite density, and crystallite size with increasing reduction temperature.

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

Machine learning for polymeric materials: an introduction

We report that Polymers are incredibly versatile materials and have become ubiquitous. Increasingly, researchers are using data science and polymer informatics to design new materials and understand their structure-property relationships. Polymer informatics is an emerging field. While there are many useful tools and databases available, many are not widely utilized. Herein, we introduce the field of polymer informatics and discuss some of the available databases and tools. We cover how to share polymer data, approaches for preparing a dataset for machine learning and recent applications of machine learning to polymer property prediction and polymer synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Reduced‐Order Modeling of Energetic Materials Using Physics‐Aware Recurrent Convolutional Neural Networks in a Latent Space (LatentPARC)

Physics-aware deep learning (PADL) has gained popularity for use in spatiotemporal dynamics simulations, such as those in computational modeling of energetic materials (EM). We show that the challenge PADL methods face while learning complex field evolution problems can be simplified and accelerated by decoupling it into two tasks: learning complex geometric features in evolving fields and modeling dynamics over these features in a lower-dimensional feature space. We build upon our previous work on physics-aware recurrent convolutional neural networks (PARC). PARC embeds knowledge of underlying physics into its neural network architecture for more robust and accurate prediction of evolving physical fields. PARC was shown to effectively learn complex nonlinear features such as the formation of hotspots and coupled shock fronts in various initiation scenarios of EMs, as a function of microstructures, serving effectively as a microstructure-aware burn model. Here, we further accelerate PARC and reduce its computational cost by projecting the original dynamics onto a lower-dimensional invariant manifold, or “latent space.” The projected latent representation encodes the complex geometry of evolving fields (e.g., temperature and pressure) in a set of data-driven features. The reduced dimension of this latent space allows us to learn the dynamics during the initiation of EM with a lighter and more efficient model. We observe a significant decrease in training and inference time while maintaining results comparable to PARC at inference. This work takes steps towards enabling rapid prediction of EM thermomechanics at larger scales and characterization of EM structure–property–performance linkages at a full application scale.

Mathematics and Computing↗
DOE OSTI2021

Bright NIR‐II Photoluminescence in Rod‐Shaped Icosahedral Gold Nanoclusters

Abstract Fluorophores with high quantum yields, extended maximum emission wavelengths, and long photoluminescence (PL) lifetimes are still lacking for sensing and imaging applications in the second near‐infrared window (NIR‐II). In this work, a series of rod‐shaped icosahedral nanoclusters with bright NIR‐II PL, quantum yields up to ≈ 8%, and a peak emission wavelength of 1520 nm are reported. It is found that the bright NIR‐II emission arises from a previously ignored state with near‐zero oscillator strength in the ground‐state geometry and the central Au atom in the nanoclusters suppresses the non‐radiative transitions and enhances the overall PL efficiency. In addition, a framework is developed to analyze and relate the underlying transitions for the absorptions and the NIR‐II emissions in the Au nanoclusters based on the experimentally defined absorption coefficient. Overall, this work not only shows good performance of the rod‐shaped icosahedral series of Au nanoclusters as NIR‐II fluorophores, but also unravels the fundamental electronic transitions and atomic‐level structure‐property relations for the enhancement of the NIR‐II PL in gold nanoclusters. The framework developed here also provides a simple method to analyze the underlying electronic transitions in metal nanoclusters.

Li, Qi↗
DOE OSTI2021

High Interfacial-Energy and Lithiophilic Janus Interphase Enables Stable Lithium Metal Anodes

The stability of solid electrolyte interphase (SEI) layers is critical for developing lithium (Li) metal batteries. However, the fabrication of stable SEI layers is plagued by un-controlled structures, properties, and functions. In this work a controllable design of an ordered LiF-rich and lithiophilic hybrid Janus interphase (LiF-HJI) is reported using organic fluorination reagent as a functional SEI precursor. The LiF-HJI with a lower crystalline LiF layer and an upper Li organosulfide layer provides high interfacial energy with the Li metal and strong Li-ion affinity, allows homogenous Li-ion distribution, fast and uniform Li-ion transport, and excellent mechanical and passivation properties, enabling stable Li metal anodes under harsh conditions, such as high deposition capacities (6 mA h cm -2 ), current densities (10 mA cm -2 ), and rates (5 C). Stable LiF-HJI@Li greatly improves cycling stability and capacity retention (80.1% after 300 cycles) of Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 cells at a commercial-level areal capacity (≈4.2 mA h cm -2 ). Even under a lean-electrolyte condition of 3 g Ah -1 , 80% capacity retention can be maintained after 100 cycles, demonstrating excellent cycling performance under such harsh conditions.

25 ENERGY STORAGE↗