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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Modeling the Photoelectrochemical Evolution of Lead-Based, Mixed-Halide Perovskites Due to Photosegregation

Lead-based, mixed-halide perovskites such as methylammonium lead iodide-bromide [MAPb(I 1-x Br x ) 3 ] undergo anion photosegregation under illumination. This is observed as low band gap photoluminescence from photogenerated iodine-rich domains due to favorable band offsets that induce carrier funneling into them. Unfortunately, theoretical rationalizations of mixed-halide photosegregation are complicated by biases inherent to photoluminescence-based observations. Recent compositionally-weighted X-ray diffraction (XRD) measurements now reveal broad distributions of photosegregated stoichiometries not captured by existing photosegregation models. To better bridge experiment and theory, we perform kinetic Monte Carlo (KMC) simulations of photosegregation within the context of a band gap-based thermodynamic model, which has previously accounted for numerous experimental observations. Our KMC simulations are modified to consider high carrier density Fermi-Dirac statistics that result from carrier funneling and accumulation within photosegregated I-rich domains. Obtained KMC results reproduce broad x terminal distributions seen experimentally and illustrate how they are characterized by a central, heavily I-enriched stoichiometry. I-rich domain “drifting” during photosegregation rationalizes the long photosegregation timescales seen experimentally with drifting simultaneously producing a wake of variable stoichiometry I-rich inclusions that form the lion’s share of stoichiometric heterogeneities seen in compositionally-weighted XRD measurements. These simulations and accompanying rationalizations further reveal a general criterion for realizing favorable free energies to induce demixing. Central to the criterion is the statistical occupation of low gap inclusions in the parent alloy by excitations. Furthermore, the resulting model thus provides a general framework for conceptualizing mixed-halide perovskite light and temperature sensitivities, mediated by photocarriers.

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

Uranium carbide properties for advanced fuel modeling – A review

Uranium carbides are receiving renewed interest as a preferred nuclear fuel composition for advanced reactors due to their numerous favorable properties. Like many other refractory and transition metal carbides these compounds exist in both hypo- and hyper-stoichiometric compositions which results in significant variations in physical, thermal, and mechanical properties. This manuscript surveys both historic and recent literature to compile important properties data mainly as a function of temperature and carbon content to support fuel performance modeling. Expressions and fits for such properties are also suggested when allowed by complete data sets. Finally, the manuscript also attempts to highlight gaps and discrepancies in the reported data to assist the nuclear fuels community identify key areas that may require further attention in terms of future research and development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Structure-based discovery of potent WD repeat domain 5 inhibitors that demonstrate efficacy and safety in preclinical animal models

WD repeat domain 5 (WDR5) is a core scaffolding component of many multiprotein complexes that perform a variety of critical chromatin-centric processes in the nucleus. WDR5 is a component of the mixed lineage leukemia MLL/SET complex and localizes MYC to chromatin at tumor-critical target genes. As a part of these complexes, WDR5 plays a role in sustaining oncogenesis in a variety of human cancers that are often associated with poor prognoses. Thus, WDR5 has been recognized as an attractive therapeutic target for treating both solid and hematological tumors. Previously, small-molecule inhibitors of the WDR5-interaction (WIN) site and WDR5 degraders have demonstrated robust in vitro cellular efficacy in cancer cell lines and established the therapeutic potential of WDR5. However, these agents have not demonstrated significant in vivo efficacy at pharmacologically relevant doses by oral administration in animal disease models. We have discovered WDR5 WIN-site inhibitors that feature bicyclic heteroaryl P 7 units through structure-based design and address the limitations of our previous series of small-molecule inhibitors. Importantly, our lead compounds exhibit enhanced on-target potency, excellent oral pharmacokinetic (PK) profiles, and potent dose-dependent in vivo efficacy in a mouse MV4:11 subcutaneous xenograft model by oral dosing. Furthermore, these in vivo probes show excellent tolerability under a repeated high-dose regimen in rodents to demonstrate the safety of the WDR5 WIN-site inhibition mechanism. Collectively, our results provide strong support for WDR5 WIN-site inhibitors to be utilized as potential anticancer therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Tri-Level Linear Programming Model for Automatic Load Shedding Using Spectral Clustering

Traditional load shedding schemes can be inadequate in grids with high renewable penetration, leading to unstable events and unnecessary grid islanding. Although for both manual and automatic operating modes load shedding areas have been predefined by grid operators, they have remained fixed, and may be sub-optimal due to dynamic operating conditions. In this work, a distributed tri-level linear programming model for automatic load shedding to avoid system islanding is presented. Preventing islanding is preferred because it reduces the need for additional load shedding besides the disconnection of transmission lines between islands. This is crucial as maintaining the local generation-demand balance is necessary to preserve frequency stability. Furthermore, uneven distribution of generation resources among islands can lead to increased load shedding, causing economic and reliability challenges. This issue is further compounded in modern power systems heavily dependent on non-dispatchable resources like wind and solar. The upper-level model uses complex power flow measurements to determine the system areas to shed load depending on actual operating conditions using a spectral clustering approach. The mid-level model estimates the area system state, while the lower-level model determines the locations and load values to be shed. The solution is practical and promising for real-world applications.

Baquedano-Aguilar, Mario D.↗
DOE OSTI2021

Cross-Feeding of a Toxic Metabolite in a Synthetic Lignocellulose-Degrading Microbial Community

The recalcitrance of complex organic polymers such as lignocellulose is one of the major obstacles to sustainable energy production from plant biomass, and the generation of toxic intermediates can negatively impact the efficiency of microbial lignocellulose degradation. Here, we describe the development of a model microbial consortium for studying lignocellulose degradation, with the specific goal of mitigating the production of the toxin formaldehyde during the breakdown of methoxylated aromatic compounds. Included are Pseudomonas putida, a lignin degrader; Cellulomonas fimi, a cellulose degrader; and sometimes Yarrowia lipolytica, an oleaginous yeast. Unique to our system is the inclusion of Methylorubrum extorquens, a methylotroph capable of using formaldehyde for growth. We developed a defined minimal “Model Lignocellulose” growth medium for reproducible coculture experiments. We demonstrated that the formaldehyde produced by P. putida growing on vanillic acid can exceed the minimum inhibitory concentration for C. fimi, and, furthermore, that the presence of M. extorquens lowers those concentrations. We also uncovered unexpected ecological dynamics, including resource competition, and interspecies differences in growth requirements and toxin sensitivities. Finally, we introduced the possibility for a mutualistic interaction between C. fimi and M. extorquens through metabolite exchange. This study lays the foundation to enable future work incorporating metabolomic analysis and modeling, genetic engineering, and laboratory evolution, on a model system that is appropriate both for fundamental eco-evolutionary studies and for the optimization of efficiency and yield in microbially-mediated biomass transformation.

Methylorubrum extorquens↗
DOE OSTI2023

Comparison of ozone formation attribution techniques in the northeastern United States

The Integrated Source Apportionment Method (ISAM) has been revised in the Community Multiscale Air Quality (CMAQ) model. This work updates ISAM to maximize its flexibility, particularly for ozone (O 3 ) modeling, by providing multiple attribution options, including products inheriting attribution fully from nitrogen oxide reactants, fully from volatile organic compound (VOC) reactants, equally from all reactants, or dynamically from NO x or VOC reactants based on the indicator gross production ratio of hydrogen peroxide (H 2 O 2 ) to nitric acid (HNO 3 ). The updated ISAM has been incorporated into the most recent publicly accessible versions of CMAQ (v5.3.2 and beyond). This study's primary objective is to document these ISAM updates and demonstrate their impacts on source apportionment results for O 3 and its precursors. Additionally, the ISAM results are compared with the Ozone Source Apportionment Technology (OSAT) in the Comprehensive Air-quality Model with Extensions (CAMx) and the brute-force method (BF). All comparisons are performed for a 4 km horizontal grid resolution application over the northeastern US for a selected 2 d summer case study (9 and 10 August 2018). General similarities among ISAM, OSAT, and BF results add credibility to the new ISAM algorithms. However, some discrepancies in magnitude or relative proportions among tracked sources illustrate the distinct features of each approach, while others may be related to differences in model formulation of chemical and physical processes. Despite these differences, OSAT and ISAM still provide useful apportionment data by identifying the geographical and temporal contributions of O 3 and its precursors. Both OSAT and ISAM attribute the majority of O 3 and NO x contributions to boundary, mobile, and biogenic sources, whereas the top three contributors to VOCs are found to be biogenic, boundary, and area sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Plastic shrinkage of mortars cured with a paraffin-based compound – Bimodal neutron/X-ray tomography study

Early-age drying (immediately after casting) of mortars and the corresponding plastic shrinkage were studied using bimodal neutron/X-ray computed tomography. This novel, correlative 3D imaging mode enabled studying simultaneously and without any source of spurious perturbation the water migration and loss processes together with the corresponding deformations due to plastic shrinkage. Bimodal imaging opens up new possibilities for studying dynamic processes of coupled water transport and deformations in porous solids. The measurements were carried out on model systems (cylindrical mortar specimens with height of 19 mm). The study focused on the effect of a paraffin-based curing compound. Our results confirm that when the curing compound was applied directly onto the drying surface in a sufficient amount, both the evaporation rate and the rate of vertical displacement (settlement) were substantially reduced. The results shed a new light on the mechanisms of plastic shrinkage and the action of curing compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structural Distortions and Short‐Range Magnetism in a Honeycomb Iridate Cu 3 ZnIr 2 O 6

Layered honeycomb iridates receive significant attention in the materials chemistry and physics fields due to the relevance of their crystal structures to the Kitaev model of a quantum spin liquid (QSL). In quest of liquid‐like magnetic ground state signatures, first‐generation alkali metal iridates A 2 IrO 3 ≡ A 3 [AIr 2 ]O 6 (A = Li, Na) and second‐generation iridates T 3 [AIr 2 ]O 6 ( T = Cu, Ag, H) are developed. T 3 [AIr 2 ]O 6 is synthesized from A 3 [AIr 2 ]O 6 via metathesis reactions replacing alkali ions located between honeycomb layers. Herein, the next level of chemical and structural complexity is introduced by synthesizing the honeycomb iridate, Cu 3 ZnIr 2 O 6 , in which alkali ions between and within the honeycomb layers are both selectively exchanged with two different transition metals. Analysis of powder X‐Ray diffraction data reveals corrugation of the honeycomb layers in Cu 3 ZnIr 2 O 6 that hinders complete magnetic frustration and results in a spin glass behavior observed from magnetization and specific heat data. Thus, Cu 3 ZnIr 2 O 6 represents yet another model, which broadens understanding of intricate relationships between intralayer distortions and magnetism of prospective Kitaev QSL compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quinonoid versus Aromatic π-Conjugated Oligomers and Polymers and Their Diradical Characters

Quinonoid elements in π-conjugated oligomers and polymers have promising characteristics by providing unique structures and electronic properties, including varying degrees of ground state open shell diradical character and small band gaps. So far, quinonoid ground state polymers were rarely identified, and one of the goals of this work was to expand the portfolio of such systems in which over 17 different repeat units were considered, about half preferred a quinonoid and half preferred aromatic structures plus several with the alternating A-Q composition were also included. The dependency of the diradical character as a function of size and composition opens a rich space to discover trends affecting the aromaticity and diradical character. Herein, we show that the diradical character is a useful parameter to classify a wide variety of polymers based on their ground states in a systematic study of a large number of homo- and heterosystems. Homo-polymers with quinonoid ground states show a high diradical character, while those with the aromatic ground state behave as closed-shell systems with no or a very small diradical character. The diradical character of quinonoid systems depends strongly on the size, which increases with the size of the oligomer. Here, we found a correlation between the diradical character and the interring C–C distance as well as the singlet–triplet energy gaps. In alternating copolymers mixing quinonoid and aromatic subunits, we found open-shell hetero-polymers with moderate to high diradical characters.

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

Structural and Electronic Effect Driven Distortions in Visible Light Absorbing Polar Materials A Ta 2 V 2 O 11 ( A = Sr, Pb)

Complex vanadates of tantalum(V), such as ATa 2 V 2 O 11 (A = Sr, Pb), are rare and underrated materials, which have potential application domains that could be substantially expanded, mitigating the existing controversy on their atomic and electronic organization. Herein, we present a thorough structural examination combining synchrotron powder X-ray diffraction-aided distortion mode analysis with computational methods to study hettotypes of SrTa 2 V 2 O 11 (STVO) and PbTa 2 V 2 O 11 (PTVO). Being distinct from the perovskite family due to the presence of [VO 4 ] groups, both compounds are polar dielectric materials with certain similarities to SBT and PBT Aurivillius phases. Applying the model of anions of metallic matrices to the analysis of electron localization functions calculated on top of as-established equilibrium structures helps retrace the effects in the Sr and Pb surroundings on the respective crystal packings of STVO and PTVO.

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

Data-driven design of novel halide perovskite alloys

The great tunability of the properties of halide perovskites presents new opportunities for optoelectronic applications as well as significant challenges associated with exploring combinatorial chemical spaces. Here, in this work, we develop a framework powered by high-throughput computations and machine learning for the design and prediction of mixed cation halide perovskite alloys. In a chemical space of ABX 3 perovskites with a selected set of options for A, B, and X species, pseudo-cubic structures with B-site mixing are simulated using density functional theory (DFT) and several properties are computed, including stability, lattice constant, band gap, vacancy formation energy, refractive index, and optical absorption spectrum, using both semi-local and hybrid functionals. Neural networks (NN) are used to train predictive models for every property using tabulated elemental properties of A, B, and X site species as descriptors. Starting from a DFT dataset of 229 points, we use the trained NN models to predict the structural, energetic, electronic, and optical properties of an extensive dataset of 17955 compounds, and perform high-throughput screening in terms of stability, band gap, and defect tolerance, to obtain 392 promising compounds that are ranked as potential absorbers according to their photovoltaic figure of merit. Compositional trends in the screened set of attractive mixed cation halide perovskites are revealed and additional computations are performed on selected compounds. The data-driven design framework developed here is promising for designing novel mixed compositions and can be extended to a wider perovskite chemical space in terms of A, B, and X species, different kinds of mixing at the A, B, or X sites, non-cubic phases, and other properties of interest.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High concentration of ultrafine particles in the Amazon free troposphere produced by organic new particle formation

The large concentrations of ultrafine particles consistently observed at high altitudes over the tropics represent one of the world’s largest aerosol reservoirs, which may be providing a globally important source of cloud condensation nuclei. However, the sources and chemical processes contributing to the formation of these particles remain unclear. Here we investigate new particle formation (NPF) mechanisms in the Amazon free troposphere by integrating insights from laboratory measurements, chemical transport modeling, and field measurements. To account for organic NPF, we develop a comprehensive model representation of the temperature-dependent formation chemistry and thermodynamics of extremely low volatility organic compounds as well as their roles in NPF processes. We find that pure-organic NPF driven by natural biogenic emissions dominates in the uppermost troposphere above 13 km and accounts for 65 to 83% of the column total NPF rate under relatively pristine conditions, while ternary NPF involving organics and sulfuric acid dominates between 8 and 13 km. The large organic NPF rates at high altitudes mainly result from decreased volatility of organics and increased NPF efficiency at low temperatures, somewhat counterbalanced by a reduced chemical formation rate of extremely low volatility organic compounds. These findings imply a key role of naturally occurring organic NPF in high-altitude preindustrial environments and will help better quantify anthropogenic aerosol forcing from preindustrial times to the present day.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Magnetism and metallicity in moiré transition metal dichalcogenides

The ability to control the properties of twisted bilayer transition metal dichalcogenides in situ makes them an ideal platform for investigating the interplay of strong correlations and geometric frustration. Of particular interest are the low energy scales, which make it possible to experimentally access both temperature and magnetic fields that are of the order of the bandwidth or the correlation scale. In this manuscript, we analyze the moiré Hubbard model, believed to describe the low energy physics of an important subclass of the twisted bilayer compounds. We establish its magnetic and the metal–insulator phase diagram for the full range of magnetic fields up to the fully spin-polarized state. We find a rich phase diagram including fully and partially polarized insulating and metallic phases of which we determine the interplay of magnetic order, Zeeman-field, and metallicity, and make connection to recent experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ising spin ladders of orthopyroxene CoGeO 3

Here, we present thermodynamic and spectroscopic measurements for an orthopyroxene CoGeO 3 with magnetic Co 2+ ions that form quasi-one-dimensional ladders. We show that noncollinear magnetic order below 𝑇 𝑁 = 32 K can be stabilized by a strong local easy-axis anisotropy of 𝑗 eff = 1/2 moments, which is induced by ligand octahedra distortions. Extraction of a magnetic Hamiltonian from inelastic neutron scattering measurements supports this interpretation and allows us to establish an effective magnetic model. The resulting exchange Hamiltonian justifies CoGeO 3 as a realization of an Ising spin ladder compound.

Maksimov, Pavel A. [Joint Inst. for Nuclear Resear↗
DOE OSTI2021

Quantum Enhanced Cavity QED Interferometer with Partially Delocalized Atoms in Lattices

Herein, we propose a quantum enhanced interferometric protocol for gravimetry and force sensing using cold atoms in an optical lattice supported by a standing-wave cavity. By loading the atoms in partially delocalized Wannier-Stark states, it is possible to cancel the undesirable inhomogeneities arising from the mismatch between the lattice and cavity fields and to generate spin squeezed states via a uniform one-axis twisting model. The quantum enhanced sensitivity of the states is combined with the subsequent application of a compound pulse sequence that allows us to separate atoms by several lattice sites. This, together with the capability to load small atomic clouds in the lattice at micrometric distances from a surface, make our setup ideal for sensing short-range forces. We show that for arrays of 10 4 atoms, our protocol can reduce the required averaging time by a factor of 10 compared to unentangled lattice-based interferometers after accounting for primary sources of decoherence.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Discovery of BBO-11818, a Potent and Selective Noncovalent Inhibitor of (ON) and (OFF) KRAS with Activity against Multiple Oncogenic Mutants

Although KRAS G12C -specific inhibitors have been introduced, no approved targeted therapies exist for other clinically significant KRAS mutants, including KRAS G12D and KRAS G12V . We discovered BBO-11818, a potent, selective, orally bioavailable noncovalent pan-KRAS inhibitor capable of targeting multiple KRAS mutants in both the inactive GDP-bound (OFF) and active GTP-bound (ON) states. BBO-11818 binds in the Switch-II/Helix 3 pocket, inducing conformational changes incompatible with effector binding, and demonstrates high-affinity binding to mutant KRAS with strong selectivity over NRAS and HRAS. BBO-11818 potently inhibited MAPK signaling and cellular viability specifically in KRAS-driven lines and produced tumor regressions in KRAS-mutant xenograft models. Combination studies with anti–PD-1, anti-EGFR antibodies, and a RAS:PI3Kα breaker compound showed enhanced efficacy. BBO-11818 has entered phase I clinical trials for patients with various KRAS mutations in colorectal, pancreatic, and lung cancers (NCT06917079).

Stahlhut, Carlos [BridgeBio Oncology Therapeutics,↗
DOE OSTI2026

Expanding the Domain of Applicability of Machine Learning Models with Limited Data for Drug Property Prediction

Accurate machine learning models for predicting small molecule interactions with biological targets are essential for therapeutic discovery, biothreat response, and computational drug design, but their performance is often limited for understudied targets with sparse experimental data. To address this challenge, we developed and evaluated methods to improve molecular property prediction under low-data conditions, using the NimA-related kinase (NEK) family as a proof-of-concept. This work focused on two complementary goals within the ATOM Modeling PipeLine (AMPL) and the Generative Molecular Design (GMD) loop: expanding model applicability through transfer learning, representation learning, feature scaling, sampling strategies, and active-learning-inspired compound selection; and enabling efficient virtual screening to prioritize compounds that balance predicted activity, design objectives, and synthetic accessibility.

organic↗
DOE OSTI2024

Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures

Decades of drug development research have explored a vast chemical space for highly active compounds. The exponential growth of virtual libraries enables easy access to billions of synthesizable molecules. Computational modeling, particularly molecular docking, utilizes physics-based calculations to prioritize molecules for synthesis and testing. Nevertheless, the molecular docking process often yields docking poses with favorable scores that prove to be inaccurate with experimental testing. To address these issues, several approaches using machine learning (ML) have been proposed to filter incorrect poses based on the crystal structures. However, most of the methods are limited by the availability of structure data. Here, we propose a new pose classification approach, PECAN2 (Pose Classification with 3D Atomic Network 2), without the need for crystal structures, based on a 3D atomic neural network with Point Cloud Network (PCN). The new approach uses the correlation between docking scores and experimental data to assign labels, instead of relying on the crystal structures. We validate the proposed classifier on multiple datasets including human mu, delta, and kappa opioid receptors and SARS-CoV-2 Mpro. Our results demonstrate that leveraging the correlation between docking scores and experimental data alone enhances molecular docking performance by filtering out false positives and false negatives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗