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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Machine learning guided discovery of ternary compounds involving La and immiscible Co and Pb elements

Abstract Ternary compounds with an immiscible pair of elements are relatively unexplored but promising for novel quantum materials discovery. Exploring what third element and its ratio that can be added to make stable ternary compounds out of an immiscible pair of elements remains a great challenge. In this work, we combine a machine learning (ML) method with ab initio calculations to efficiently search for the energetically favorable ternary La-Co-Pb compounds containing immiscible elements Co and Pb. Three previously reported structures are correctly captured by our approach. Moreover, we predict a ground state La 3 CoPb compound and 57 low-energy La-Co-Pb ternary compounds. Attempts to synthesize La 3 CoPb via multiple techniques produce mixed or multi-phases samples with, at best, ambiguous signals of the predicted lowest-energy La 3 CoPb and the second lowest-energy La 18 Co 28 Pb 3 phases. The calculated results of Gibbs free energy are consistent with experiments, and will provide very useful guidance for further experimental synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

High-throughput computation of electric polarization in solids via Berry flux diagonalization

Electric polarization in the absence of an externally applied electric field is a key property of polar materials, but the standard interpolation-based ab initio approach to compute polarization differences within the modern theory of polarization presents challenges for automated high-throughput calculations. Berry flux diagonalization [J. Bonini et al., Phys. Rev. B 102, 045141 (2020)] has been proposed as an efficient and reliable alternative, though it has yet to be widely deployed. Here, we assess Berry flux diagonalization using ab initio calculations of a large set of materials, introducing and validating heuristics that ensure branch alignment with a minimal number of intermediate interpolated structures. Our automated implementation of Berry flux diagonalization succeeds in cases where prior interpolation-based workflows fail due to band-gap closures or branch ambiguities. Benchmarking with ab initio calculations of 176 candidate ferroelectrics, we demonstrate the efficacy of the approach on a broad range of insulating materials and obtain accurate effective polarization values with fewer interpolated structures than prior automated interpolation-based workflows. Our real-space heuristics that can predict gauge stability a priori from ionic displacements enable a general automated framework for reliable polarization calculations and efficient high-throughput screening of chemically and structurally diverse polar insulators. These results establish Berry flux diagonalization as a robust and efficient method to compute the effective polarization of solids and to accelerate the data-driven discovery of functional polar materials.

Poteshman, Abigail N. [University of Chicago, IL (↗
DOE OSTI2025

Polymer connectivity governs electrophotocatalytic activity in the solid state

The reductive functionalization of inert substrates such as chloroarenes is a critical yet challenging transformation relevant to both environmental remediation and organic synthesis. Combining electricity and light is an emerging strategy to access the deeply reducing potentials required for single electron transfer to chloroarenes, yet this approach is limited by poor stability and mechanistic ambiguity. Here, in this work, we demonstrate heterogeneous electrophotocatalysis using redox-active rylene diimide polymers for the reduction of chloroarenes. We find that the electrophotocatalytic activity varies dramatically as a function of the rylene diimide and the redox-inactive polymer backbone. In particular, a flexible, non-conjugated perylenediimide polymer outperforms all other tested electrophotocatalysts. Transient absorption spectroscopy reveals that precomplexation between the doubly reduced perylenediimide and the haloarene substrate is key to productive catalysis. Overall, this work highlights heterogeneous electrophotocatalysis using insoluble redox-active organic materials and provides critical structure–property insights into solid-state electrophotocatalytic activity, informing the development of next-generation materials for sustainable synthesis.

electrocatalysis↗
DOE OSTI2026

Isolated and H 2 -reduced Anderson clusters catalyse low-temperature hydrogenation of CO 2 to methanol

CO 2 hydrogenation, especially to methanol, is crucial to establishing sustainable closed-loop systems for carbon utilization. However, the difficulties of CO 2 activation at low temperatures and the ambiguity of structure–activity correlations are obstacles to reducing the energy consumption of the hydrogenation process. Here we report that molecularly defined Anderson PtMo 6 O 24 clusters, sited within a robust metal–organic framework, are catalytic for low-temperature CO 2 hydrogenation. The performance of the cluster showed no signs of decay in either its activity or methanol selectivity over 3,600 h at 180 °C. It also achieves a per-pass yield exceeding that of state-of-the-art heterogeneous catalysts under similar conditions. Combined in situ spectroscopy and density functional theory calculations demonstrated that CH 3 OH formation is dominated by the reverse water–gas shift and subsequent CO* hydrogenation pathway, while the HCOO* pathway may serve as a supplementary route. The well-defined cluster structure offers an ideal model for elucidating structure–activity correlations and opens exciting avenues for the rational design of high-activity, low-temperature catalysts for CO 2 hydrogenation.

heterogeneous catalysis↗
DOE OSTI2021

cAMP binding to closed pacemaker ion channels is non-cooperative

Electrical activity in the brain and heart depends on rhythmic generation of action potentials by pacemaker ion channels (HCN) whose activity is regulated by cAMP binding. Previous work has uncovered evidence for both positive and negative cooperativity in cAMP binding, but such bulk measurements suffer from limited parameter resolution. Efforts to eliminate this ambiguity using single-molecule techniques have been hampered by the inability to directly monitor binding of individual ligand molecules to membrane receptors at physiological concentrations. Here we overcome these challenges using nanophotonic zero-mode waveguides4 to directly resolve binding dynamics of individual ligands to multimeric HCN1 and HCN2 ion channels. We show that cAMP binds independently to all four subunits when the pore is closed, despite a subsequent conformational isomerization to a flip state at each site. The different dynamics in binding and isomerization are likely to underlie physiologically distinct responses of each isoform to cAMP and provide direct validation of the ligand-induced flip-state model. Furthermore, this approach for observing stepwise binding in multimeric proteins at physiologically relevant concentrations can directly probe binding allostery at single-molecule resolution in other intact membrane proteins and receptors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Modern temperatures in central–north Greenland warmest in past millennium

The Greenland Ice Sheet has a central role in the global climate system owing to its size, radiative effects and freshwater storage, and as a potential tipping point. Weather stations show that the coastal regions are warming, but the imprint of global warming in the central part of the ice sheet is unclear, owing to missing long-term observations. Current ice-core-based temperature reconstructions are ambiguous with respect to isolating global warming signatures from natural variability, because they are too noisy and do not include the most recent decades. By systematically redrilling ice cores, we created a high-quality reconstruction of central and north Greenland temperatures from ad 1000 until 2011. Here we show that the warming in the recent reconstructed decade exceeds the range of the pre-industrial temperature variability in the past millennium with virtual certainty (P < 0.001) and is on average 1.5 ± 0.4 degrees Celsius (1 standard error) warmer than the twentieth century. Our findings suggest that these exceptional temperatures arise from the superposition of natural variability with a long-term warming trend, apparent since ad 1800. The disproportionate warming is accompanied by enhanced Greenland meltwater run-off, implying that anthropogenic influence has also arrived in central and north Greenland, which might further accelerate the overall Greenland mass loss.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The persistence of memory in ionic conduction probed by nonlinear optics

Predicting practical rates of transport in condensed phases enables the rational design of materials, devices and processes. This is especially critical to developing low-carbon energy technologies such as rechargeable batteries. For ionic conduction, the collective mechanisms, variation of conductivity with timescales and confinement, and ambiguity in the phononic origin of translation, call for a direct probe of the fundamental steps of ionic diffusion: ion hops. However, such hops are rare-event large-amplitude translations, and are challenging to excite and detect. Here we use single-cycle terahertz pumps to impulsively trigger ionic hopping in battery solid electrolytes. This is visualized by an induced transient birefringence, enabling direct probing of anisotropy in ionic hopping on the picosecond timescale. The relaxation of the transient signal measures the decay of orientational memory, and the production of entropy in diffusion. We extend experimental results using in silico transient birefringence to identify vibrational attempt frequencies for ion hopping. Using nonlinear optical methods, we probe ion transport at its fastest limit, distinguish correlated conduction mechanisms from a true random walk at the atomic scale, and demonstrate the connection between activated transport and the thermodynamics of information.

25 ENERGY STORAGE↗
DOE OSTI2026

Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions

High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.

Prantikos, Konstantinos [Argonne National Laborato↗
DOE OSTI2026

An AI-driven framework for evaluating local and state authorities’ permitting processes

The demand for new energy infrastructure is increasing across the United States, but heterogenous permitting processes and embedded requirements across different local jurisdictions can cause project delays, increase “soft costs,” and hinder developer expansion. This study analyzes the variability in local permitting requirements across the U.S. and develops a quantitative approach to describe their clarity and effectiveness in enabling infrastructure project development. By using an Energy Language Model (ELM), a large language model (LLM) for energy technologies, we systematically gathered permitting information from nearly 300 state-, county-, and city-level documents, creating a structured dataset of requirements and procedures on an unprecedented scale and speed. Our analysis revealed that local (city and county) permitting requirement documents are underrepresented compared to state-level guidance documents, which can impede timely and cost-effective installation of new electric infrastructure. Our validation process showed that the final database has an accuracy of approximately 95%. We, further, created a new quantitative method to score permitting requirements for clarity and efficiency, with electric vehicle supply equipment as an initial use case. The average local permitting document scored a 1.8 out of 5, which we interpret as meaning that half of the requirements developers face when installing electric infrastructure are ambiguous, increasing both cost and time. We also created a “Generalized Permit Process”, highlighting common procedural steps and identifying specific opportunities for municipalities to improve their documentation. This research establishes a systematic and scalable framework for evaluating the complexities of local infrastructure permitting processes by combining LLM-powered data collection and quantitative scoring. The framework enables policymakers and developers to identify and mitigate procedural bottlenecks, with the expectation that these improvements can accelerate application review and approval, reduce project costs, and expedite connection to utility distribution grids. As a foundational approach for streamlining local project development processes, this study’s methods are intended to be extended to a wide range of energy applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

The underappreciated role of anthropogenic sources in atmospheric soluble iron flux to the Southern Ocean

The atmospheric deposition of soluble (bioaccessible) iron enhances ocean primary productivity and subsequent atmospheric CO 2 sequestration in iron-limited ocean basins, especially the Southern Ocean. While anthropogenic sources have been recently suggested to be important in some northern hemisphere oceans, the role in the Southern Ocean remains ambiguous. By comparing multiple model simulations with the new aircraft observations for anthropogenic iron, we show that anthropogenic soluble iron deposition flux to the Southern Ocean could be underestimated by more than a factor of ten in previous modeling estimates. Our improved estimate for the anthropogenic iron budget enhances its contribution on the soluble iron deposition in the Southern Ocean from about 10% to 60%, implying a dominant role of anthropogenic sources. We predict that anthropogenic soluble iron deposition in the Southern Ocean is reduced substantially (30-90%) by the year 2100, and plays a major role in the future evolution of atmospheric soluble iron inputs to the Southern Ocean.

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

Understanding intercalation chemistry for sustainable aqueous zinc–manganese dioxide batteries

Rechargeable aqueous Zn-MnO 2 technology combines one of the oldest battery chemistries with favourable sustainability characteristics, including safety, cost and environmental compatibility. However, the ambiguous charge storage mechanism presents a challenge to fulfil the great potential of this energy technology. In this work, we leverage on advanced electron microscopy, electrochemical analysis and theoretical calculations to look into the intercalation chemistry within the cathode material, or α-MnO 2 more specifically. We show that Zn 2+ insertion into the cathode is unlikely in the aqueous system; rather, the charge storage process is dominated by proton intercalation to form α-H x MnO 2 . We further reveal anisotropic lattice change as a result of entering protons proceeding from the surface into the bulk of α-MnO 2 , which accounts for the structural failure and capacity decay of the electrode upon cycling. Our work not only advances the fundamental understanding of rechargeable zinc batteries but also suggests the possibility to optimize proton intercalation kinetics for better-performing cell designs. A rechargeable aqueous Zn-MnO 2 battery features a combination of favourable sustainability characteristics from safety to cost. The authors deploy advanced characterizations and theoretical calculations to provide fresh insight into the charge storage mechanism, which not only closes an ongoing debate but suggests ways forward.

25 ENERGY STORAGE↗
DOE OSTI2021

Ab initio thermodynamics reveals the nanocomposite structure of ferrihydrite

Ferrihydrite is a poorly crystalline iron oxyhydroxide nanomineral that serves a critical role as the most bioavailable form of ferric iron for living systems. However, its atomic structure and composition remain unclear due in part to ambiguities in interpretation of X-ray scattering results. Prevailing models so far have not considered the prospect that at the level of individual nanoparticles multiple X-ray indistinguishable phases could coexist. Using ab initio thermodynamics we show that ferrihydrite is likely a nanocomposite of distinct structure types whose distribution depends on particle size, temperature, and hydration. Nanoparticles of two contrasting single-phase ferrihydrite models of Michel and Manceau are here shown to be thermodynamically equivalent across a wide range of temperature and pressure conditions despite differences in their structural water content. Higher temperature and water pressure favor the formation of the former, while lower temperature and water pressure favor the latter. For aqueous suspensions at ambient conditions, their coexistence is maximal for particle sizes up to 12 nm. The predictions inform and help resolve different observations in various experiments.

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

Computational modeling predicts the stability of both Pd + and Pd2 + ion-exchanged into H-CHA

Passive NO x adsorbers (PNA) using Pd/zeolites have emerged as a promising solution for the reduction of cold-start emissions from vehicle exhaust. However, the nature of the active sites and the mechanisms underlying NO x adsorption in Pd/zeolites remain a subject of ongoing investigation. In this study, we employ quantum chemical simulations to investigate the structure of Pd species in cation-exchange sites at isolated Al and Al pairs in the 6-ring and 8-ring of the CHA framework before the introduction of NO x . Our calculations show that the speciation of Pd in these exchange sites strongly depends on the precise Al arrangement within the framework, as well as the operating conditions. Ionically dispersed Pd is found to be the most favorable species over a wide range of oxidizing and reducing conditions. Small oligomers of PdO and metallic Pd do not appear to be competitive at either isolated Al or Al pairs. Notably, our calculations show that ion exchange sites other than next–next–nearest neighbor Al pairs in the 6-ring will be preferentially occupied by Pd + instead of Pd 2+ . The stability of Pd + in the zeolite environment is an interesting contrast with its rareness in molecular Pd compounds. Nonetheless, a detailed analysis of the electronic structure shows that predicted Pd oxidation states are consistent with chemical intuition for all complexes investigated in this study. We also discuss the potential ambiguity in Pd characterization provided by typical experimental techniques such as XANES, EXAFS and UV-Vis, and highlight the need for additional EPR spectroscopy studies to further elucidate the initial Pd speciation in zeolites for PNA applications.

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

Adsorption of ethylenediamine on Cu surfaces: attributes of a successful capping molecule using first-principles calculations

The shape-controlled synthesis of Cu nanocrystals can benefit a wide range of applications, though challenges exist in achieving high and selective yields to a particular shape. Capping agents play a pivotal role in controlling shape, but their exact role remains ambiguous. In this study, the adsorption of ethylenediamine (EDA) on Cu(100) and Cu(111) was investigated with quantum density functional theory (DFT) to reveal the complex roles of EDA in promoting penta-twinned Cu nanowire growth. We find EDA has stronger binding on Cu(100) than on Cu(111), which agrees the general expectation that penta-twinned Cu nanowires express facets with stronger capping-molecule binding. Despite this stronger binding, ab initio thermodynamics reveals the surface energy of EDA-covered Cu(111) is lower than that EDA-covered Cu(100) at all solution-phase EDA chemical potentials, so there is no thermodynamic driving force for penta-twinned nanowires. We also investigated the capability of EDA to protect Cu surfaces from oxidation in water by quantifying energy barriers for a water molecule to diffuse through EDA layers on Cu(100) and Cu(111). The energy barrier on Cu(100) is significantly lower, which supports observations of faster oxidation of Cu(100) in electrochemical experiments. Thus, we elucidate another possible function of a capping agent – to enable selective oxidation of crystal facets. This finding adds to the general understanding of successful attributes of capping agents for shape-selective nanocrystal growth.

36 MATERIALS SCIENCE↗
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 OSTI2022

SAXS-guided unbiased coarse-grained Monte Carlo simulation for identification of self-assembly nanostructures and dimensions

Recent studies have shown that solvated amphiphiles can form nanostructured self-assemblies called dynamic binary complexes (DBCs) in the presence of ions. Since the nanostructures of DBCs are directly related to their viscoelastic properties, it is important to understand how the nanostructures change under different solution conditions. However, it is challenging to obtain a three-dimensional molecular description of these nanostructures by utilizing conventional experimental characterization techniques or thermodynamic models. To this end, we combined the structural data from small angle X-ray scattering (SAXS) experiments and thermodynamic knowledge from coarse-grained Monte Carlo (CGMC) simulations to identify the detailed three-dimensional nanostructure of DBCs. Specifically, unbiased CGMC simulations are performed with SAXS-guided initial conditions, which aids us to sample accurate nanostructures in a computationally efficient fashion. As a result, an elliptical bilayer nanostructure is obtained as the most probable nanostructure of DBCs whose dimensions are validated by scanning electron microscope (SEM) images. Then, utilizing the obtained molecular model of DBCs, here we could also explain the pH tunability of the system. Overall, our results from SAXS-guided unbiased CGMC simulations highlight that using potential energy combined with SAXS data, we can distinguish otherwise degenerate nanostructures resulting from the inherent ambiguity of SAXS patterns.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scrutinizing formally Ni IV centers through the lenses of core spectroscopy, molecular orbital theory, and valence bond theory

Nickel K- and L 2,3 -edge X-ray absorption spectra (XAS) are discussed for 16 complexes and complex ions with nickel centers spanning a range of formal oxidation states from II to IV. K-edge XAS alone is shown to be an ambiguous metric of physical oxidation state for these Ni complexes. Meanwhile, L 2,3 -edge XAS reveals that the physical d-counts of the formally Ni IV compounds measured lie well above the d 6 count implied by the oxidation state formalism. The generality of this phenomenon is explored computationally by scrutinizing 8 additional complexes. The extreme case of NiF 6 2- is considered using high-level molecular orbital approaches as well as advanced valence bond methods. The emergent electronic structure picture reveals that even highly electronegative F-donors are incapable of supporting a physical d 6 Ni IV center. The reactivity of Ni IV complexes is then discussed, highlighting the dominant role of the ligands in this chemistry over that of the metal centers.

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

Solving the P–O/P–OH riddle: direct synthesis and neutron diffraction characterization of dianionic dithiophosphonates

Here, we report the first definitive neutron diffraction study aimed at resolving the P–OH/P$=$O structural ambiguity in metal dithiophosphonates. The small NH 4 counterion forces a rare syn-configuration via an extended hydrogen-bonding network. Neutron analysis definitively confirmed the fully deprotonated P$=$O moiety, thus confirming the formation of a dianionic dithiophosphonate, a versatile synthon in homoleptic and heteroleptic coordination environments.

Pillay, Michael N. [National Dong Hwa Univ. (Taiwa↗