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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 OSTI2025

Isolation of a new polyoxometalate complex of plutonium

We report the synthesis, plus structural and spectroscopic characterization, of a plutonium(IV) complex with the polyoxometalate W 5 O 18 6− . The complex was isolated as Cs 8 [Pu(W 5 O 18 ) 2 ]·CsCl·6.5H 2 O, with the tetravalent actinide cation sandwiched between two lacunary polyoxotungstate anions. It represents a rare case of a POM compound with plutonium and also the first Peacock–Weakley type complex of plutonium.

Colliard, Ian [Lawrence Livermore National Laborat↗
DOE OSTI2026

Low-cost calculation and analysis of 2D IR spectra of model diiron trinitrosyl complexes in the NO stretch region with vibrational perturbation theory

Two-dimensional infrared spectroscopy offers unique capabilities for probing vibrational coupling in complex metal–ligand systems. In this paper, we combine two-dimensional infrared spectroscopy with vibrational perturbation theory to investigate vibrational coupling in a diiron trinitrosyl complex across three stable redox states. Although these systems are challenging for electronic structure methods, we demonstrate that key features of experimental 2D IR spectra can be accurately reproduced using reduced-dimensional anharmonic calculations with a small harmonic frequency scaling. Analysis reveals that N–O stretching modes maintain high locality across all redox states, with coupling patterns that directly reflect variations in Fe–N bond strength. Using curvilinear coordinate analysis, we demonstrate these differences result from systematic changes in cubic anharmonic force constants rather than mode delocalization. Our results establish N–O stretches as sensitive probes of metal–ligand bonding strength, expanding the toolkit for studying biologically relevant nitrosyl complexes.

Moran, Hayden A. [Texas A&M University, College St↗
DOE OSTI2025

Designing molecular qubits: computational insights into first-row and group 6 transition metal complexes

In the realm of optically addressable qubits, a previously synthesized and characterized Cr( IV ) pseudo-tetrahedral complex, featuring four strongly donating ligands surrounding the chromium center, has demonstrated potential as a qubit candidate. This study proposes analogs of this complex through a metal substitution strategy, extending the investigation to different complexes based on metal centers selected from first-row and Group 6 transition metals. Computational modeling based on multiconfigurational methods CASPT2 and MC-PDFT was utilized to calculate energy gaps between ground and excited electronic spin states, and zero-field splitting parameters. Simulations were applied to each equilibrium geometry and related deformations based on vibrational modes. All results align with previous experimental findings, but also show that qubits based on V and Ti centers could be more electronically stable than the Cr one, suggesting a lower electronic features dependency from their related geometry. In some cases geometrical deformations provide changes in relative energy gaps between triplet and singlet excited state, that could potentially swap, offering a different initialization process, and some inspiration for ligand design based on such deformations. Additionally, this study identifies an unsynthesized Ti( II ) compound as a promising candidate for molecular qubits. This finding highlights the role of computational multireference methods in the rational design of qubit systems.

Sauza-de la Vega, Arturo [Univ. of Chicago, IL (Un↗
DOE OSTI2026

Reduced salen in a monomeric Fe complex

We report the first monomeric formally M I transition metal salen complex without ion pairing. A combination of spectroscopy, crystallography, and computations indicates that reduction of an Fe II salen complex gives substantial reduced ligand character. We also present a computational method for accurately predicting 57 Fe Mössbauer parameters of Fe salen complexes.

Feldman, Dana M. [Yale University, New Haven, CT (↗
DOE OSTI2026

Stabilizing homogeneous CaMn6Sn6via oscillatory crystal growth: structural complexity in a kagome metal

CaMn6Sn6 is a member of the large family of Mn-based kagome metals derived by filling voids of the prototypical CoSn structure. We observed Ca-deficiency and structural complexity, with approximately 10% deficiency of calcium relative to the ideal 166 stoichiometry. These features are common in related Ca-based materials. We find that growth conditions stabilize different phases with varying Curie temperatures. Diffraction and magnetization measurements reveal that conventional growth profiles yield inhomogeneity both within and between crystals in a given batch, whereas an oscillatory temperature profile promotes homogeneous crystals that adopt a superstructure beyond the parent hexagonal structure type. We present the physical properties of crystals grown using the oscillatory approach. The crystals are highly conductive, with a c-axis residual resistivity ratio ρ(300 K)/ρ(2 K) exceeding 100 and a positive, linear magnetoresistance at base temperature. Magnetically, the crystals are quite similar to MgMn6Sn6, with easy-plane ferromagnetic behavior and a Curie temperature of TC ≈ 237 K. These results highlight the critical role of growth conditions in stabilizing homogeneous crystals of complex phases such as Ca0.9Mn6Sn6. The oscillatory growth approach provides an effective route for accessing the intrinsic properties of this complex material and may be broadly useful for the growth of related kagome systems.

May, Andrew [ORNL] (ORCID:0000000307778539)↗
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 OSTI2024

Reaction mechanisms for electrical doping of organic semiconductors using complex dopants

Electrical doping of organic semiconductors (OSCs) can be achieved using simple one-electron reductants and oxidants as n- and p-dopants, respectively, but for such dopants, increased doping strength is accompanied by increased sensitivity to ambient moisture and/or oxygen. “Indirect” or “complex” dopants—defined here as those that generate OSC radical cations or anions via pathways more complex than a single simple electron transfer, i.e., by multistep reactions—represent a means of circumventing this problem. Further, this review highlights the importance of understanding the reaction mechanisms by which such dopants operate for: (i) ensuring a researcher knows the composition of a doped material; (ii) predicting the thermodynamic feasibility of achieving doping with related dopant:OSC combinations; and (iii) predicting whether thermodynamically feasible doping reactions are likely to be rapid or slow, or to require subsequent activation. The mechanistic information available to date for some of the wide variety of complex n- and p-dopants that have been reported is then reviewed, emphasizing that in many cases our knowledge is far from complete.

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

Revisiting the Anisotropic Complex Refractive Indices of Sodium Nitrate for Interpretation of the Reflectance Spectrum of Pressed Pellets

Reflectance spectroscopy is notoriously confounding in that the measured spectral response is highly dependent upon the morphology of the sample. Fortunately, all such perturbations are neatly encoded by the complex refractive index of the sample. Herein, we seek to quantitatively model the measured infrared reflectance spectrum of a specularly flat pressed pellet sample of the birefringent compound, sodium nitrate. Single crystals of sodium nitrate were synthesized via a slow evaporation process and spectroscopically analyzed using polarization-dependent infrared single-angle reflectance spectroscopy. The anisotropic complex refractive index was measured from 7500 to 300 cm-1 (1.33 to 33.33 µm). The deduced anisotropic optical constants were found to be consistent with those previously reported. Once measured and validated, the optical constants were applied to model the pressed pellet reflectance spectrum. It was evident that an average of the anisotropic refractive indices was insufficient to account for the measured pellet reflectance. In order to account for contributions of all possible microcrystalline orientations within the pellet, the Python package PYELLI was used to calculate a basis set of orientation-dependent reflection spectra spanning the distinct ? and ? Euler rotations of the uniaxial crystal. When the population of orientations was allowed to vary freely in a spectral fit analysis, the fit-deduced orientations were tightly clustered along f = 45º, hinting at residual anisotropy in the pressed pellet sample. Conversely, an equally valid spectral fit (with marginally worse fit metric) was obtained when the population was constrained to an isotropic distribution of orientations. Subsequent non-zero cross-polarization reflectance measurements likewise suggested anisotropy in the pellet. However, both grazing incidence wide-angle x-ray scattering and scanning electron microscopy measurements revealed that the microcrystal orientations at the surface of the pressed pellet sample were isotropically distributed (and that the average crystallite size was larger than ?/10). Application of the measured complex refractive indices for modeling the reflectance spectrum of the pressed pellet, and rectification of these seemingly contradictory observations will be discussed.

Wilhelm, Michael J.↗
DOE OSTI2025

An unusual Co–S bond links B 12 chaperones in an interprotein complex

Chaperones in trafficking pathways ensure specificity of transition metal loading and protection against adventitious side reactions. In B 12 , an essential cofactor for humans, a cobalt ion is coordinated to a >1.3 kDa tetrapyrrolic scaffold, posing logistical challenges for its translocation. In this study, we report the 3.4 Å crystal structure of the human MMACHC and MMADHC B 12 chaperones, tethered via a rarely seen covalent cobalt–sulfur bond. B 12 is bound in the base-off state to MMACHC, with Cys-261 on MMADHC serving as the upper axial ligand; the lower-axial position is vacant. The propensity of thiolato-cobalamin derivatives bound to MMACHC to undergo spontaneous decomposition via general acid catalysis or reduction/oxidation chemistry is averted in the interprotein complex with MMADHC. An exposed face in the complex suggests an exit route for B 12 . No known clinical variants localize to the interprotein interface, consistent with the cobalt–sulfur bond being key to forming the high-affinity complex.

Science & Technology - Other Topics↗
DOE OSTI2025

Action at a distance: The remarkable coupling of CO 2 uptake to electron transfer in specialized cyanobacterial NDH-1 complexes

Cyanobacteria achieve highly efficient photosynthesis using a CO 2 -concentrating mechanism relying on specialized Type I (NDH-1) complexes. Among these, NDH-1 3 and NDH-1 4 catalyze redox-coupled hydration of CO 2 to bicarbonate, supporting carbon fixation in carboxysomes. The mechanism of coupling electron transfer to CO 2 -hydration by these variant NDH-1 complexes remains unknown. We engineered a Synechococcus PCC7942 strain that expresses exclusively the high flux/low affinity NDH-14 complex, enabling the observation of the coupling of CO 2 hydration to cyclic electron flow in isolation from the other NDH-1 isoforms normally present in cells. We found that inhibition of the CupB protein by the carbonic anhydrase inhibitor ethoxzolamide (EZ) suppressed CO 2 uptake, slowed photosystem I rereduction, and abolished proton pumping as probed by acridine orange fluorescence. These effects were absent in strains lacking Cup proteins, confirming specificity. The results demonstrate that CO 2 hydration and electron transfer through NDH-14 are tightly coupled via proton translocation across the thylakoid membrane. These findings provide direct evidence for the bidirectional interaction in bioenergetic coupling between the plastoquinone reduction and the CO 2 uptake at the distal Zn-site over a span of ~150 Å and support a proton-removal hypothesis involving the proton transfer pathways from the Zn-site of CO2 hydration to an energetically coupled proton loading site evolutionarily repurposed from the ancestral proton pumping mechanism to enable energetic CO 2 uptake.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Understanding polaronic transport in complex oxides by combining precise synthesis and first-principles many-body theory

In complex oxides, charge carriers often couple strongly with lattice vibrations to form polarons–entangled electron–phonon quasiparticles whose transport properties remain difficult to characterize. Experimental access to intrinsic polaronic transport requires ultraclean samples, while theoretical description demands methods beyond low-order perturbation theory. Here, we show a predictive theory–experiment workflow to study polaron transport in complex oxides. Focusing on a prototypical polaronic oxide, anatase TiO 2 , we combine growth of high-quality oxygen-vacancy-doped films using hybrid molecular beam epitaxy with a first-principles electron–phonon diagrammatic Monte-Carlo (FEP-DMC) framework recently developed for accurate polaron predictions. Our films exhibit record-high electron mobility for anatase TiO 2 , in excellent agreement with FEP-DMC calculations conducted prior to experiment, which predict a room-temperature mobility of 45 ± 15 cm −2 V −1 s −1 and a mobility-temperature scaling of μ ∝ T −1.9 ± 0.077 . Microscopic analysis using scanning transmission electron microscopy and x-ray photoelectron spectroscopy reveals the role of oxygen vacancies in modulating transport at lower temperatures. FEP-DMC further provides quantitative insight into polaron formation energy, phonon cloud distribution, lattice distortion around the polaron, and the polaronic contribution to mobility. Together, these results provide a deeper microscopic understanding of large-polaron transport in a complex oxide and provide the blueprint to characterize other polaronic materials.

anatase TiO2↗
DOE OSTI2025

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗
DOE OSTI2025

Leveraging dendritic complexity for neuromorphic computing

Abstract Beyond-von Neumann computing approaches are necessary to sustain the growth of microelectronics and the increasing appetite for artificial intelligence/machine learning algorithms. Neuromorphic computing is an emerging paradigm that takes inspiration from the brain to provide a path forward to improve the computational efficiency and computational density of next-generation computing architectures. In nature, we observe brains performing complex computations with a much smaller energy footprint than conventional computing approaches. Current neuromorphic systems are focused primarily on scalability, namely, increasing the number of computational units (neurons) and connections between units (synapses). However, for brain-like cognition and efficiency in next-generation computing hardware, we need increased complexity in function, as well as improved connection density for scalability. Here, we present our work that aims to incorporate dendrites for ‘compute-on-wire’ in neuromorphic architectures to increase the computational complexity (e.g. number of programmable parameters, nonlinear dynamics) as well as computational efficiency (energy/compute) of artificial neural networks (ANNs). We do this by showcasing neuromorphic dendrite elements that can be leveraged for various applications. We will present examples of neuroscience-inspired direction-selective circuits and an ANN with active dendrites leveraging shunting inhibition. We also demonstrate the benefits of using dendrites in deep neural networks. To conclude, we discuss how we can utilize emerging hardware devices in these systems and design next-generation neuromorphic architectures with dendrites.

Cardwell, Suma G. (ORCID:0000000226575545)↗
DOE OSTI2025

Optimizing genomic prediction for complex traits via investigating multiple factors in switchgrass

Genomic prediction has accelerated breeding processes and provided mechanistic insights into the genetic bases of complex traits. To further optimize genomic prediction, we assess the impact of genome assemblies, genotyping approaches, variant types, allelic complexities, polyploidy levels, and population structures on the prediction of 20 complex traits in switchgrass (Panicum virgatum L.), a perennial biofuel feedstock. Surprisingly, short read-based genome assembly performs comparably to or even better than long read-based assembly. Due to higher gene coverage, exome capture and multi-allelic variants outperform genotyping-by-sequencing and bi-allelic variants, respectively. Tetraploid models show higher prediction accuracy than octoploid models for most traits, likely due to the greater genetic distances among tetraploids. Depending on the trait in question, different types of variants need to be integrated for optimal predictions. Furthermore, our study provides insights into the factors influencing genomic prediction outcomes, guiding best practices for future studies and for improving agronomic traits in switchgrass and other species through selective breeding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Benefits and Limits of Phasing Alleles for Network Inference of Allopolyploid Complexes

Abstract Accurately reconstructing the reticulate histories of polyploids remains a central challenge for understanding plant evolution. Although phylogenetic networks can provide insights into relationships among polyploid lineages, inferring networks may be hindered by the complexities of homology determination in polyploid taxa. We use simulations to show that phasing alleles from allopolyploid individuals can improve phylogenetic network inference under the multispecies coalescent by obtaining the true network with fewer loci compared with haplotype consensus sequences or sequences with heterozygous bases represented as ambiguity codes. Phased allelic data can also improve divergence time estimates for networks, which is helpful for evaluating allopolyploid speciation hypotheses and proposing mechanisms of speciation. To achieve these outcomes in empirical data, we present a novel pipeline that leverages a recently developed phasing algorithm to reliably phase alleles from polyploids. This pipeline is especially appropriate for target enrichment data, where the depth of coverage is typically high enough to phase entire loci. We provide an empirical example in the North American Dryopteris fern complex that demonstrates insights from phased data as well as the challenges of network inference. We establish that our pipeline (PATÉ: Phased Alleles from Target Enrichment data) is capable of recovering a high proportion of phased loci from both diploids and polyploids. These data may improve network estimates compared with using haplotype consensus assemblies by accurately inferring the direction of gene flow, but statistical nonidentifiability of phylogenetic networks poses a barrier to inferring the evolutionary history of reticulate complexes.

Evolutionary Biology↗
DOE OSTI2025

Krylov complexity in mixed phase space

We investigate the Krylov complexity of thermofield double states in systems with mixed phase space, uncovering a direct correlation with the Brody distribution, which interpolates between Poisson and Wigner statistics. Our analysis spans two-dimensional random matrix models featuring (I) GOE-Poisson and (II) GUE-Poisson transitions and extends to higher-dimensional cases, including a stringy matrix model (GOE-Poisson) and the mass-deformed SYK model (GUE-Poisson). Krylov complexity consistently emerges as a reliable marker of quantum chaos, displaying a characteristic peak in the chaotic regime that gradually diminishes as the Brody parameter approaches zero, signaling a shift toward integrability. These results establish Krylov complexity as a powerful diagnostic of quantum chaos and highlight its interplay with eigenvalue statistics in mixed phase systems.

chaos & nonlinear dynamics↗
DOE OSTI2024

Origin of spin-driven ferroelectricity and effect of external pressure on the complex magnetism of the 6⁢ H perovskite Ba 3 ⁢Ho⁢Ru 2⁢ O 9

The compound Ba 3 HoRu 2 O 9 magnetically orders at 50 K (T N1 ), followed by another complex magnetic ordering at 10.2 K (T N2 ). The second magnetic phase transition was characterized by the coexistence of two competing magnetic ground states associated with two different magnetic wave vectors (K 1 = 0.5 0 0 and K 2 = 0.25 0.25 0). The multiferroicity and magnetoelectric coupling were predicted below T N2 in these 4d-based materials. Here, in this work, we have discussed the origin of spin-driven ferroelectricity, which is not known yet, and the nature of magnetoelectric domains. We have investigated the compound through time-of-flight neutron diffraction, synchrotron x-ray diffraction (XRD), ac susceptibility, frequency-dependent complex dielectric spectroscopy, and dc magnetization under external pressure. We have demonstrated that the noncollinear structure involving two different magnetic ions, Ru (4d) and Ho (4f), breaks the spatial inversion symmetry via inverse Dzyaloshinskii-Moriya (DM) interaction through strong 4d-4f magnetic correlation, which shifts the oxygen atoms and results in nonzero polarization. Such an observation of inverse DM interaction from two different magnetic ions which cause ferroelectricity is rarely observed. The stronger spin-orbit coupling of 4d orbital might play a major role in creating DM interaction of noncollinear spins. We have systematically studied the spin and dipolar dynamics, which exhibit intriguing behavior with shorter coherence lengths of second magnetic phase associated with the k 2 wave vector. The results manifest the development of finite-size magnetoelectric domains instead of true long-range ordering, which justifies the experimentally obtained low value of ferroelectric polarization. The lattice parameters and volume show a sharp anomaly at T N2 obtained by analyzing the temperature-dependence XRD, which is consistent with the ferroelectric transition, predicting a noncentrosymmetric space group, $P\bar{6}2c$, for this compound. Furthermore, we have investigated the effect of external pressure on this complex magnetism. The result reveals an enhancement of ordering temperature by the application of external pressure (~1.6 K/GPa). The external pressure might favor stabilizing the magnetic ground state associated with second magnetic phase. Our study shows an unconventional mechanism of spin-driven ferroelectricity involving inverse DM interaction between Ru (4d) and Ho (4f) magnetic ions due to strong 4d-4f cross coupling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Two transitions in complex eigenvalue statistics: Hermiticity and integrability breaking

Open quantum systems have complex energy eigenvalues which are expected to follow non-Hermitian random matrix statistics, when chaotic, or two-dimensional (2d) Poisson statistics, when integrable. We investigate the spectral properties of a many-body quantum spin chain, i.e., the Hermitian Heisenberg model with imaginary disorder. Its rich complex eigenvalue statistics is found to separately break both Hermiticity and integrability at different scales of the disorder strength. With no disorder, the system is integrable and Hermitian, with spectral statistics corresponding to the 1d Poisson point process. At very small disorder, we find a transition from 1d Poisson statistics to an effective D -dimensional Poisson point process, showing Hermiticity breaking. At intermediate disorder, we find integrability breaking, as inferred from the statistics matching that of non-Hermitian complex symmetric random matrices in class AI † . For large disorder, as the spins align, we recover the expected integrability (now in the non-Hermitian setup), indicated by 2d Poisson statistics. These conclusions are based on fitting the spin-chain data of numerically generated nearest- and next-to-nearest-neighbor spacing distributions to an effective 2d Coulomb gas description at inverse temperature β . We confirm that such an effective description of random matrices also applies in classes AI † and AII † up to next-to-nearest-neighbor spacings. Published by the American Physical Society 2025

Akemann, Gernot (ORCID:0000000217104258)↗