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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

Ligand Control of Structural Diversity in Luminescent Hybrid Copper(I) Iodides

Copper(I) iodide hybrids are of interest for next-generation lighting technologies because of their efficient luminescence in the absence of rare-earth elements. Here, we report 10 structurally diverse hybrid copper(I) iodides that emit in the green–red region with quantum yields reaching 67%. The compounds display a diversity of structures including ones with one-dimensional (1D) Cu–1 chains, Cu 2 I 2 rhomboid dimers, and structures with two different arrangements of Cu 4 I 4 tetramers. The compounds with Cu 2 I 2 rhomboid dimers or Cu 4 I 4 cubane tetramers have higher photoluminescence quantum yields than those with Cu–I 1D chains and octahedral Cu 4 I 4 tetramers, owing to the optimal degree of condensation of the inorganic motifs, which suppresses nonradiative processes. Electronic structure calculations on these compounds point out the critical influence of the inorganic motif and organic ligand on the nature of the band gaps and thus the excitation characteristics. Temperature-dependent photoluminescence spectra are presented to better understand the nature of luminescence in compounds with different inorganic motifs. Here. the emerging understanding of composition–structure–property correlations in this family provides inspiration for the rational design of hybrid phosphors for general lighting applications.

36 MATERIALS SCIENCE↗

Phonons in Copper Diphosphide (CuP 2 ): Raman Spectroscopy and Lattice Dynamics Calculations

Copper diphosphide (CuP 2 ) is an emerging binary semiconductor with promising properties for energy conversion and storage applications. While functionality and possible applications of CuP 2 have been studied, there is a curious gap in the investigation of its vibrational properties. In this work, we provide a reference Raman spectrum of CuP 2 , with a complete analysis of all Raman active modes from both experimental and theoretical perspectives. Raman measurements have been performed on polycrystalline CuP 2 thin films with close to stoichiometric composition. Detailed deconvolution of the Raman spectrum with Lorentzian curves has allowed identification of all theoretically predicted Raman active modes (9A g and 9B g ), including their positions and symmetry assignment. Furthermore, calculations of the phonon density of states (PDOS), as well as the phonon dispersions, provide a microscopic understanding of the experimentally observed phonon lines, in addition to the assignment to the specific lattice eigenmodes. We further provide the theoretically predicted positions of the infrared (IR) active modes, along with the simulated IR spectrum from density functional theory (DFT). Overall good agreement is found between the experimental and DFT-calculated Raman spectra of CuP 2 , providing a reference platform for future investigations on this material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dependence of Linker Length and Composition on Ionic Conductivity and Lithium Deposition in Single-Ion Conducting Network Polymers

In this report, single-ion conducting electrolytes stand as promising alternatives to state-of-the-Art electrolytes in lithium batteries, although a single-ion conducting material with high Li + conductivity, stability in contact with lithium, and suitable mechanical properties has been slow to emerge. Here, we describe the synthesis of a series of single-ion conducting network polymers from the reaction of tetrakis(4-(chloromethyl)-2,3,5,6-Tetrafluorophenyl)borate with oligoethylene glycoxide linkers Li 2 O[(CH 2 CH 2 )O] n (n = 1, 2, 3, 9, and 22). Polymers with the longest linkers (n = 9 and 22; ANP-9 and ANP-10, respectively) form materials with conductivities of ~ 10 -6 S cm -1 at 100 °C. With the addition of 65 wt % propylene carbonate (PC), all the network polymers in the series exhibit high conductivities at ambient temperatures, with the n = 1 material (ANP-6) achieving a bulk ionic conductivity of 2.5 x 10 -4 S cm -1 at 25 °C. More conductive single-ion conducting gels could be prepared by using the less coordinating pentanediol dilithium salt as a linker (ANP-11; σ = 3.5 x 10 -4 S cm -1 at 25 °C), although this material exhibited a surprisingly high interfacial resistance in contact with a lithium electrode. In contrast, the gel formed with ANP-6 is notably stable in contact with metallic lithium electrodes, displays a lithium-ion transference number of unity, and boasts a wide electrochemical stability window of greater than 4.5 V. Temperature-dependent ac impedance analysis reveals that the ionic conductivity of this material-and likely the other gels in the series-matches closely to a Vogel-Tamman-Fulcher temperature model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the Development of Order and Interfaces during the Growth of Ultrathin La 2 CuO 4 Films by Molecular Beam Epitaxy

While the atomic structure of interfaces in complex oxide heterostructures created by epitaxial growth has been investigated extensively, few studies have been conducted on how interfaces form and restructure at the initial stage of film growth. The dynamic aspects of the growth behavior can strongly influence the final interfacial atomic structure, which may lead to the emergence of interface-specific properties, such as the rise of interfacial superconductivity between certain Ruddlesden-Popper oxide materials. In this report, the structural development of La2CuO 4 thin films grown by molecular beam epitaxy on a LaSrAlO 4 substrate is investigated by X-ray diffraction measurements with rapid scans over a volume of reciprocal space. This method provides far more detailed information on interface formation than traditional fixed-point measurements. The results show that the atomic structure of the interface becomes fully established after just a single unit cell of growth. Interestingly, restructuring continues to occur within the topmost half to one unit cell of the film during the deposition process. However, diffraction intensity oscillations from both reflection high-energy electron and X-ray measurements stabilize only after the growth of two unit cells, indicating that the growth front morphology continues to evolve until the start of the third unit cell. This multimodal investigation provides insights into the atomic processes taking place during layered oxide interface formation, including the dynamical rearrangement of LaO and CuO 2 layers. Such information is not only relevant to the engineering and optimization of functional layer structures but can also be critical for ultrathin films.

36 MATERIALS SCIENCE↗

Writing the Programs of Programmable Catalysis

It has long been known that non-steady state and periodic catalytic reactor operation in terms of temperature, pressure, and composition can lead to higher overall productivity and/or product selectivity than the best steady operation. Recently, the emergence of catalysts whose intrinsic properties can be made to oscillate with time, introduces advanced forcing capabilities that can be “programmed” into the catalysts to broaden the scope and applicability of periodic operation to surface chemistry. In this work, an algorithmic approach is implemented to significantly accelerate the discovery and optimization of periodic steady states of catalytic reactors. Decomposition of complex dynamics into fundamental mechanistic fast–slow steps is seen to improve conceptual understanding of the relationship between binding energy oscillation protocols and overall catalytic rates. Finding structured forcing protocols, optimally tailored to the multiple time scales of a given individual mechanism, requires an efficient search of high-dimensional parameter spaces. Here, this is enabled here through active learning (Bayesian optimization, enhanced by our proposed Bayesian continuation). Implementation of these methods is shown to accelerate the evaluation of catalyst programs by up to several orders of magnitude. Faster screening of programmable catalysts to discover periodic steady states enables the optimization of catalytic operating protocols and thus opens the possibility for catalyst engineering based on optimal forcing programs to control rate and product selectivity, even for complex multistep catalytic mechanisms.

catalysis↗

Advancing energy storage through solubility prediction: leveraging the potential of deep learning

Solubility prediction plays a crucial role in energy storage applications, such as redox flow batteries, because it directly affects the efficiency and reliability. Researchers have developed various methods that utilize quantum calculations and descriptors to predict the aqueous solubilities of organic molecules. Notably, machine learning models based on descriptors have shown promise for solubility prediction. As deep learning tools, graph neural networks (GNNs) have emerged to capture complex structure–property relationships for material property prediction. Specifically, MolGAT, a type of GNN model, was designed to incorporate n-dimensional edge attributes, enabling the modeling of intricacies in molecular graphs and enhancing the prediction capabilities. In a previous study, MolGAT successfully screened 23 467 promising redox-active molecules from a database of over 500 000 compounds, based on redox potential predictions. This study focused on applying the MolGAT model to predict the aqueous solubility (log S) of a broad range of organic compounds, including those previously screened for redox activity. The model was trained on a diverse sample of 8494 organic molecules from AqSolDB and benchmarked against literature data, demonstrating superior accuracy compared with other state of the art graph-based and descriptor-based models. Subsequently, the trained MolGAT model was employed to screen redox-active organic compounds identified in the first phase of high-throughput virtual screening, targeting favorable solubility in energy storage applications. The second round of screening, which considered solubility, yielded 12 332 promising redox-active and soluble organic molecules suitable for use in aqueous redox flow batteries. Thus, the two-phase high-throughput virtual screening approach utilizing MolGAT, specifically trained for redox potential and solubility, is an effective strategy for selecting suitable intrinsically soluble redox-active molecules from extensive databases, potentially advancing energy storage through reliable material development. This indicates that the model is reliable for predicting the solubility of various molecules and provides valuable insights for energy storage, pharmaceutical, environmental, and chemical applications.

25 ENERGY STORAGE↗

Investigating Quantum Materials with Half-Polarized Diffraction and magnetic PDF analysis at the HB-2A Neutron Powder Diffractometer

Local magnetic ordering and anisotropy is often central to the emergent behavior and subsequent functional properties in quantum materials and beyond. Neutron powder diffraction provides a straightforward yet extremely powerful technique for quantitative measurements of microscopic magnetic properties. The HB-2A powder diffractometer located at the High Flux Isotope Reactor in ORNL is traditionally utilized for long-range magnetic structure determination. Recently these capabilities have been extended to include methods aimed at accessing local magnetism: Half- polarized neutron powder diffraction (pNPD) and magnetic pair distribution function (mPDF) analysis. These two distinct techniques are possible on HB-2A due to the versatility of the instrument’s reciprocal space coverage, resolution and novel ultra-low temperature multi-sample changers that operate down to dilution refrigerator temperatures. This provides unique capabilities not found on any powder diffraction instrument and is particularly well suited to investigations of magnetic quantum materials. The development and implementation of these techniques will be discussed with a series of science case examples ranging from geometric frustrated magnets to magnetic metal-organic frameworks. Data reduction and analysis tools will be presented that enable the extraction of the local site susceptibility tensor and local spin-spin correlations in real space. Finally, potential combinations of these techniques in the form of half-polarized magnetic pair distribution function (pmPDF) analysis will be considered. Looking forward, HB-2A is undergoing a detector upgrade that will be in the user program by 2026. This will offer an order of magnitude increase in count rates to further aid the development of these often low signal measurements and provide new scientific capabilities.

Neutron Scattering↗

In situ thermal conductivity measurement revealing kinetics of thermochemical reactions

Utilizing thermochemical reactions for thermal energy storage and solar fuel production has been an emerging research topic. Thermal transport properties of the materials are an important parameter that can determine the kinetics and efficiency of thermochemical reactions. With the increasing number of new thermochemical materials (TCMs); however, there is a lack of reliable techniques to monitor the thermal transport property of the materials and their changes as a function of reactions in real time. In this work, we report the in situ monitoring of thermochemical reactions using modulated photothermal radiometry (MPR). The thermal conductivities of two TCMs, namely, calcium hydroxide (Ca(OH) 2 ) and Ba 0.15 Sr 0.85 FeO 3–δ (BSF1585), were measured as a function of temperature and time using the MPR technique. The measured thermal conductivities were correlated to the reaction. The work has two significant contributions to the research communities. First, it provides a non-invasive diagnostic tool for monitoring the thermal transport properties of TCMs that can potentially be a high-throughput measurement technique conducive to optimizing TCMs, reactors, and related thermal systems. Second, for TCMs that show observable changes in thermal transport properties, a correlation between the measured thermal conductivity and the conversion fraction of the reaction can be established for monitoring the reaction kinetics based on thermal characterization.

14 SOLAR ENERGY↗

Altermagnetic polar metallic phase in ultrathin epitaxially strained RuO 2 films

Altermagnetism refers to a wide class of magnetic orders featuring magnetic sublattices with opposite spins related by rotational symmetries, resulting in nontrivial spin splitting and magnetic multipoles. However, the direct observation of the altermagnetic transition remains elusive. Here, by combining theoretical analysis, electrical transport, X-ray, and optical spectroscopies, we establish a phase diagram in hybrid molecular beam epitaxy-grown RuO 2 /TiO 2 (110) films, mapping symmetries along with altermagnetic/electronic/structural phase transitions as functions of film thickness and temperature. This features an altermagnetic metallic polar phase in epitaxially strained 2 nm films, suggesting a potential link between polar metals and altermagnetic materials. Such a clear signature of a magnetic phase transition at ~500 K is observed exclusively in ultrathin strained films, unlike in bulk RuO 2 single crystals. These results highlight the power of epitaxial heterostructure engineering to induce altermagnetism in systems initially nonmagnetic, opening avenues for realizing emergent quantum phases with multifunctional properties.

RuO2 thin film↗

Local lattice distortions and electronic phases in perovskite manganite Pr 0.5 Sr 0.5 MnO 3

We use variable temperature and magnetic field total x-ray scattering to study the crystal structure of the strongly correlated Pr 0.5 Sr 0.5 MnO 3 perovskite, which is a paramagnetic insulator at room temperature, becomes a ferromagnetic metal at 272 K and, upon further decreasing the temperature, turns into an antiferromagnetic insulator at 105 K. We find that a model featuring a monoclinic symmetry captures the structure and its temperature and field evolution well, eliminating the need to evoke a phase segregation scenario as done in prior studies. It appears that coupled variations in Mn–oxygen bonding distances and angles from their values in an undistorted perovskite lattice, i.e., coupled local lattice distortions, assist the phase transitions in Pr 0.5 Sr 0.5 MnO 3 , contributing to its unique physical properties. Local structural distortions thus emerge as an important degree of freedom in strongly correlated systems, in particular perovskite manganates, and, therefore, they should be fully accounted for when their fascinating physics is considered.

36 MATERIALS SCIENCE↗

Atomic-scale polarization switching in wurtzite ferroelectrics

Ferroelectric wurtzites have the potential to revolutionize modern microelectronics because they are easily integrated with multiple mainstream semiconductor platforms. However, the electric fields required to reverse their polarization direction and unlock electronic and optical functions need substantial reduction for operational compatibility with complementary metal-oxide semiconductor (CMOS) electronics. To understand this process, we observed and quantified real-time polarization switching of a representative ferroelectric wurtzite (Al 0.94 B 0.06 N) at the atomic scale with scanning transmission electron microscopy. The analysis revealed a polarization reversal model in which puckered aluminum/boron nitride rings in the wurtzite basal planes gradually flatten and adopt a transient nonpolar geometry. Independent first-principles simulations reveal the details and energetics of the reversal process through an antipolar phase. Furthermore, this model and local mechanistic understanding are a critical initial step for property engineering efforts in this emerging material class.

36 MATERIALS SCIENCE↗

Integrating Systems and Synthetic Biology to Understand and Engineer Microbiomes

Microbiomes are complex and ubiquitous networks of microorganisms whose seemingly limitless chemical transformations could be harnessed to benefit agriculture, medicine, and biotechnology. Here, the spatial and temporal changes in microbiome composition and function are influenced by a multitude of molecular and ecological factors. This complexity yields both versatility and challenges in designing synthetic microbiomes and perturbing natural microbiomes in controlled, predictable ways. In this review, we describe factors that give rise to emergent spatial and temporal microbiome properties and the meta-omics and computational modeling tools that can be used to understand microbiomes at the cellular and system levels. We also describe strategies for designing and engineering microbiomes to enhance or build novel functions. Throughout the review,we discuss key knowledge and technology gaps for elucidating the networks and deciphering key control points for microbiome engineering, and highlight examples where multiple omics and modeling approaches can be integrated to address these gaps.

42 ENGINEERING↗

Electron Transfer from Semiconductor Nanocrystals to Redox Enzymes

This review summarizes progress in understanding electron transfer from photoexcited nanocrystals to redox enzymes. The combination of the light-harvesting properties of nanocrystals and the catalytic properties of redox enzymes has emerged as a versatile platform to drive a variety of enzyme-catalyzed reactions with light. Transfer of a photoexcited charge from a nanocrystal to an enzyme is a critical first step for these reactions. This process has been studied in depth in systems that combine Cd-chalcogenide nanocrystals with hydrogenases. The two components can be assembled in close proximity to enable direct interfacial electron transfer or integrated with redox mediators to transport charges. Time-resolved spectroscopy and kinetic modeling have been used to measure the rates and efficiencies of the electron transfer. Electron transfer has been described within the framework of Marcus theory, providing insights into the factors that can be used to control the photochemical activity of these biohybrid systems. The range of potential applications and reactions that can be achieved using nanocrystal–enzyme systems is expanding, and numerous fundamental and practical questions remain to be addressed.

Chemistry↗

AL-ASMR: Active Learning of Atomistic Surrogate Models for Rare Events

Atomistic simulation with artificial intelligence (AI) is an emerging tool for understanding materials' properties and behaviors and predicting novel materials with optimized/targeted properties. Neural network potentials (NNPs) are outstanding in this field as they have shown a comparable accuracy to ab initio electronic structure calculations for reproducing potential energy surfaces while being several orders of magnitude faster. However, such NNPs can perform poorly outside of their training domain and typically fail catastrophically in the prediction of rare events in molecular dynamics (MD) simulations. For effective AL loops to distinguish the informative data from enhanced sampled configurations, we developed a decision engine by configurational similarity and uncertainty quantification (UQ) with data augmentation.

Jung, Gang Seob↗

Nuclear Structure Studies at the Limits of Stability

On the quest for a predictive model of atomic nuclei, the properties of rare isotopes have emerged as critical observables that benchmark extrapolations, identify missing physics ingredients in models, or that enable discovery science. Formerly NSCL and now FRIB facilitate world-leading experiments due to the availability of fast, stopped, and reaccelerated rare-isotope beams in conjunction with unique instruments. DOE-SC NP Award DE-SC0020451 supported from 2019 to 2023 MSU’s nuclear structure and reactions program that tackles compelling questions in the field with complementary techniques, probing single-particle and collective degrees of freedom in relevant regions of the nuclear chart and enabled developments that positioned the PIs and their research groups for first FRIB science.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evidence for X-Ray Emission in Excess to the Jet-afterglow Decay 3.5 yr after the Binary Neutron Star Merger GW 170817: A New Emission Component

For the first ~3 yrs after the binary neutron star merger event GW 170817, the radio and X-ray radiation has been dominated by emission from a structured relativistic off-axis jet propagating into a low-density medium with n < 0.01 cm -3 . We report on observational evidence for an excess of X-ray emission at δt > 900 days after the merger. With L x ≈ 5 × 10 38 erg s -1 at 1234 days, the recently detected X-ray emission represents a ≥ 3.2σ (Gaussian equivalent) deviation from the universal post-jet-break model that best fits the multiwavelength afterglow at earlier times. In the context of JetFit afterglow models, current data represent a departure with statistical significance ≥ 3.1σ, depending on the fireball collimation, with the most realistic models showing excesses at the level of ≥ 3.7σ. A lack of detectable 3 GHz radio emission suggests a harder broadband spectrum than the jet afterglow. These properties are consistent with the emergence of a new emission component such as synchrotron radiation from a mildly relativistic shock generated by the expanding merger ejecta, i.e., a kilonova afterglow. In this context, we present a set of ab initio numerical relativity binary neutron star (BNS) merger simulations that show that an X-ray excess supports the presence of a high-velocity tail in the merger ejecta, and argues against the prompt collapse of the merger remnant into a black hole. Radiation from accretion processes on the compact-object remnant represents a viable alternative. Neither a kilonova afterglow nor accretion-powered emission have been observed before, as detections of BNS mergers at this phase of evolution are unprecedented

79 ASTRONOMY AND ASTROPHYSICS↗

A dust-shell model of the infrared object HD 45677

A dust-shell model of the infrared star HD-45677 was constructed by means of a generalization of the mathematical techniques of Huang. The model shows that an isotropically scattering, uniform-density spherical circumstellar dust shell is able to account for the observed emergent energy distribution. The extinction properties of the grains required depend on the energy distribution incident on the inner boundary of the shell such that gray grains are needed if the stellar temperature is about 13,000 K and a reciprocal wavelength extinction law is indicated for a star of 20,000 K. This model for HD 45677 is compared with that of Dyck and Milkey, who propose free-free emission from a circumstellar gas shell to account for the observed infrared excess.

Apruzese, J. P.↗

Theoretical modeling of the infrared fluorescence from interstellar polycyclic aromatic hydrocarbons

We have modeled the family of interstellar IR emission bands at 3.3, 6.2, 7.7, 8.6, 11.3, and 12.7 microns by calculating the fluorescence from a size distribution of interstellar polycyclic aromatic hydrocarbons (PAHs) embedded in the radiation field of a hot star. It is found that the various emission bands are dominated by distinctly different PAHs, from molecules with much less than about 80 C atoms for the 3.3 micron feature, to molecules with 10 exp 2-10 exp 5 C atoms for the emission in the IRAS 12 and 25 micron bands. We quantitatively describe the influence on the emergent spectrum of various PAH properties such as the molecular structure, the amount of dehydrogenation, the intrinsic strength of the IR active modes, and the size distribution. Comparing our model results to the emission spectrum from the Orion Bar region, we conclude that interstellar PAHs are likely fully, or almost fully, hydrogenated. Moreover, it is found that the intrinsic strengths of the 6.2 and 7.7 micron C-C stretching modes, and the 8.6 micron C-H in-plane bending mode are 2-6 times larger than measured for neutral PAHs in the laboratory.

Schutte, W. A.↗