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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

$\scriptsize\mathrm{{SQuIGG\overrightarrow{L}E}}$: Studying Quenching in Intermediate- z Galaxies—Gas, $\scriptsize\mathrm{{Angu\overrightarrow{L}ar}}$ Momentum, and Evolution

We describe the Studying Quenching in Intermediate-z Galaxies: Gas, $\scriptsize\mathrm{\rm{angu}}\overrightarrow{L}{\rm{ar}}$ momentum, and Evolution ($\scriptsize\mathrm{{SQuIGG\overrightarrow{L}E}}$) survey of intermediate-redshift post-starburst galaxies. We leverage the large sky coverage of the Sloan Digital Sky Survey to select ~1300 recently quenched galaxies at 0.5 < z ≤ 0.9 based on their unique spectral shapes. These bright, intermediate-redshift galaxies are ideal laboratories to study the physics responsible for the rapid quenching of star formation: they are distant enough to be useful analogs for high-redshift quenching galaxies, but low enough redshift that multiwavelength follow-up observations are feasible with modest telescope investments. We use the Prospector code to infer the stellar population properties and nonparametric star formation histories (SFHs) of all galaxies in the sample. We find that $\scriptsize\mathrm{{SQuIGG\overrightarrow{L}E}}$ galaxies are both very massive (M * ~ 10 11.25 M ⊙ ) and quenched, with inferred star formation rates ≲1 M ⊙ yr -1 , more than an order of magnitude below the star-forming main sequence. The best-fit SFHs confirm that these galaxies recently quenched a major burst of star formation: >75% of $\scriptsize\mathrm{{SQuIGG\overrightarrow{L}E}}$ galaxies formed at least a quarter of their total stellar mass in the recent burst, which ended just ~200 Myr before observation. We find that $\scriptsize\mathrm{{SQuIGG\overrightarrow{L}E}}$ galaxies are on average younger and more burst-dominated than most other z ≲ 1 post-starburst galaxy samples. This large sample of bright post-starburst galaxies at intermediate redshift opens a wide range of studies into the quenching process. In particular, the full $\scriptsize\mathrm{{SQuIGG\overrightarrow{L}E}}$ survey will investigate the molecular gas reservoirs, morphologies, kinematics, resolved stellar populations, active galactic nucleus incidence, and infrared properties of this unique sample of galaxies in order to place definitive constraints on the quenching process.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Formation, chemical evolution and solidification of the dense liquid phase of calcium (bi)carbonate

Metal carbonates, which are ubiquitous in the near-surface mineral record, are a major product of biomineralizing organisms and serve as important targets for capturing anthropogenic CO 2 emissions. However, pathways of carbonate mineralization typically diverge from classical predictions due to the involvement of disordered precursors, such as the dense liquid phase (DLP), yet little is known about DLP formation or solidification processes. Using in situ methods we report that a highly hydrated bicarbonate DLP forms via liquid–liquid phase separation and transforms into hollow hydrated amorphous CaCO 3 particles. Acidic proteins and polymers extend DLP lifetimes while leaving the pathway and chemistry unchanged. Molecular simulations suggest that the DLP forms via direct condensation of solvated Ca 2+ •(HCO 3 – ) 2 complexes that react due to proximity effects in the confined DLP droplets. Furthermore, our findings provide insight into CaCO 3 nucleation that is mediated by liquid–liquid phase separation, advancing the ability to direct carbonate mineralization and elucidating an often-proposed complex pathway of biomineralization.

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

On the Structural Transformation of Ni/BaH 2 During a N 2 -H 2 Chemical Looping Process for Ammonia Synthesis: A Joint In Situ Inelastic Neutron Scattering and First-Principles Simulation Study

The demand for decarbonizing the ammonia industry by using renewable energy has invoked increasing research interests into catalyst development for effective N 2 reduction under mild conditions. Hydride-based materials are among some of the emerging catalysts for ammonia synthesis at ambient pressure and low temperatures (< 673 K). A recent chemical looping process based on Ni/BaH 2 showed the most promise as it can realize ammonia production at a temperature as low as 373 K and under ambient pressure. However, the chemical transformation of the hydride catalyst at the molecular level remains unclear in this process. Here, we report detailed in situ neutron spectroscopy and diffraction investigations along with first-principles simulations on the structural transformation of Ni/BaH 2 during the nitridation and hydrogenation steps in the chemical looping process for ammonia synthesis. It was shown that a ball-milling process of the starting Ni/BaH 2 could significantly decrease the size of BaH 2 and increase the density of defects, thus potentially enhancing the reactivity of the hydride. The evolution from BaH 2 to barium imide (BaNH) was evidenced in the inelastic neutron scattering (INS) and neutron diffraction results during the N 2 reaction step. During the hydrogenation study, in addition to the recovery of BaH 2 , a possible intermediate species, N-deficient barium imide, was also detected. In comparing the N 2 and H 2 reaction steps, the neutron results indicate that the hydrogenation step appears more difficult than the nitridation step, confirming the facile N 2 fixation property of Ni/BaH 2 catalyst in ammonia synthesis.

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

Correlation between oxygen evolution reaction activity and surface compositional evolution in epitaxial La 0.5 Sr 0.5 Ni 1– x Fe x O 3– δ thin films

Water electrolysis can use renewable electricity to produce green hydrogen, a portable fuel and sustainable chemical precursor. Improving electrolyzer efficiency hinges on the activity of the oxygen evolution reaction (OER) catalyst. Earth-abundant, ABO 3 -type perovskite oxides offer great compositional, structural, and electronic tunability, with previous studies showing compositional substitution can increase the OER activity drastically. However, the relationship between the tailored bulk composition and that of the surface, where OER occurs, remains unclear. Here, we study the effects of electrochemical cycling on the OER activity of La 0.5 Sr 0.5 Ni 1– x Fe x O 3– δ ( x = 0–0.5) epitaxial films grown by oxide molecular beam epitaxy as a model Sr-containing perovskite oxide. In this work, electrochemical testing and surface-sensitive spectroscopic analyses show Ni segregation, which is affected by electrochemical history, along with surface amorphization, coupled with changes in OER activity. Our findings highlight the importance of surface composition and electrochemical cycling conditions in understanding OER performance, suggesting common motifs of the active surface with high surface area systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Considerations for Defining G-Values for Aluminum-Clad Spent Nuclear Fuel

Sealed-canister dry storage of aluminum-clad spent nuclear fuel (ASNF) generated by research reactors is an alternative to current storage and disposition pathways as directed by the U.S. Department of Energy. The major challenge faced for this storage approach is radiolytic H 2 generation, including from the aluminum (oxy)hydroxide layers on the surface of ASNF. Experimental and modeling activities have been carried out to characterize the radiolytic yield as part of a DOE-sponsored research program to develop the technical basis for ASNF dry storage. The G-value is a commonly way to report results of radiolysis testing and is defined as the radiolytic yield of a species (e.g. molecular hydrogen) per unit radiation energy deposited into the material system. An independent technical review of the ASNF dry storage technical basis performed by Pacific Northwest National Laboratory raised questions about differences in G-value definitions used for experiments on ASNF surrogates consisting of aluminum samples with adherent (oxy)hydroxides compared to G-values reported in prior literature and how the magnitudes compared between different studies. Material systems resembling ASNF pose complications for measuring/defining G-values to predict the evolution of H 2 in a sealed canister, including i) accounting for radiolytic yields potentially arising from multiple sources, i.e., residual free (vapor), physisorbed, and chemisorbed/chemically bound waters; ii) deciding what portions of the multi-material system to include in the absorbed energy (radiation dose) calculation, considering possible energy exchange between materials as well as measurement limitations, and iii) capturing variations in G-value associated with non-linear yield vs. dose curves and/or dependence on the cover gas. This report summarizes previous literature information on radiolytic H 2 generation and associated G-values from mixed-material systems (generally oxides in contact with water or organic compounds) and from (oxy)hydroxides/hydrates to compare with the definitions and values for ASNF surrogate samples containing adherent aluminum (oxy)hydroxides.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2003

Id expression in amphioxus and lamprey highlights the role of gene cooption during neural crest evolution

Neural crest cells are unique to vertebrates and generate many of the adult structures that differentiate them from their closest invertebrate relatives, the cephalochordates. Id genes are robust markers of neural crest cells at all stages of development. We compared Id gene expression in amphioxus and lamprey to ask if cephalochordates deploy Id genes at the neural plate border and dorsal neural tube in a manner similar to vertebrates. Furthermore, we examined whether Id expression in these cells is a basal vertebrate trait or a derived feature of gnathostomes. We found that while expression of Id genes in the mesoderm and endoderm is conserved between amphioxus and vertebrates, expression in the lateral neural plate border and dorsal neural tube is a vertebrate novelty. Furthermore, expression of lamprey Id implies that recruitment of Id genes to these cells occurred very early in the vertebrate lineage. Based on expression in amphioxus we postulate that Id cooption conferred sensory cell progenitor-like properties upon the lateral neurectoderm, and pharyngeal mesoderm-like properties upon cranial neural crest. Amphioxus Id expression is also consistent with homology between the anterior neurectoderm of amphioxus and the presumptive placodal ectoderm of vertebrates. These observations support the idea that neural crest evolution was driven in large part by cooption of multipurpose transcriptional regulators from other tissues and cell types.

NASA Program Fundamental Space Biology↗
NASA NTRS1999

LIfe: Past, Present and Future

Molecular methods of taxonomy and phylogeny have changed the way in which life on earth is viewed -- they have allowed us to transition from a eukaryote-centric view of the planet to one that is peculiarly prokarote-centric, containing three kingdoms, two of which are prokaryotic unicells.

biosignature↗
DOE OSTI2021

Insights into the Rich Polymorphism of the Na + Ion Conductor Na 3 PS 4 from the Perspective of Variable-Temperature Diffraction and Spectroscopy

Solid electrolytes are crucial for next-generation solid-state batteries, and Na 3 PS 4 is one of the most promising Na + conductors for such applications, despite outstanding questions regarding its structural polymorphs. In this contribution, we present a detailed investigation of the evolution in structure and dynamics of Na 3 PS 4 over a wide temperature range 30 < T T < 500 °C, which we attribute to dynamic local tetragonal distortions. The first-order phase transition to the mesophasic high-temperature polymorph (γ, Fddd ) is associated with a sharp volume increase and the onset of liquid-like dynamics for sodium-cations (translational) and thiophosphate-polyanions (rotational) evident by inelastic neutron and Raman spectroscopies, as well as pair-distribution function and molecular dynamics analyses. Overall, these results shed light on the rich polymorphism of Na 3 PS 4 and are relevant for a range host of high-performance materials deriving from the Na 3 PS 4 structural archetype.

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

Photoinduced correlations in stochastic dynamics of a solid-state ionic conductor

Photoexcitation by ultrashort laser pulses plays a crucial role in controlling reaction pathways, creating nonequilibrium material properties, and probing complex molecular dynamics. The photoresponse following a laser pulse is generally nonidentical between exposures due to spatiotemporal fluctuations or the stochastic nature of dynamical pathways. However, most ultrafast pump-probe experiments struggle to distinguish intrinsic sample fluctuations from extrinsic apparatus noise, often missing deviations from the averaged response. Leveraging the stability and high photon flux of time-resolved X-ray micro-diffraction at a synchrotron, we characterized stochastic photoinduced dynamics in a solid-state ionic conductor. By analyzing temporal evolutions of the lattice parameter of a single grain, we found that shot-to-shot fluctuations are not independent. Instead, correlations exist between nonequilibrium lattice trajectories following adjacent shots, with a characteristic correlation length of approximately 1500 shots, corresponding to an energy barrier of 0.4 ± 0.1 eV, close to the activation energy of lithium-ion diffusion.

36 MATERIALS SCIENCE↗
NASA NTRS1999

Membrane-Based Functions in the Origin of Cellular Life

Our objective is to help explain how the earliest ancestors of contemporary cells (protocells) performed their essential functions employing only the molecules available in the protobiological milieu. Our hypothesis is that vesicles, built of amphiphilic, membrane-forming materials, emerged early in protobiological evolution and served as precursors to protocells. We further assume that the cellular functions associated with contemporary membranes, such as capturing and, transducing of energy, signaling, or sequestering organic molecules and ions, evolved in these membrane environments. An alternative hypothesis is that these functions evolved in different environments and were incorporated into membrane-bound structures at some later stage of evolution. We focus on the application of the fundamental principles of physics and chemistry to determine how they apply to the formation of a primitive, functional cell. Rather than attempting to develop specific models for cellular functions and to identify the origin of the molecules which perform these functions, our goal is to define the structural and energetic conditions that any successful model must fulfill, therefore providing physico-chemical boundaries for these models. We do this by carrying out large-scale, molecular level computer simulations on systems of interest.

Chipot, Christophe↗
NASA NTRS1981

Molecular relationships between closely related strains and species of nematodes

Electrophoretic comparisons have been made for 24 enzymes in the Bergerac and Bristol strains of Caenorhabditis elegans and the related species, Caenorhabditis briggsae. No variation was detected between the two strains of C. elegans. In contrast, the two species, C. elegans and C. briggsae exhibited electrophoretic differences in 22 of 24 enzymes. A consensus 5S rRNA sequence was determined for C. elegans and found to be identical to that from C. briggsae. By analogy with other species with relatively well established fossil records it can be inferred that the time of divergence between the two nematode species is probably in the tens of millions of years. The limited anatomical evolution during a time period in which proteins undergo extensive changes supports the hypothesis that anatomical evolution is not dependent on overall protein changes.

Butler, M. H.↗
DOE OSTI2021

Data Science Meets Physical Organic Chemistry

At the heart of synthetic chemistry is the holy grail of predictable catalyst design. In particular, researchers involved in reaction development in asymmetric catalysis have pursued a variety of strategies toward this goal. This is driven by both the pragmatic need to achieve high selectivities and the inability to readily identify why a certain catalyst is effective for a given reaction. While empiricism and intuition have dominated the field of asymmetric catalysis since its inception, enantioselectivity offers a mechanistically rich platform to interrogate catalyst-structure response patterns that explain the performance of a particular catalyst or substrate. In the early stages of an asymmetric reaction development campaign, the overarching mechanism of the reaction, catalyst speciation, the turnover limiting step, and many other details are unknown or posited based on related reactions. Considering the unclear details leading to a successful reaction, initial enantioselectivity data are often used to intuitively guide the ultimate direction of optimization. However, if the conditions of the Curtin-Hammett principle are satisfied, then measured enantioselectivity can be directly connected to the ensemble of diastereomeric transition states (TSs) that lead to the enantiomeric products, and the associated free energy difference between competing TSs (ΔΔ G ‡ = - RT ln[( S )/( R )], where ( S ) and ( R ) represent the concentrations of the enantiomeric products). We, and others, speculated that this important piece of information can be leveraged to guide reaction optimization in a quantitative way. Although traditional linear free energy relationships (LFERs), such as Hammett plots, have been used to illuminate important mechanistic features, we sought to develop data science derived tools to expand the power of LFERs in order to describe complex reactions frequently encountered in modern asymmetric catalysis. Specifically, we investigated whether enantioselectivity data from a reaction can be quantitatively connected to the attributes of reaction components, such as catalyst and substrate structural features, to harness data for asymmetric catalyst design. In this context, we developed a workflow to relate computationally derived features of reaction components to enantioselectivity using data science tools. The mathematical representation of molecules can incorporate many aspects of a transformation, such as molecular features from substrate, product, catalyst, and proposed transition states. Statistical models relating these features to reaction outputs can be used for various tasks, such as performance prediction of untested molecules. Perhaps most importantly, statistical models can guide the generation of mechanistic hypotheses that are embedded within complex patterns of reaction responses. Overall, merging traditional physical organic experiments with statistical modeling techniques creates a feedback loop that enables both evaluation of multiple mechanistic hypotheses and future catalyst design. In this Account, we highlight the evolution and application of this approach in the context of a collaborative program based on chiral phosphoric acid catalysts (CPAs) in asymmetric catalysis.

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

Quantum Computing for Neutrino-Nucleus Scattering

Neutrino-nucleus cross section uncertainties are expected to be a dominant systematic in future accelerator neutrino experiments. The cross sections are determined by the linear response of the nucleus to the weak interactions of the neutrino, and are dominated by energy and distance scales of the order of the separation between nucleons in the nucleus. These response functions are potentially an important early physics application of quantum computers. Here we present an analysis of the resources required and their expected scaling for scattering cross section calculations. The current estimates of Trotter steps needed to achieve an energy resolution of 10 MeV and the number of CNOT gates for analyzing Ar40 highlights the need for significant improvements in algorithms. We also examine simple small-scale neutrino-nucleus models on modern quantum hardware. In this paper, we use variational methods to obtain the ground state of a three nucleon system (the triton) and then implement the relevant time evolution. To tame the errors in present-day NISQ devices, we explore the use of different error-mitigation techniques to increase the fidelity of the calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Machine-learning interatomic potentials for interfaces in all-solid-state batteries: Perspectives on training data, model selection, and validation

Interfaces play a pivotal role in dictating the performance and reliability of all-solid-state batteries (ASSBs), where complex electro-chemo-mechanical phenomena at grain boundaries (GBs) and interfaces can lead to degradation and failure. Traditional atomistic simulation methods, such as first-principles calculations and classical molecular dynamics, face limitations in modeling these interfaces due to either high computational cost or insufficient transferability to the diverse atomic environments evolving at interfaces. Machine-learning interatomic potentials (MLIPs) have emerged as a transformative approach, enabling large-scale, high-accuracy simulations of disordered and chemically complex systems by leveraging the predictability of machine learning models trained on first-principles data. Recent applications of MLIPs have demonstrated their ability to capture intricate behaviors at ASSB interfaces, including ion transport, interfacial evolution, and degradation mechanisms, with accuracy and efficiency unattainable by conventional methods. This prospective paper presents comprehensive analysis and practical guidance for MLIP development for GBs and interfaces in ASSBs, with a focus on three key pillars: data generation, model selection, and validation. Here, we review the current state of MLIP applications for GBs and interfaces in both general and ASSB-specific materials, highlighting best practices and challenges in constructing diverse and representative datasets, choosing appropriate machine learning architectures, and rigorously validating model performance. We also discuss emerging strategies and opportunities for improved reliability and efficiency of MLIPs to simulate realistic interfaces in ASSBs.

Energy - Storage↗
NASA NTRS1975

Conference on Interactions of the Interplanetary Plasma with the Modern and Ancient Moon, George Williams College, Lake Geneva, Wis., September 30-October 4, 1974, Proceedings

The papers deal with solar-wind and magnetospheric interactions with the moon, ancient and present-day lunar surface magnetic and electric fields, the dynamics and evolution of the lunar atmosphere, the lunar record of solar radiation, and nonmeteoric transport of lunar surface materials. Topics discussed include bow-shock protons in the lunar environment, energetic ion events during the lunar night, mapping of the lunar surface magnetic field from orbital observations of mirrored electrons, geomagnetic disturbances induced by the moon, the relationship between lunar topography and limb compressions, measurements of lunar sky brightness, atmospheric supply and loss mechanisms on the moon, the nature and composition of the lunar atmosphere, molecular gas species in that atmosphere, and vacuum-UV spectroscopic measurements of the surface properties of lunar materials. Individual items are announced in this issue.

Source record↗
DOE OSTI2026

Strain-Driven Evolution of Structural and Carrier Recombination Dynamics in Germanium

Strain engineering in group-IV semiconductors, in particular germanium (Ge), offers a promising route for advancing next-generation optoelectronic device performance. High minority carrier lifetime serves as a direct indicator of superior material quality and device efficiency. Several factors govern the minority carrier lifetime in both strained Ge and strained GeSn, such as strain level, epilayer thickness, defects, surface roughness, and Sn alloying. In this study, the impact of biaxial strain on effective minority carrier lifetimes of tensile-strained Ge (0% ..epsilon..-Ge/Al?As, 0.78% ..epsilon..-Ge/In0.115?Ga0.885?As, and 0.93% ..epsilon..-Ge/In0.16?Ga0.84?As) and compressively strained GeSn (-0.53% c-Ge0.97?Sn0.03/Al?As) epilayers, grown by molecular beam epitaxy, was experimentally investigated via the microwave-reflection photoconductive decay (..mu..-PCD) technique as a simultaneous function of thickness and strain. The structural and strain-relaxation properties were analyzed by high-resolution x-ray diffraction and Raman spectroscopy, while surface morphology analysis using atomic force microscopy provided insights into the surface roughness of strained Ge-based epilayers. Defect characterization by cross-section transmission electron microscopy revealed superior crystalline quality of ..epsilon..-Ge in one epilayer, while twin boundary formation was observed in the other. We investigated the carrier recombination dynamics in epitaxially strained Ge by extracting the bulk recombination lifetime and surface recombination velocity using the thickness-dependent minority carrier lifetime. High effective minority carrier lifetimes of approximately 60-340 ns were achieved at high strain levels with minimal dependence on the thickness of the strained Ge-based epilayers by means of the ..mu..-PCD technique. Minority carrier lifetimes in Ge-based epilayers exhibit a quadratic dependence on the biaxial strain, ranging from -0.88% (compressive) to +1.6% (tensile). The analysis of the carrier recombination dynamics in strained Ge-based heterostructures offers a pathway to designing group-IV based optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics

Chemical processes at metal oxide−water interfaces are of central importance in geochemistry, biology, and energy technologies. A better understanding of these processes would allow us to make a significant step toward optimizing and controlling them, which could in turn lead to broader impacts. Computational modeling is indispensable to accomplishing this task because complexity and disorder often make it difficult to extract atomistic information from experiments. Balancing computational cost and accuracy, simulation schemes based on efficient machine learning representations of the potential energy surface (PES) predicted by ab initio calculations have become increasingly popular over the past decade. In particular, several studies have demonstrated the ability of machine learning models to accurately reproduce the complex ab initio PESs of aqueous oxide interfaces, allowing simulations of systems and processes that are not accessible with ab initio methods. In this Account, we review our recent efforts to understand adsorption processes and reactions at aqueous oxide interfaces using deep potential molecular dynamics (DPMD), a simulation scheme employing deep neural networks (DNNs), which has proven to be quite successful in accurately describing many different systems in the condensed phase. After summarizing the DPMD methodology, we first review our work on the acid−base chemistry of oxide surfaces in contact with water, a fundamental characteristic that controls proton transfer and surface charge at the interface. We focus on the aqueous interface of rutile IrO 2 , an oxide material thus far considered the best catalyst for the oxygen evolution reaction (OER). We show that this interface is characterized by a large fraction of dissociated water and a strong Brønsted acidity of the surface sites, in good agreement with the experimentally measured value of the point of zero proton charge. In our second example, we investigate how the adsorption of organic species from ambient air or water affects the structure and wettability of the aqueous interfaces of TiO 2 , a prototypical photocatalytic material. This is a question that is relevant to understanding the UV-induced hydrophilicity of TiO 2 surfaces, a property at the basis of self-cleaning windows and related applications. Specifically focusing on formic and acetic acids, the two most common atmospheric organic acids, our simulations reveal that these acids control the wettability of TiO 2 largely through acid−base chemistry at the interface rather than chemisorption on the oxide surface, a finding that could help improve the design of self-cleaning surfaces and photocatalytic devices. Finally, we review our recent study of methanol at TiO 2 −water interfaces, a system whose interest is largely motivated by the role of methanol in enhancing photocatalytic hydrogen evolution on TiO 2 . Our simulations provide mechanistic insights into the coupled roles of the organic adsorbate and water at the TiO 2 interface, with implications for how methanol enhances the activity of H 2 evolution.

adsorption↗