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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 289 records · Page 16

Substitution Reactions in the Pyrolysis of Acetone Revealed through a Modeling, Experiment, Theory Paradigm

The development of high-fidelity mechanisms for chemically reactive systems is a challenging process that requires the compilation of rate descriptions for a large and somewhat ill-defined set of reactions. The present unified combination of modeling, experiment, and theory provides a paradigm for improving such mechanism development efforts. Here we combine broadband rotational spectroscopy with detailed chemical modeling based on rate constants obtained from automated ab initio transition state theory-based master equation calculations and high-level thermochemical parametrizations. Broadband rotational spectroscopy offers quantitative and isomer-specific detection by which branching ratios of polar reaction products may be obtained. Using this technique, we observe and characterize products arising from H atom substitution reactions in the flash pyrolysis of acetone (CH 3 C(O)CH 3 ) at a nominal temperature of 1800 K. The major product observed is ketene (CH 2 CO). Minor products identified include acetaldehyde (CH 3 CHO), propyne (CH 3 CCH), propene (CH 2 CHCH 3 ), and water (HDO). Literature mechanisms for the pyrolysis of acetone do not adequately describe the minor products. The inclusion of a variety of substitution reactions, with rate constants and thermochemistry obtained from automated ab initio kinetics predictions and Active Thermochemical Tables analyses, demonstrates an important role for such processes. Furthermore, the pathway to acetaldehyde is shown to be a direct result of substitution of acetone's methyl group by a free H atom, while propene formation arises from OH substitution in the enol form of acetone by a free H atom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid Allylic 1,6 H-Atom Transfer in an Unsaturated Criegee Intermediate

Here, a novel allylic 1,6 hydrogen-atom-transfer mechanism is established through infrared activation of the 2-butenal oxide Criegee intermediate, resulting in very rapid unimolecular decay to hydroxyl (OH) radical products. A new precursor, Z/E -1,3-diiodobut-1-ene, is synthesized and photolyzed in the presence of oxygen to generate anew four-carbon Criegee intermediate with extended conjugation across the vinyl and carbonyl oxide groups that facilitates rapid allylic 1,6 H-atom transfer. A low-energy reaction pathway involving isomerization of 2-butenal oxide from a lower-energy ( tZZ ) conformer to a higher-energy ( cZZ ) conformer followed by 1,6 hydrogen transfer via a seven-membered ring transition state is predicted theoretically and shown experimentally to yield OH products. The low-lying ( tZZ ) conformer of 2-butenaloxide is identified based on computed an harmonic frequencies and intensities of its conformers. Experimental IR action spectra recorded in the fundamental CH stretch region with OH product detection by UV laser-induced fluorescence reveal a distinctive IR transition of the low-lying ( tZZ ) conformer at 2996 cm -1 that results in rapid unimolecular decay to OH products. Statistical RRKM calculations involving a combination of conformational isomerization and unimolecular decay via 1,6 H-transfer yield an effective decay rate k eff ( E ) on the order of 10 8 s -1 at ca. 3000 cm -1 in good accord with the experiment. Unimolecular decay proceeds with significant enhancement due to quantum mechanical tunneling. A rapid thermal decay rate of ca. 10 6 s -1 is predicted by master-equation modeling of 2-butenal oxide at 298 K, 1 bar. This novel unimolecular decay pathway is expected to increase the nonphotolytic production of OH radicals upon alkene ozonolysis in the troposphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemistry of Sugar Formation in the Gas Phase: Following the Activated Aldehyde

Sugars are produced by living organisms, and are required building blocks for life as we know it, which raises the foundational question of how sugars formed in a prebiotic environment. The abiotic formose reaction produces sugars from formaldehyde, but our understanding of its initiation step remains murky, with chemists invoking the concept of an “activated aldehyde” to seed this reaction. Singlet hydroxycarbenes, high-energy isomers of aldehydes, were recently reported to facilitate sugar formation under cold, nonaqueous conditions relevant to interstellar environments. Here, we generate singlet methylhydroxycarbene ( 1 CH 3 –C̈–OH) from the photodissociation of pyruvic acid and experimentally measure its gas-phase reaction with d 4 -acetaldehyde using multiplexed photoionization mass spectrometry. The C 4 H 4 D 4 O 2 isomer d 4 -acetoin is the sole product, which we kinetically link to the reactant CH 3 –C̈–OH, and attribute to a carbonyl-ene formation mechanism. We see no evidence of 3-hydroxybutanal, the C–H insertion product expected in carbene chemistry. Using automated exploration we calculate stationary points on the potential energy surface and report master equation rate coefficients from T = 20–600 K, providing quantitative kinetics of this fast reaction for use in chemical models. The prereactive complex in this reaction is stabilized by both hydrogen bonding and electrophilic carbene C═O interactions. These effects create a short-range dynamical bottleneck for the reaction besides the long- and midrange barrierless bottlenecks. Combined with recent reports of 1 HC̈OH production from methanol photodissociation and pyruvic acid production in cold irradiated ices, this work provides evidence that singlet hydroxycarbene + aldehyde chemistry is a feasible path to prebiotic sugar formation.

aldehydes↗

A Parameterization of Turbulent Dissipation and Pressure Damping Time Scales in Stably Stratified Inversions, and its Effects on Low Clouds in Global Simulations

Abstract It is difficult for coarse‐resolution global models of the atmosphere to accurately simulate the observed distribution of low clouds. In particular, it is difficult for moist turbulence closure models to simulate sufficiently bright near‐coastal stratocumulus (Sc) without simulating overly bright marine shallow cumuli (Cu). To parameterize bright Sc, a turbulence parameterization must damp the turbulent fluxes of heat and moisture above cloud top in order to prevent excessive entrainment of dry air into cloud top. To parameterize dim shallow Cu, the subgrid variances of temperature and moisture must remain large, in order to permit partial cloudiness. However, damping the fluxes but not the variances just above cloud top is difficult if a parameterization uses a single “master” time scale to damp both. In nature, the above‐cloud fluxes are damped by pressure fluctuations, whereas scalar variances are damped by a different process, namely, turbulent dissipation. In a stably stratified inversion above cloud, pressure damping is large but turbulent dissipation is small. To avoid this problem, a multitime scale parameterization for damping has been developed. The damping parameterization has been implemented in a global model and evaluated. The parameterization is capable of dimming shallow Cu while producing adequately bright Sc.

54 ENVIRONMENTAL SCIENCES↗

Liquid condensation of reprogramming factor KLF4 with DNA provides a mechanism for chromatin organization

Expression of a few master transcription factors can reprogram the epigenetic landscape and three-dimensional chromatin topology of differentiated cells and achieve pluripotency. During reprogramming, thousands of long-range chromatin contacts are altered, and changes in promoter association with enhancers dramatically influence transcription. Molecular participants at these sites have been identified, but how this re-organization might be orchestrated is not known. Biomolecular condensation is implicated in subcellular organization, including the recruitment of RNA polymerase in transcriptional activation. Here, we show that reprogramming factor KLF4 undergoes biomolecular condensation even in the absence of its intrinsically disordered region. Liquid–liquid condensation of the isolated KLF4 DNA binding domain with a DNA fragment from the NANOG proximal promoter is enhanced by CpG methylation of a KLF4 cognate binding site. We propose KLF4-mediated condensation as one mechanism for selectively organizing and re-organizing the genome based on the local sequence and epigenetic state.

59 BASIC BIOLOGICAL SCIENCES↗

Programmed cell death regulator BAP2 is required for IRE1-mediated unfolded protein response in Arabidopsis

Environmental and physiological situations can challenge the balance between protein synthesis and folding capacity of the endoplasmic reticulum (ER) and cause ER stress, a potentially lethal condition. The unfolded protein response (UPR) restores ER homeostasis or actuates programmed cell death (PCD) when ER stress is unresolved. The cell fate determination mechanisms of the UPR are not well understood, especially in plants. Here, we integrate genetics and ER stress profiling with natural variation and quantitative trait locus analysis of 350 natural accessions of the model species Arabidopsis thaliana . Our analyses implicate a single nucleotide polymorphism to the loss of function of the general PCD regulator BON-ASSOCIATED PROTEIN2 (BAP2) in UPR outcomes. We establish that ER stress-induced BAP2 expression is antagonistically regulated by the UPR master regulator, inositol-requiring enzyme 1 (IRE1), and that BAP2 controls adaptive UPR amplitude in ER stress and ignites pro-death mechanisms in conditions of UPR insufficiency.

59 BASIC BIOLOGICAL SCIENCES↗

Transcriptional competition shapes proteotoxic ER stress resolution

Through dynamic activities of conserved master transcription factors (mTFs), the unfolded protein response (UPR) relieves proteostasis imbalance of the endoplasmic reticulum (ER), a condition known as ER stress. Because dysregulated UPR is lethal, the competence for fate changes of the UPR mTFs must be tightly controlled. However, the molecular mechanisms underlying regulatory dynamics of mTFs remain largely elusive. Here, we identified the abscisic acid-related regulator G-class bZIP TF2 (GBF2) and the cis-regulatory element G-box as regulatory components of the plant UPR led by the mTFs, bZIP28 and bZIP60. We demonstrate that, by competing with the mTFs at G-box, GBF2 represses UPR gene expression. Conversely, a gbf2 null mutation enhances UPR gene expression and suppresses the lethality of a bzip28 bzip60 mutant in unresolved ER stress. Here, by demonstrating that GBF2 functions as a transcriptional repressor of the UPR, we address the long-standing challenge of identifying shared signalling components for a better understanding of the dynamic nature and complexity of stress biology. Furthermore, our results identify a new layer of UPR gene regulation hinged upon an antagonistic mTFs-GFB2 competition for proteostasis and cell fate determination.

59 BASIC BIOLOGICAL SCIENCES↗

An IRE1-proteasome system signalling cohort controls cell fate determination in unresolved proteotoxic stress of the plant endoplasmic reticulum

Excessive accumulation of misfolded proteins in the endoplasmic reticulum (ER) causes ER stress, which is an underlying cause of major crop losses and devastating human conditions. Here, ER proteostasis surveillance is mediated by the conserved master regulator of the unfolded protein response (UPR), Inositol Requiring Enzyme 1 (IRE1), which determines cell fate by controlling pro-life and pro-death outcomes through as yet largely unknown mechanisms. Here we report that Arabidopsis IRE1 determines cell fate in ER stress by balancing the ubiquitin–proteasome system (UPS) and UPR through the plant-unique E3 ligase, PHOSPHATASE TYPE 2CA (PP2CA)-INTERACTING RING FINGER PROTEIN 1 (PIR1). Indeed, PIR1 loss leads to suppression of pro-death UPS and the lethal phenotype of an IRE1 loss-of-function mutant in unresolved ER stress in addition to activating pro-survival UPR. Specifically, in ER stress, PIR1 loss stabilizes ABI5, a basic leucine zipper (bZIP) transcription factor, that directly activates expression of the critical UPR regulator gene, bZIP60, triggering transcriptional cascades enhancing pro-survival UPR. Collectively, our results identify new cell fate effectors in plant ER stress by showing that IRE1’s coordination of cell death and survival hinges on PIR1, a key pro-death component of the UPS, which controls ABI5, a pro-survival transcriptional activator of bZIP60.

59 BASIC BIOLOGICAL SCIENCES↗

Unconventional isoquinoline-based SERMs elicit fulvestrant-like transcriptional programs in ER+ breast cancer cells

Estrogen receptor alpha (ERα) is a ligand-dependent master transcriptional regulator and key driver of breast cancer pathology. Small molecule hormones and competitive antagonists favor unique ERα conformational ensembles that elicit ligand-specific transcriptional programs in breast cancer and other hormone-responsive tissues. By affecting disparate ligand binding domain structural features, unconventional ligand scaffolds can redirect ERα genomic binding patterns to engage novel therapeutic transcriptional programs. To improve our understanding of these ERα structure-transcriptional relationships, we develop a series of chemically unconventional antagonists based on the antiestrogens elacestrant and lasofoxifene. High-resolution x-ray co-crystal structures show that these molecules affect both classical and unique structural motifs within the ERα ligand binding pocket. They show moderately reduced antagonistic potencies on ERα genomic activities but are effective anti-proliferative agents in luminal breast cancer cells. Interestingly, they favor a 4-hydroxytamoxifen-like accumulation of ERα in breast cancer cells but lack uterotrophic activities in an endometrial cell line. Importantly, RNA sequencing shows that the lead molecules engage transcriptional pathways similar to the selective estrogen receptor degrader fulvestrant. This advance shows that fulvestrant-like genomic activities can be achieved without affecting ERα accumulation in breast cancer cells.

60 APPLIED LIFE SCIENCES↗

Common workflows for computing material properties using different quantum engines

The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon and a burden. While providing great opportunities for cross-verification, these packages adopt different methods, algorithms, and paradigms, making it challenging to choose, master, and efficiently use them. We demonstrate how developing common interfaces for workflows that automatically compute material properties greatly simplifies interoperability and cross-verification. We introduce design rules for reusable, code-agnostic, workflow interfaces to compute well-defined material properties, which we implement for eleven quantum engines and use to compute various material properties. Each implementation encodes carefully selected simulation parameters and workflow logic, making the implementer’s expertise of the quantum engine directly available to non-experts. All workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure.

36 MATERIALS SCIENCE↗

High entropy powering green energy: hydrogen, batteries, electronics, and catalysis

A reformation in energy is underway to replace fossil fuels with renewable sources, driven by the development of new, robust, and multi-functional materials. High-entropy materials (HEMs) have emerged as promising candidates for various green energy applications, having unusual chemistries that give rise to remarkable functionalities. This review examines recent innovations in HEMs, focusing on hydrogen generation/storage, fuel cells, batteries, semiconductors/electronics, and catalysis—where HEMs have demonstrated the ability to outperform state-of-the-art materials. We present new master plots that illustrate the superior performance of HEMs compared to conventional systems for hydrogen generation/storage and heat-to-electricity conversion. We highlight the role of computational methods, such as density functional theory and machine learning, in accelerating the discovery and optimization of HEMs. The review also presents current challenges and proposes future directions for the field. We emphasize the need for continued integration of modeling, data, and experiments to investigate and leverage the underlying mechanisms of the HEMs that are powering progress in sustainable energy.

batteries↗

Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Heterogeneous Catalyst Discovery

Artificial intelligence is reshaping scientific exploration, but most methods automate procedural tasks without engaging in scientific reasoning, limiting autonomy in discovery. We demonstrate that hierarchical agentic large language model reasoning can efficiently drive simulation and scientific exploration. Across two chemical applications, CO adsorption on Cu surface transition metal adatoms and on M–N–C catalysts, reasoning-guided exploration reduces required atomistic simulations by up to 90% relative to heuristic or random selection. Comparisons across single-agent, multi-agent, and stochastic baselines show that hierarchical strategies yield more coherent and information-efficient search trajectories. Reasoning traces reveal chemically grounded decisions that cannot be explained by semantic bias or stochastic sampling. We realize these agentic reasoning strategies in Materials Agents for Simulation and Theory in Electronic-structure Reasoning (MASTER), a multimodal system that translates natural language into density functional theory workflows. Altogether, multi-agent collaboration accelerates heterogeneous catalyst discovery and marks a step toward more autonomous, reasoning-guided scientific exploration.

30 DIRECT ENERGY CONVERSION↗

Reconfigurable quantum phononic circuits via piezo-acoustomechanical interactions

Abstract We show that piezoelectric strain actuation of acoustomechanical interactions can produce large phase velocity changes in an existing quantum phononic platform: aluminum nitride on suspended silicon. Using finite element analysis, we demonstrate a piezo-acoustomechanical phase shifter waveguide capable of producing ± π phase shifts for GHz frequency phonons in 10s of μm with 10s of volts applied. Then, using the phase shifter as a building block, we demonstrate several phononic integrated circuit elements useful for quantum information processing. In particular, we show how to construct programmable multi-mode interferometers for linear phononic processing and a dynamically reconfigurable phononic memory that can switch between an ultra-long-lifetime state and a state strongly coupled to its bus waveguide. From the master equation for the full open quantum system of the reconfigurable phononic memory, we show that it is possible to perform read and write operations with over 90% quantum state transfer fidelity for an exponentially decaying pulse.

Taylor, Jeffrey C. (ORCID:0000000215982436)↗

Leveraging public AI tools to explore systems biology resources in mathematical modeling

Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are not designed for easy human readability and thus require specialized software to visualize and interpret results. Therefore, comprehending modeling and underlying networks and pathways is contingent on mastering systems biology tools, which is particularly challenging for users with no or little background in data science or system biology. To address this challenge, we investigated the usage of public Artificial Intelligence (AI) tools in exploring systems biology resources in mathematical modeling. We tested public AI’s understanding of mathematics in models, related systems biology data, and the complexity of model structures. Our approach can enhance the accessibility of systems biology for non-system biologists and help them understand systems biology without a deep learning curve.

59 BASIC BIOLOGICAL SCIENCES↗

Cross-HLA targeting of intracellular oncoproteins with peptide-centric CARs

The majority of oncogenic drivers are intracellular proteins, thus constraining their immunotherapeutic targeting to mutated peptides (neoantigens) presented by individual human leukocyte antigen (HLA) allotypes. However, most cancers have a modest mutational burden that is insufficient to generate responses using neoantigen-based therapies. Neuroblastoma is a paediatric cancer that harbours few mutations and is instead driven by epigenetically deregulated transcriptional networks. Here we show that the neuroblastoma immunopeptidome is enriched with peptides derived from proteins that are essential for tumourigenesis and focus on targeting the unmutated peptide QYNPIRTTF, discovered on HLA-A*24:02, which is derived from the neuroblastoma dependency gene and master transcriptional regulator PHOX2B. To target QYNPIRTTF, we developed peptide-centric chimeric antigen receptors (CARs) using a counter-panning strategy with predicted potentially cross-reactive peptides. We further hypothesized that peptide-centric CARs could recognize peptides on additional HLA allotypes when presented in a similar manner. Informed by computational modelling, we showed that PHOX2B peptide-centric CARs also recognize QYNPIRTTF presented by HLA-A*23:01 and the highly divergent HLA-B*14:02. Finally, we demonstrated potent and specific killing of neuroblastoma cells expressing these HLAs in vitro and complete tumour regression in mice. These data suggest that peptide-centric CARs have the potential to vastly expand the pool of immunotherapeutic targets to include non-immunogenic intracellular oncoproteins and widen the population of patients who would benefit from such therapy by breaking conventional HLA restriction.

59 BASIC BIOLOGICAL SCIENCES↗

Targeting of intracellular oncoproteins with peptide-centric CARs

The majority of oncogenic drivers are intracellular proteins, constraining their immunotherapeutic targeting to mutated peptides (neoantigens) presented by individual human leukocyte antigen (HLA) allotypes. However, most cancers have a modest mutational burden that is insufficient for generating responses using neoantigen-based therapies. Neuroblastoma is a paediatric cancer that harbours few mutations and is instead driven by epigenetically deregulated transcriptional networks. Here we show that the neuroblastoma immunopeptidome is enriched with peptides derived from proteins essential for tumorigenesis. We focused on targeting the unmutated peptide QYNPIRTTF discovered on HLA-A*24:02, which is derived from the neuroblastoma-dependency gene and master transcriptional regulator PHOX2B. To target QYNPIRTTF, we developed peptide-centric chimeric antigen receptors (PC-CARs) through a counter panning strategy using predicted potentially cross-reactive peptides. We further proposed that PC-CARs can recognize peptides on additional HLA allotypes when presenting a similar overall molecular surface. Informed by our computational modelling results, we show that PHOX2B PC-CARs also recognize QYNPIRTTF presented by HLA-A*23:01, the most common non-A2 allele in people with African ancestry. Finally, we demonstrate potent and specific killing of neuroblastoma cells expressing these HLAs in vitro and complete tumour regression in mice. These data suggest that PC-CARs have the potential to expand the pool of immunotherapeutic targets to include non-immunogenic intracellular oncoproteins and allow targeting through additional HLA allotypes in a clinical setting.

60 APPLIED LIFE SCIENCES↗

Azobenzene-based sinusoidal surface topography drives focal adhesion confinement and guides collective migration of epithelial cells

Surface topography is a key parameter in regulating the morphology and behavior of single cells. At multicellular level, coordinated cell displacements drive many biological events such as embryonic morphogenesis. However, the effect of surface topography on collective migration of epithelium has not been studied in detail. Mastering the connection between surface features and collective cellular behaviour is highly important for novel approaches in tissue engineering and repair. Herein, we used photopatterned microtopographies on azobenzene-containing materials and showed that smooth topographical cues with proper period and orientation can efficiently orchestrate cell alignment in growing epithelium. Furthermore, the experimental system allowed us to investigate how the orientation of the topographical features can alter the speed of wound closure in vitro. Our findings indicate that the extracellular microenvironment topography coordinates their focal adhesion distribution and alignment. These topographic cues are able to guide the collective migration of multicellular systems, even when cell–cell junctions are disrupted.

59 BASIC BIOLOGICAL SCIENCES↗

Classifying topology in photonic crystal slabs with radiative environments

Abstract In the recent years, photonic Chern materials have attracted substantial interest as they feature topological edge states that are robust against disorder, promising to realize defect-agnostic integrated photonic crystal slab devices. However, the out-of-plane radiative losses in those photonic Chern slabs has been previously neglected, yielding limited accuracy for predictions of these systems’ topological protection. Here, we develop a general framework for measuring the topological protection in photonic systems, such as in photonic crystal slabs, while accounting for in-plane and out-of-plane radiative losses. Our approach relies on the spectral localizer that combines the position and Hamiltonian matrices of the system to draw a real-picture of the system’s topology. This operator-based approach to topology allows us to use an effective Hamiltonian directly derived from the full-wave Maxwell equations after discretization via finite-elements method (FEM), resulting in the full account of all the system’s physical processes. As the spectral FEM-localizer is constructed solely from FEM discretization of the system’s master equation, the proposed framework is applicable to any physical system and is compatible with commonly used FEM software. Moving forward, we anticipate the generality of the method to aid in the topological classification of a broad range of complex physical systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗