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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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By combining the advantages of microfluidics and bulk batch synthesis, we developed a single-step, microfluidic-supported synthesis for anisotropic polyvinyl methacrylate (PVMA) polymer nanoparticles with dimensions ranging from 200 nm to 50 nm.
Using simulations and experiments, we propose a protocol for the programmable templated self-assembly of light-activated self-propelled particles. Additionally, we identify the scaling relations for the assembly's characteristic times.
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This work describes the examination of two derivatives of dipicolinic acid as the stripping reagents in the combined HEH[EHP], Cyanex-923 system TALSPEAK-MME. The investigation focused on the behavior of the lanthanides, Am, and the transition metals Zr, Mo, Pd, Ru and Rh in the extraction, solvent conditioning, and stripping steps. Solvent conditioning with glycine buffer solutions was shown to be effective for the removal of entrained HNO3¬ as well as managing Pd concentration prior to stripping. The stripping kinetics revealed very rapid phase transfer reactions. The DPA derivatives were shown to have comparable performance to traditional polyaminopolycarboxylate ligands in this system.
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Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.
Penicillium expansum is a major postharvest pathogen of apples, causing loss in fruits through tissue damage, as well as in apple products due to contamination with the mycotoxin patulin. During infections, patulin is a cultivar-dependent virulence factor that facilitates apple lesion development. Patulin also has characterized antimicrobial activity and is important for inhibiting other competitive phytopathogens, but the role of this inhibitory activity has not been investigated in the context of the apple microbiome. Here, in our current study, we isolated 68 apple microbiota and characterized their susceptibility to P. expansum extracts. We found gram-negative bacteria and basidiomycete yeast to demonstrate largely patulin-specific growth inhibition compared with gram-positive and ascomycete isolates. From co-cultures, we identified a Hanseniaspora and Gluconobacter pairing that reduced P. expansum biomass and found that H. uvarum alone is sufficient to reduce apple disease progression in vivo. We investigated possible mechanisms of H. uvarum biocontrol activity and found modest inhibition on apple puree plates, as well as a trend toward lower patulin levels at the wound site. Active biocontrol activity required live yeast, which was also effective in controlling Botrytis cinerea apple infections. Lastly, we explored the breadth of H. uvarum biocontrol activity with over 30 H. uvarum isolates and found consistent inhibition of P. expansum apple disease.
Target leaf spot (TLS) of sorghum, caused by the necrotrophic fungus Bipolaris cookei, can cause severe yield loss in many parts of the world. We grew B. cookei in liquid culture and observed that the resulting culture filtrate (CF) was differentially toxic when infiltrated into the leaves of a population of 288 diverse sorghum lines. In this population, we found a significant correlation between high CF sensitivity and susceptibility to TLS. This suggests that the toxin produced in culture may play a role in the pathogenicity of B. cookei in the field. We demonstrated that the toxic activity is light sensitive and, surprisingly, insensitive to pronase, suggesting that it is not proteinaceous. We identified the two sorghum genetic loci most associated with the response to CF in this population. Screening seedlings with B. cookei CF could be a useful approach for prescreening germplasm for TLS resistance.
Electronic coherences are key to understanding and controlling photoinduced molecular transformations. Here, we identify a crucial quantum-mechanical feature of electron-nuclear correlation, the projected nuclear quantum momenta, essential to capture the correct coherence behavior. For simulations, we show that, unlike traditional trajectory-based schemes, exact-factorization-based methods approximate these correlation terms and correctly capture electronic coherences in a range of situations, including their spatial dependence, an important aspect that influences subsequent electron dynamics and that is becoming accessible in more experiments.
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