Generative Embeddings Network-based Semantic Inference and Search (GENESIS)
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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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This report describes the results of a workshop conducted at Goddard Space Flight Center (GSFC) to identify current and anticipated trends in human-computer interface technology that may influence the design or operation of a space station workstation. The workshop was attended by approximately 40 persons from government and academia who were selected for their expertise in some aspect of human-machine interaction research. The focus of the workshop was a 1 1/2 brainstorming/forecasting session in which the attendees were assigned to interdisciplinary working groups and instructed to develop predictions for each of the following technology areas: (1) user interface, (2) resource management, (3) control language, (4) data base systems, (5) automatic software development, (6) communications, (7) training, and (8) simulation. This report is significant in that it provides a unique perspective on workstation design for the space station. This perspective, which is characterized by a major emphasis on user requirements, should be most valuable to Phase B contractors involved in design development of the space station workstation. One of the more compelling results of the workshop is the recognition that no major technological breakthroughs are required to implement the current workstation concept. What is required is the creative application of existing knowledge and technology.
The project investigated biogeochemical processes at terrestrial-aquatic interfaces (TAIs), focusing on soil microsite heterogeneity and its impact on greenhouse gas (GHG) fluxes. Using laboratory experiments, modeling, and data integration, researchers explored redox-driven microbial processes under fluctuating hydrological conditions. Key advancements included modifying the DAMM-GHG model to incorporateelectron acceptor availability and enhancing the AquaMEND model for improved microbial metabolism representation. Results highlighted microsite redox variability as a key driver of GHG fluxes, informing Earth system models. The project fostered interdisciplinary collaborations, student training, and the development of novel modeling frameworks to improve Earth'senergy budget.
The International Space Station Medical Projects (ISSMP) Element provides planning, integration, and implementation services for HRP research studies for both spaceflight and flight analog research. Through the implementation of these two efforts, ISSMP offers an innovative way of guiding research decisions to meet the unique challenges of understanding the human risks to space exploration. Flight services provided by ISSMP include leading informed consent briefings, developing and validating in-flight crew procedures, providing ISS crew and ground-controller training, real-time experiment monitoring, on-orbit experiment and hardware operations and facilitating data transfer to investigators. For analog studies at the NASA Human Exploration Research Analog (HERA), the ISSMP team provides subject recruitment and screening, science requirements integration, data collection schedules, data sharing agreements, mission scenarios and facilities to support investigators. The ISSMP also serves as the HRP interface to external analog providers including the :envihab bed rest facility (Cologne, Germany), NEK isolation chamber (Moscow, Russia) and the Antarctica research stations. Investigators working in either spaceflight or analog environments requires a coordinated effort between NASA and the investigators. The interdisciplinary nature of both flight and analog research requires investigators to be aware of concurrent research studies and take into account potential confounding factors that may impact their research objectives. Investigators must define clear research requirements, participate in Investigator Working Group meetings, obtain human use approvals, and provide study-specific training, sample and data collection and procedures all while adhering to schedule deadlines. These science requirements define the technical, functional and performance operations to meet the research objectives. The ISSMP maintains an expert team of professionals with the knowledge and experience to guide investigators science through all aspects of mission planning, crew operations, and research integration. During this session, the ISSMP team will discuss best-practices approaches for successfully preparing and conducting studies in both the flight and analog environments. Critical tips and tricks will be shown to greatly improve your chances of successfully completing your research aboard the International Space Station and in Spaceflight Analogs.
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.
Semiconductor photoelectrochemistry is a dynamic and interdisciplinary field at the forefront of research in solar fuels, energy conversion, and catalysis. Here, this Perspective captures the collective insights from the second Gerischer Electrochemistry Today Symposium, held at Colorado State University in Fort Collins, CO, in August 2024, which convened leading researchers, early-career scientists, and industry partners to define the critical next steps for the field. Through interactive sessions, technical talks, panel discussions, and training initiatives─including a Semiconductor Electrochemistry Bootcamp─the symposium emphasized three pillars of advancement: (i) facilitating the exchange of new ideas in semiconductor electrochemistry and charge separation; (ii) fostering the development of future researchers, research topics, and participation in the semiconductor workforce; and (iii) building community. This Energy Focus distills key themes from the meeting and identifies major knowledge gaps in the following areas: mechanisms of charge separation and recombination, role of defects and disorder, dynamic and operando characterization methods, interfacial chemistry and surface passivation, theoretical and modeling limitations, and standardization and benchmarking. The inclusive and collaborative structure of the symposium enabled the generation of this comprehensive report that will serve as a roadmap for fundamental and applied research in the rapidly evolving field of semiconductor electrochemistry over the next decade.