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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 1,099 records · Page 61

A Case Study of Multimodal, Multi-institutional Data Management for the Combinatorial Materials Science Community

Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functional materials and acceleration of their design will require addressing the deficiencies that currently exist in materials informatics, particularly a lack of standardized experimental data management. The challenges associated with experimental data management are especially true for combinatorial materials science, where advancements in automation of experimental workflows have produced datasets that are often too large and too complex for human reasoning. The data management challenge is further compounded by the multimodal and multi-institutional nature of these datasets, as they tend to be distributed across multiple institutions and can vary substantially in format, size, and content. Furthermore, modern materials engineering requires the tuning of not only composition but also of phase and microstructure to elucidate processing–structure–property–performance relationships. To adequately map a materials design space from such datasets, an ideal materials data infrastructure would contain data and metadata describing (i) synthesis and processing conditions, (ii) characterization results, and (iii) property and performance measurements. In this work, we present a case study for the low-barrier development of such a dashboard that enables standardized organization, analysis, and visualization of a large data lake consisting of combinatorial datasets of synthesis and processing conditions, X-ray diffraction patterns, and materials property measurements generated at several different institutions. While this dashboard was developed specifically for data-driven thermoelectric materials discovery, we envision the adaptation of this prototype to other materials applications, and, more ambitiously, future integration into an all-encompassing materials data management infrastructure.

36 MATERIALS SCIENCE↗

Microbial communities for valorizing biomass using the carboxylate platform to produce volatile fatty acids: A review

The carboxylate platform employs a diverse microbial consortium of anaerobes in which the methanogens are inhibited. Nearly all biomass components are digested to a mixture of C1-C8 monocarboxylic acids and their corresponding salts. The methane-arrested anaerobic digestion proceeds readily without needing to sterilize biomass or equipment. It accepts a wide range of feedstocks (e.g., agricultural residues, municipal solid waste, sewage sludge, animal manure, food waste, algae, and energy crops), and produces high product yields. This review highlights several important aspects of the platform, including its thermodynamic underpinnings, influences of inoculum source and operating conditions on product formation, and downstream chemical processes that convert the carboxylates to hydrocarbon fuels and oxygenated chemicals. Furthermore, this review further establishes the carboxylate platform as a viable and economical route to industrial biomass utilization.

59 BASIC BIOLOGICAL SCIENCES↗

Kinetic, metabolic, and statistical analytics: addressing metabolic transport limitations among organelles and microbial communities

Microbial organisms engage in a variety of metabolic interactions. A crucial part of these interactions is the exchange of molecules between different organelles, cells, and the environment. The main forces mediating this metabolic exchange are transporters. This transport can be difficult to measure experimentally because several transport mechanisms remain opaque. However, theoretical calculations about the inputs and outputs of cells via metabolic exchanges have enabled the successful inference of the workings of intra-organismal and inter-organismal systems. Kinetic, metabolic, and statistical modeling approaches in combination with omics data are enhancing our knowledge and understanding about metabolic exchange and mass resource allocation. Furthermore, this model-driven analytics approach can guide effective experimental design and yield new insights into biological function and control.

59 BASIC BIOLOGICAL SCIENCES↗