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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 559 records · Page 31

BeyondFingerprinting: AI-guided discovery of robust materials & processes

BeyondFingerprinting was a 2021-2024 Sandia Grand Challenge LDRD exploring the potential to develop new resilient materials and manufacturing processes by taking an artificial-intelligence (AI)-guided approach that integrates human-subject-matter expertise with algorithms enriched with physics-based constraints to unearth process-structure-property correlations. Such algorithms, trained on high-throughput experiments and simulations, are shown to serve as surrogate models that efficiently detect key “fingerprints” in materials data, prognose material performance, and guide effective process improvements. To accelerate broader adoption across mission areas, this AI-guided approach was demonstrated with three complex process-centric exemplars: electroplating, physical vapor deposition, and laser powder bed fusion. Together, these exemplars impact nearly every hardware component relevant to DOE and NNSA national security missions.

36 MATERIALS SCIENCE↗

Unsupervised physics-informed disentanglement of multimodal data

Here, we introduce physics-informed multimodal autoencoders (PIMA) - a variational inference framework for discovering shared information in multimodal datasets. Individual modalities are embedded into a shared latent space and fused through a product-of-experts formulation, enabling a Gaussian mixture prior to identify shared features. Sampling from clusters allows cross-modal generative modeling, with a mixture-of-experts decoder that imposes inductive biases from prior scientific knowledge and thereby imparts structured disentanglement of the latent space. This approach enables cross-modal inference and the discovery of features in high-dimensional heterogeneous datasets. Consequently, this approach provides a means to discover fingerprints in multimodal scientific datasets and to avoid traditional bottlenecks related to high-fidelity measurement and characterization of scientific datasets.

97 MATHEMATICS AND COMPUTING↗

Determination of surface recombination velocity in heavily doped silicon

A method was developed and successfully tested for the determination of the effective surface recombination velocity of silicon layers doped by diffusion of phosphorus to a level of 10 to the 19th to 10 to the 21st per cu cm. The effective recombination velocity was obtained from the dependence of the electron-beam-induced current on the penetration of the electron beam of a scanning electron microscope. A special silicon diode was constructed which permitted the collection at the p-n junction of the carriers excited by the electron beam. This diode also permitted the study of the effects of surface preparation on the effective surface recombination velocity.

Watanabe, M.↗

Determination of minority-carrier lifetime and surface recombination velocity with high spacial resolution

Quantitative analysis of the electron beam induced current in conjunction with high-resolution scanning makes it possible to evaluate the minority-carrier lifetime three dimensionally in the bulk and the surface recombination velocity two dimensionally, with a high spacial resolution. The analysis is based on the concept of the effective excitation strength of the carriers which takes into consideration all possible recombination sources. Two-dimensional mapping of the surface recombination velocity of phosphorus-diffused silicon diodes is presented as well as a three-dimensional mapping of the changes in the minority-carrier lifetime in ion-implanted silicon.

Watanabe, M.↗