X-ray diffraction
PulseAugur coverage of X-ray diffraction — every cluster mentioning X-ray diffraction across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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Periodic Labs builds AI scientists for physical world experimentation
Periodic Labs is pioneering a new frontier in AI by developing autonomous laboratories capable of conducting physical experiments. Their vision of "synthesis superintelligence" aims to accelerate scientific discovery by…
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Plain text's enduring value and Rosalind Franklin's DNA discovery
This cluster contains two unrelated articles, one discussing the enduring value of plain text technology and another exploring Rosalind Franklin's contribution to the discovery of DNA's structure. The first article, sha…
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New self-learning agent streamlines X-ray diffraction analysis
Researchers have developed Gan Jiang, a self-learning scientific agent designed for powder X-ray diffraction analysis. This agent utilizes an integrated ecosystem of tools including XMatcher, XQueryer, XDecomposer, and …
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LLM Agents Drive Autonomous Materials Synthesis and Hypothesis Generation
Researchers have developed SynAgent, a novel framework that utilizes large language model agents to autonomously conduct materials synthesis experiments. Unlike traditional methods that focus on optimizing samples, SynA…
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AI model infers material microstructures from X-ray diffraction data
Researchers have developed a novel cross-modal learning framework to infer 3D dislocation microstructures directly from X-ray diffraction data. This approach embeds representations of dislocation density fields and thei…
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New SPEAR framework enhances AI explainability in materials science
Researchers have developed a new framework called SPEAR (Structure Property Explainability with Attention Regularization) to improve the interpretability of machine learning models used in materials science. This framew…
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Diffusion Model Predicts Crystal Structures from X-Ray Diffraction Data
Researchers have developed XRDiff, a novel diffusion model capable of predicting crystal structures from powder X-ray diffraction (PXRD) data. This model can infer structures based on known stoichiometry or, more challe…
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Deep learning revolutionizes crystal structure prediction and analysis
Researchers have developed new deep learning methods for crystal structure prediction and analysis. One approach, CrystalX, uses deep learning to automate routine X-ray diffraction analysis, outperforming existing autom…
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Machine learning potentials struggle to predict silica glass structure
Researchers have investigated the limitations of machine learning potentials in accurately predicting the medium-range order of silica glass. Using neutron and X-ray diffraction alongside molecular dynamics, they found …