首页|Studies from Lawrence Livermore National Laboratory Have Provided New Informatio n about Machine Learning (Integrating Machine Learning Potential and X-ray Absor ption Spectroscopy for Predicting the Chemical Speciation of Disordered Carbon . ..)

Studies from Lawrence Livermore National Laboratory Have Provided New Informatio n about Machine Learning (Integrating Machine Learning Potential and X-ray Absor ption Spectroscopy for Predicting the Chemical Speciation of Disordered Carbon . ..)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news originating from Livermore, California, by N ewsRx correspondents, research stated, "Precise determination of atomic structur al information in functional materials holds transformative potential and broad implications for emerging technologies. Spectroscopic techniques, such as X-ray absorption near-edge structure (XANES), have been widely used for material chara cterization; however, extracting chemical information from experimental probes r emains a significant challenge, particularly for disordered materials." Financial supporters for this research include United States Department of Energ y (DOE), United States Department of Energy (DOE), Laboratory Directed Research and Development (LDRD) program, United States Department of Energy (DOE).

LivermoreCaliforniaUnited StatesNo rth and Central AmericaCyborgsEmerging TechnologiesMachine LearningLawre nce Livermore National Laboratory

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jun.19)