LEARNINGInstructSingleCRYSTALGROWTHFLUXMethodGrowth of high-quality single crystals is of great significance for research of condensed matter physics. The exploration of suitable growing conditions for single crystals is expensive and time-consuming, especially for ternary compounds because of the lack of ...
We present a machine learning approach for high-throughput crystal orientation mapping, which relies on the optical technique called directional reflectance microscopy. We successfully apply our method on Inconel 718 specimens produced by additive manufacturing, which exhibit complex, spatially-varying ...
learning optimization in this work. Royalty-free graphic of the robotic hand was obtained from pngtree. There are a number of interrelated process parameters in CBD which will influence the growth mode of (CuS)x(ZnS)1-x nanocomposite thin films. The first is the relative ratios of the Cu an...
Alloy modelling has a history of machine-learning-like approaches, preceding the tide of data-science-inspired work. The dawn of computational databases has made the integration of analysis, prediction and discovery the key theme in accelerated alloy research. Advances in machine-learning methods and...
Machine learning also offers a different perspective to understand and model systems with a scalable computational platform. Here, we present the results of this philosophy describing the growth of platinum nanoparticles under supercritical conditions using a mathematical tool called Gaussian process ...
Summary of the testing-set mean absolute error (MAE), coefficient of determination (R2), and Spearman rank-order correlation coefficient (ρ) for several machine learning methods to predict the computed band gaps of MOFs from their deposited crystal structures with free solvent removed. Kernel ridge...
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Research findings on Machine Learning are discussed in a new report. According to news reporting originating from Tamil Nadu, India, by NewsRx correspondents, research stated, "Crop yield prediction is a...
Today, I would like to announce that we are creating a new workshop forPAKDD 2025called the1st Workshop on Pattern mining and Machine learning for Bioinformatics(PM4B 2025). The goal of the workshop is to establish a collaborative platform for researchers and practitioners to share theoretical ...
Fig. 1: Schematic illustrations of carbon-growth-on-metal machine-learning potential (CGM-MLP) generated by active learning on-the-fly during hybrid molecular dynamics and time-stamped force-biased Monte Carlo (MD/tfMC) simulations. aThe initial training dataset includes representative carbon structures...
machine learning methods, the data acquisition process and active learning procedures. We highlight multiple recent applications of machine-learned potentials in various fields, ranging from organic chemistry and biomolecules to inorganic crystal structure predictions and surface science. We furthermore ...