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The use of machine learning in chemistry is on the rise for the prediction of chemical properties. The input feature representation or descriptor in these applications is an important factor that affects the accuracy as well as the extent of the explored chemical space. Here, we present the Periodic Table Tensor descriptor that combines features from Behler-Parrinello's symmetry functions and a Periodic Table Representation. Using our descriptor and a convolutional neural network model, we achieved 2.2 kcal/mol and 94 meV/atom Mean Absolute Error (MAE) for the prediction of the atomization energy of organic molecules in the QM9 dataset and the formation energy of materials from Materials Project dataset, respectively. We also show that structures optimized with Force Field can be used as input to predict the atomization energies of molecules at DFT level. Our approach extends the application of Behler-Parrinello's symmetry functions without a limitation on the number of elements, which is highly promising for universal property calculators in large chemical spaces.
This article was published in the following journal.
Name: Journal of chemical information and modeling
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We have extended our graphical processing unit (GPU) accelerated direct configuration interaction program to multiple devices, reducing iteration times for configuration spaces of 165 million determin...
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Establishing a solid theoretical foundation for structured deep neural networks is greatly desired due to the successful applications of deep learning in various practical domains. This paper aims at ...
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Objective: To establish the efficacy of laser application with chemical treatment in dental bleaching compared to chemical treatment alone. Methods: The investigators conducted a randomiz...
In addition to muscle thickness and average echo intensity, this study aimed to use quantitative ultrasonic technology to increase the number of related parameters of power Doppler ultraso...
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A class of unsegmented helminths with fundamental bilateral symmetry and secondary triradiate symmetry of the oral and esophageal structures. Many species are parasites.
An application that must be submitted to a regulatory agency (the FDA in the United States) before a drug can be studied in humans. This application includes results of previous experiments; how, where, and by whom the new studies will be conducted; the chemical structure of the compound; how it is thought to work in the body; any toxic effects found in animal studies; and how the compound is manufactured. (From the "New Medicines in Development" Series produced by the Pharmaceutical Manufacturers Association and published irregularly.)
Large cytoplasmic ribonucleoprotein particles that have an eight-fold symmetry with a central pore and petal-like structure giving the appearance of an octagonal dome. (The Dictionary of Cell Biology, Lackie and Dow, 2nd ed.)
The formation of a solid in a solution as a result of a chemical reaction or the aggregation of soluble substances into complexes large enough to fall out of solution.
Application of principles and practices of engineering science to the transformation, design, and manufacture of substances on an industrial scale.