This article reports implementation and performance of the artificial force induced reaction (AFIR) method in the upcoming 2017 version of GRRM program (GRRM17). The AFIR method, which is one of automated reaction path search methods, induces geometrical deformations in a system by pushing or pulling fragments defined in the system by an artificial force. In GRRM17, three different algorithms, that is, multicomponent algorithm (MC-AFIR), single-component algorithm (SC-AFIR), and double-sphere algorithm (DS-AFIR), are available, where the MC-AFIR was the only algorithm which has been available in the previous 2014 version. The MC-AFIR does automated sampling of reaction pathways between two or more reactant molecules. The SC-AFIR performs automated generation of global or semiglobal reaction path network. The DS-AFIR finds a single path between given two structures. Exploration of minimum energy structures within the hypersurface in which two different electronic states degenerate, and an interface with the quantum mechanics/molecular mechanics method, are also described. A code termed SAFIRE will also be available, as a visualization software for complicated reaction path networks. © 2017 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/jcc.25106 | DOI Listing |
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Division of Intelligent and Biomechanical Systems, State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, Haidian, Beijing, 100084, China.
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Background: Safe and effective pediatric blood pumps continue to lag far behind those developed for adults. To address this growing unmet clinical need, we are developing a hybrid, continuous-flow, magnetically levitated, pediatric total artificial heart (TAH). Our hybrid TAH design, the Dragon Heart (DH), integrates both an axial flow and centrifugal flow blood pump within a single, compact housing.
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Laboratory of Animal Husbandry, Department of Animal Production, Faculty of Agriculture, Forestry and Natural Environment, School of Agriculture, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
Artificial rearing (AR) of lambs is nowadays a common practice in Mediterranean dairy sheep production systems to enhance the milk available for cheese or yoghurt manufacturing. The sufficient growth of lambs in an AR system is vital for the economic success of dairy sheep farms. However, AR is often associated with negative impacts on the performance and physiology of lambs.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
BIFOLD─Berlin Institute for the Foundations of Learning and Data, 10587 Berlin, Germany.
While machine learning (ML) models have been able to achieve unprecedented accuracies across various prediction tasks in quantum chemistry, it is now apparent that accuracy on a test set alone is not a guarantee for robust chemical modeling such as stable molecular dynamics (MD). To go beyond accuracy, we use explainable artificial intelligence (XAI) techniques to develop a general analysis framework for atomic interactions and apply it to the SchNet and PaiNN neural network models. We compare these interactions with a set of fundamental chemical principles to understand how well the models have learned the underlying physicochemical concepts from the data.
View Article and Find Full Text PDFNanomaterials (Basel)
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Department of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA.
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