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Bringing chemical structures to life with augmented reality, machine learning, and quantum chemistry.
Sakshuwong, Sukolsak; Weir, Hayley; Raucci, Umberto; Martínez, Todd J.
Afiliação
  • Sakshuwong S; Department of Management Science and Engineering, Stanford University, Stanford, California 94305, USA.
  • Weir H; Stanford PULSE Institute, SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA.
  • Raucci U; Stanford PULSE Institute, SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA.
  • Martínez TJ; Stanford PULSE Institute, SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA.
J Chem Phys ; 156(20): 204801, 2022 May 28.
Article em En | MEDLINE | ID: mdl-35649841
ABSTRACT
Visualizing 3D molecular structures is crucial to understanding and predicting their chemical behavior. However, static 2D hand-drawn skeletal structures remain the preferred method of chemical communication. Here, we combine cutting-edge technologies in augmented reality (AR), machine learning, and computational chemistry to develop MolAR, an open-source mobile application for visualizing molecules in AR directly from their hand-drawn chemical structures. Users can also visualize any molecule or protein directly from its name or protein data bank ID and compute chemical properties in real time via quantum chemistry cloud computing. MolAR provides an easily accessible platform for the scientific community to visualize and interact with 3D molecular structures in an immersive and engaging way.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Realidade Aumentada Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Realidade Aumentada Idioma: En Ano de publicação: 2022 Tipo de documento: Article