Definition and quantum chemical applications of nested summation symbols and logical functions: Pedagogical artificial intelligence devices for formulae writing, sequential programming and automatic parallel implementation

1995 ◽  
Vol 18 (1) ◽  
pp. 37-72 ◽  
Author(s):  
Ramon Carb� ◽  
Emili Besal�
Keyword(s):  
Artificial Intelligence ◽  
Quantum Chemical ◽  
Parallel Implementation ◽  
Sequential Programming ◽  
Logical Functions ◽  
Nested Summation Symbols

scholarly journals A Self-Improving Photosensitizer Discovery System via Bayesian Optimization and Quantum Chemical Calculation

2021 ◽  
Author(s):  
Shidang Xu ◽  
Jiali Li ◽  
Pengfei Cai ◽  
Xiaoli Liu ◽  
Bin Liu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Quantum Chemical ◽  
Prediction Accuracy ◽  
High Performance ◽  
Materials Science ◽  
Bayesian Optimization ◽  
Average Error ◽  
Chemical Calculation ◽  
Discovery System ◽  
Self Learning

Artificial intelligence (AI) based self-learning or self-improving material discovery system is the holy grail of next-generation material discovery and materials science. Herein, we demonstrate how to combine accurate prediction of material performance via quantum chemical calculations and Bayesian optimization-based active learning to realize a self-improving discovery system for high-performance photosensitizers (PS). Through self-improving cycles, such a system can improve the model prediction accuracy (best mean average error of 0.09 eV for singlet-triplet spitting) and high-performance PS search ability, realizing the efficient discovery of PS. From a molecular space with more than 7 million molecules, 5950 potential high-performance PSs were discovered.

scholarly journals Artificial Intelligence-Enhanced Quantum Chemical Method with Broad Applicability

2021 ◽  
Author(s):  
Peikun Zheng ◽  
Roman Zubatyuk ◽  
Wei Wu ◽  
Olexandr Isayev ◽  
Pavlo O. Dral
Keyword(s):  
Artificial Intelligence ◽  
Quantum Chemical ◽  
Chemical Method ◽  
Quantum Chemical Method ◽  
Broad Applicability

scholarly journals A Self-Improving Photosensitizer Discovery System via Bayesian Optimization and Quantum Chemical Calculation

2021 ◽  
Author(s):  
Shidang Xu ◽  
Jiali Li ◽  
Pengfei Cai ◽  
Xiaoli Liu ◽  
Bin Liu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Quantum Chemical ◽  
Prediction Accuracy ◽  
High Performance ◽  
Materials Science ◽  
Bayesian Optimization ◽  
Average Error ◽  
Chemical Calculation ◽  
Discovery System ◽  
Self Learning

Artificial intelligence (AI) based self-learning or self-improving material discovery system is the holy grail of next-generation material discovery and materials science. Herein, we demonstrate how to combine accurate prediction of material performance via quantum chemical calculations and Bayesian optimization-based active learning to realize a self-improving discovery system for high-performance photosensitizers (PS). Through self-improving cycles, such a system can improve the model prediction accuracy (best mean average error of 0.09 eV for singlet-triplet spitting) and high-performance PS search ability, realizing the efficient discovery of PS. From a molecular space with more than 7 million molecules, 5950 potential high-performance PSs were discovered.

Artificial Intelligence

2009 ◽  
Author(s):  
David L. Poole ◽  
Alan K. Mackworth
Keyword(s):  
Artificial Intelligence
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