Will Artificial Intelligence be Useful (or Misused) in Environmental Toxicology and Chemistry?

Stahl, Ralph G.

doi:10.1002/etc.5575

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…381,382 Chat GPT, a modern tool of AI, has recently been employed in environmental-related fields: 383 environmental geochemical research, 384 global warming, 385 and environmental toxicology. 386 Admittedly, although computational chemistry methods have become an essential tool for environmental research, several limitations and challenges still need to be addressed in the next years. Computational approaches need to be developed to account for the complexity of real environmental systems while reducing computational cost.…”

Section: Challenges Perspectives and Conclusionmentioning

confidence: 99%

“…The inclusion of ML in QM and MD simulations has already been explored to study interfacial processes, radical chemical reactions, extended systems (e.g., biomolecules and nanomaterials), and photochemical transformations. The embedding of ML and IA models into QM and MM methods will likely lead to novel hybrid QM/MM/ML, further expanding the current applicability and accuracy of computational chemistry. , Chat GPT, a modern tool of AI, has recently been employed in environmental-related fields: environmental geochemical research, global warming, and environmental toxicology …”

Section: Challenges Perspectives and Conclusionmentioning

confidence: 99%

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Computational Chemistry as Applied in Environmental Research: Opportunities and Challenges

Sandoval-Pauker,

Yin,

Castillo

et al. 2023

ACS EST Eng.

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The constant development of computer systems and infrastructure has allowed computational chemistry to become an important component of environmental chemistry research. In the past decade, the application of quantum and classical mechanical calculations to model and understand environmental systems has increased exponentially. In this review, we highlight various applications of computational chemistry techniques in areas of environmental chemistry research (e.g., wastewater/air treatment, sensing, biodegradation). We briefly describe each computational approach, starting with quantum chemistry principle methods followed by molecular mechanics (MM), molecular dynamics (MD), and hybrid QM/MM methods. The recent introduction of artificial intelligence and machine learning techniques and their potential to disrupt the field are also discussed. Challenges and current and future directions to address them are presented.

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