Computational Chemistry as Applied in Environmental Research: Opportunities and Challenges

ACS ES&T Engineering, Journal Year: 2023, Volume and Issue: 4(1), P. 66 - 95

Published: Oct. 12, 2023

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

Language: Английский

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Basic guidelines of first-principles calculations for suitable selection of electrochemical Li storage materials: a review

Journal of Materials Chemistry A, Journal Year: 2023, Volume and Issue: 11(45), P. 24482 - 24518

Published: Jan. 1, 2023

This study provides deep insights into how computational methods complement and enhance experimental investigations.

Language: Английский

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Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters

Published: Sept. 20, 2023

Contemporary materials discovery requires intricate sequences of synthesis, formulation and characterization that often span multiple locations with specialized expertise or instrumentation. To accelerate these workflows, we present a cloud-based strategy enables delocalized asynchronous design–make–test–analyze cycles. We showcase this approach through the exploration molecular gain for organic solid-state lasers as frontier application in optoelectronics. Distributed robotic synthesis in-line property characterization, orchestrated by AI experiment planner, resulted 21 new state-of-the-art materials. Automated gram-scale ultimately allowed verification best-in-class stimulated emission thin-film device. Demonstrating integration five laboratories across globe, workflow provides blueprint delocalizing – democratizing scientific discovery.

Language: Английский

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Machine learning based nonlocal kinetic energy density functional for simple metals and alloys

Physical review. B./Physical review. B, Journal Year: 2024, Volume and Issue: 109(11)

Published: March 18, 2024

Developing an accurate kinetic energy density functional (KEDF) remains a major hurdle in orbital-free theory. We propose machine-learning-based physical-constrained nonlocal (MPN) KEDF and implement it with the usage of bulk-derived local pseudopotentials plane wave basis sets abacus package. The MPN is designed to satisfy three exact physical constraints: scaling law electron energy, free gas limit, non-negativity Pauli density. systematically tested for simple metals, including Li, Mg, Al, 59 alloys. conclude that incorporating information designing new KEDFs obeying constraints are essential improve accuracy, transferability, stability ML-based KEDF. These results shed light on construction functionals.

Language: Английский

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From Molecular Electronics to Molecular Intelligence

ACS Nano, Journal Year: 2024, Volume and Issue: 18(42), P. 28531 - 28556

Published: Oct. 12, 2024

Molecular electronics is a field that explores the ultimate limits of electronic device dimensions by using individual molecules as operable devices. Over past five decades since proposal molecular rectifier Aviram and Ratner in 1974 ( Chem. Phys. Lett.1974,29, 277−283), researchers have developed various fabrication characterization techniques to explore electrical properties molecules. With push characterizations data analysis methodologies, reproducibility issues single-molecule conductance measurement been chiefly resolved, origins variation among different devices investigated. Numerous prototypical with external physical chemical stimuli demonstrated based on advances instrumental methodological developments. These enable functions such switching, logic computing, synaptic-like computing. However, goal electronics, how can molecular-based intelligence be achieved through devices? At fiftieth anniversary we try answer this question summarizing recent progress providing an outlook electronics. First, review methodologies for junctions, which provide foundation Second, preliminary efforts toward integration circuits are discussed future potential intelligent applications. Third, some sensing applications introduced, demonstrating phenomena at scale beyond conventional macroscopic From perspective, summarize current challenges prospects describing concepts "AI electronics" "single-molecule AI".

Language: Английский

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