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      Ultrafast Computational Screening of Molecules with Inverted Singlet–Triplet Energy Gaps Using the Pariser–Parr–Pople Semiempirical Quantum Chemistry Method

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          Abstract

          Molecules with an inverted energy gap between their first singlet and triplet excited states have promising applications in the next generation of organic light-emitting diode (OLED) materials. Unfortunately, such molecules are rare, and only a handful of examples are currently known. High-throughput virtual screening could assist in finding novel classes of these molecules, but current efforts are hampered by the high computational cost of the required quantum chemical methods. We present a method based on the semiempirical Pariser–Parr–Pople theory augmented by perturbation theory and show that it reproduces inverted gaps at a fraction of the cost of currently employed excited-state calculations. Our study paves the way for ultrahigh-throughput virtual screening and inverse design to accelerate the discovery and development of this new generation of OLED materials.

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          SciPy 1.0: fundamental algorithms for scientific computing in Python

          SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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            Matplotlib: A 2D Graphics Environment

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              Array programming with NumPy

              Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves 1 and in the first imaging of a black hole 2 . Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.
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                Author and article information

                Journal
                J Phys Chem A
                J Phys Chem A
                jx
                jpcafh
                The Journal of Physical Chemistry. a
                American Chemical Society
                1089-5639
                1520-5215
                14 March 2024
                28 March 2024
                : 128
                : 12
                : 2445-2456
                Affiliations
                []Institute of Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich , Vladimir-Prelog-Weg 1, Zürich CH-8093, Switzerland
                []Department of Chemistry and Chemical Engineering, Chalmers University of Technology , Kemigården 4, Gothenburg SE-41258, Sweden
                [§ ]Chemical Physics Theory Group, Department of Chemistry, University of Toronto , 80 St. George Street, Toronto M5S 3H6, Canada
                []Department of Computer Science, University of Toronto , 40 St. George Street, Toronto M5S 2E4, Canada
                []Stratingh Institute for Chemistry, University of Groningen , Nijenborgh 4, Groningen 9747, AG, The Netherlands
                [# ]Department of Chemical Engineering & Applied Chemistry, University of Toronto , 200 College Street, Toronto M5S 3E5, Canada
                []Department of Materials Science & Engineering, University of Toronto , 184 College Street, Toronto M5S 3E4, Canada
                []Vector Institute for Artificial Intelligence , 661 University Ave. Suite 710, Toronto M5G 1M1, Canada
                []Lebovic Fellow, Canadian Institute for Advanced Research (CIFAR) , 661 University Avenue, Toronto M5G 1M1, Canada
                []Acceleration Consortium, University of Toronto , 700 University Avenue, Toronto M5G 1Z5, Canada
                Author notes
                Author information
                https://orcid.org/0000-0002-4191-6790
                https://orcid.org/0000-0001-8836-6266
                https://orcid.org/0000-0002-8277-4434
                Article
                10.1021/acs.jpca.3c06357
                10983003
                38485448
                c76adf76-fb9e-4cc6-b27d-f26411d5abc6
                © 2024 The Authors. Published by American Chemical Society

                Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 22 September 2023
                : 23 February 2024
                : 23 February 2024
                Funding
                Funded by: Canadian Institute for Advanced Research, doi 10.13039/100007631;
                Award ID: NA
                Funded by: Canada First Research Excellence Fund, doi 10.13039/501100010785;
                Award ID: NA
                Funded by: Vetenskapsrådet, doi 10.13039/501100004359;
                Award ID: 2020-00314
                Funded by: Natural Resources Canada, doi 10.13039/501100000159;
                Award ID: NA
                Funded by: Social Sciences and Humanities Research Council of Canada, doi 10.13039/501100000155;
                Award ID: NA
                Funded by: Natural Sciences and Engineering Research Council of Canada, doi 10.13039/501100000038;
                Award ID: NA
                Funded by: Canadian Institutes of Health Research, doi 10.13039/501100000024;
                Award ID: NA
                Categories
                Article
                Custom metadata
                jp3c06357
                jp3c06357

                Physical chemistry
                Physical chemistry

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