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}

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@article{tao2016,
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  abstract = {Weakly bound non-valence anions are molecular systems where the excess electron stabilizes in a very diffuse orbital whose size, shape, and binding energy ({$\sim$}1-100 meV) are governed by the long-range electrostatic potential of the molecule. Its binding energy comes mainly from charge-dipole or charge- multipole interactions or dispersion forces. While highly correlated methods, like coupled cluster methods, are considered to be the state of the art for describing anionic systems, especially when the electron lies in a very diffuse orbital, we consider here the possibility to use DFT-based calculations. In such molecular anions, the outer electron experiences long-range exchange and correlation interactions. We show that DFT can describe longrange bound states provided that a correct asymptotic exchange and correlation potential is used, namely, that from a range-separated hybrid functional. This opens an alternative to the computationally demanding highly correlated method calculations. It is also suggested that the study of weakly bound anions could help in the construction of new DFT potentials to study systems where nonlocal effects are significant.},
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}

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@article{tsuzuki2006,
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@article{turney2012,
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}

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}

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@article{vanvleet,
  title = {Beyond {{Born-Mayer}}: {{Improved Models}} for {{Short-Range Repulsion}} in Ab Initio {{Force Fields}}},
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}

@article{vanvleeta,
  title = {Beyond {{Born-Mayer}}: {{Improved}} Models Fo Short-Range Repulsion in Ab Initio Force Fields},
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}

@article{vereecken2012,
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  urldate = {2023-06-28},
  langid = {english}
}

@article{verstraelen2016,
  title = {Minimal {{Basis Iterative Stockholder}}: {{Atoms}} in {{Molecules}} for {{Force-Field Development}}},
  shorttitle = {Minimal {{Basis Iterative Stockholder}}},
  author = {Verstraelen, Toon and Vandenbrande, Steven and {Heidar-Zadeh}, Farnaz and Vanduyfhuys, Louis and Van Speybroeck, Veronique and Waroquier, Michel and Ayers, Paul W.},
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  doi = {10.1021/acs.jctc.6b00456},
  urldate = {2022-04-27},
  abstract = {Atomic partial charges appear in the Coulomb term of many force-field models and can be derived from electronic structure calculations with a myriad of atoms-inmolecules (AIM) methods. More advanced models have also been proposed, using the distributed nature of the electron cloud and atomic multipoles. In this work, an electrostatic force field is defined through a concise approximation of the electron density, for which the Coulomb interaction is trivially evaluated. This approximate ``pro-density'' is expanded in a minimal basis of atom-centered s-type Slater density functions, whose parameters are optimized by minimizing the Kullback- Leibler divergence of the pro-density from a reference electron density, e.g., obtained from an electronic structure calculation. The proposed method, Minimal Basis Iterative Stockholder (MBIS), is a variant of the Hirshfeld AIM method, but it can also be used as a density-fitting technique. An iterative algorithm to refine the pro-density is easily implemented with a linear-scaling computational cost, enabling applications to supramolecular systems. The benefits of the MBIS method are demonstrated with systematic applications to molecular databases and extended models of condensed phases. A comparison to 14 other AIM methods shows its effectiveness when modeling electrostatic interactions. MBIS is also suitable for rescaling atomic polarizabilities in the Tkatchenko-Scheffler scheme for dispersion interactions.},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/HWNCP6AM/Verstraelen et al. - 2016 - Minimal Basis Iterative Stockholder Atoms in Mole.pdf}
}

@article{villot2023,
  title = {Electronic Structure Theory on Modeling Short-Range Noncovalent Interactions between Amino Acids},
  author = {Villot, Corentin and Lao, Ka Un},
  year = {2023},
  month = mar,
  journal = {J. Chem. Phys.},
  volume = {158},
  number = {9},
  pages = {094301},
  issn = {0021-9606, 1089-7690},
  doi = {10.1063/5.0138032},
  urldate = {2023-04-05},
  abstract = {While short-range noncovalent interactions (NCIs) are proving to be of importance in many chemical and biological systems, these atypical bindings happen within the so-called van der Waals envelope and pose an enormous challenge for current computational methods. We introduce SNCIAA, a database of 723 benchmark interaction energies of short-range noncovalent interactions between neutral/charged amino acids originated from protein x-ray crystal structures at the ``gold standard'' coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory with a mean absolute binding uncertainty less than 0.1 kcal/mol. Subsequently, a systematic assessment of commonly used computational methods, such as the second-order M\o ller-Plesset theory (MP2), density functional theory (DFT), symmetry-adapted perturbation theory (SAPT), composite electronic-structure methods, semiempirical approaches, and the physical-based potentials with machine learning (IPML) on SNCIAA is carried out. It is shown that the inclusion of dispersion corrections is essential even though these dimers are dominated by electrostatics, such as hydrogen bondings and salt bridges. Overall, MP2, {$\omega$}B97M-V, and B3LYP+D4 turned out to be the most reliable methods for the description of short-range NCIs even in strongly attractive/repulsive complexes. SAPT is also recommended in describing short-range NCIs only if the {$\delta$}MP2 correction has been included. The good performance of IPML for dimers at close-equilibrium and long-range conditions is not transferable to the short-range. We expect that SNCIAA will assist the development/improvement/validation of computational methods, such as DFT, force-fields, and ML models, in describing NCIs across entire potential energy surfaces (short-, intermediate-, and long-range NCIs) on the same footing.},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/FT2YHAWM/Villot and Lao - 2023 - Electronic structure theory on modeling short-rang.pdf}
}

@article{villot2023a,
  title = {Electronic Structure Theory on Modeling Short-Range Noncovalent Interactions between Amino Acids},
  author = {Villot, Corentin and Lao, Ka Un},
  year = {2023},
  month = mar,
  journal = {The Journal of Chemical Physics},
  volume = {158},
  number = {9},
  pages = {094301},
  issn = {0021-9606},
  doi = {10.1063/5.0138032},
  urldate = {2023-07-06},
  abstract = {While short-range noncovalent interactions (NCIs) are proving to be of importance in many chemical and biological systems, these atypical bindings happen within the so-called van der Waals envelope and pose an enormous challenge for current computational methods. We introduce SNCIAA, a database of 723 benchmark interaction energies of short-range noncovalent interactions between neutral/charged amino acids originated from protein x-ray crystal structures at the ``gold standard'' coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory with a mean absolute binding uncertainty less than 0.1 kcal/mol. Subsequently, a systematic assessment of commonly used computational methods, such as the second-order M\o ller-Plesset theory (MP2), density functional theory (DFT), symmetry-adapted perturbation theory (SAPT), composite electronic-structure methods, semiempirical approaches, and the physical-based potentials with machine learning (IPML) on SNCIAA is carried out. It is shown that the inclusion of dispersion corrections is essential even though these dimers are dominated by electrostatics, such as hydrogen bondings and salt bridges. Overall, MP2, {$\omega$}B97M-V, and B3LYP+D4 turned out to be the most reliable methods for the description of short-range NCIs even in strongly attractive/repulsive complexes. SAPT is also recommended in describing short-range NCIs only if the {$\delta$}MP2 correction has been included. The good performance of IPML for dimers at close-equilibrium and long-range conditions is not transferable to the short-range. We expect that SNCIAA will assist the development/improvement/validation of computational methods, such as DFT, force-fields, and ML models, in describing NCIs across entire potential energy surfaces (short-, intermediate-, and long-range NCIs) on the same footing.},
  file = {/Users/dasirianni/Zotero/storage/W64ENE8A/Electronic-structure-theory-on-modeling-short.html}
}

@article{villot2023b,
  title = {Electronic Structure Theory on Modeling Short-Range Noncovalent Interactions between Amino Acids},
  author = {Villot, Corentin and Lao, Ka Un},
  year = {2023},
  month = mar,
  journal = {The Journal of Chemical Physics},
  volume = {158},
  number = {9},
  pages = {094301},
  issn = {0021-9606},
  doi = {10.1063/5.0138032},
  urldate = {2023-07-06},
  abstract = {While short-range noncovalent interactions (NCIs) are proving to be of importance in many chemical and biological systems, these atypical bindings happen within the so-called van der Waals envelope and pose an enormous challenge for current computational methods. We introduce SNCIAA, a database of 723 benchmark interaction energies of short-range noncovalent interactions between neutral/charged amino acids originated from protein x-ray crystal structures at the ``gold standard'' coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory with a mean absolute binding uncertainty less than 0.1 kcal/mol. Subsequently, a systematic assessment of commonly used computational methods, such as the second-order M\o ller-Plesset theory (MP2), density functional theory (DFT), symmetry-adapted perturbation theory (SAPT), composite electronic-structure methods, semiempirical approaches, and the physical-based potentials with machine learning (IPML) on SNCIAA is carried out. It is shown that the inclusion of dispersion corrections is essential even though these dimers are dominated by electrostatics, such as hydrogen bondings and salt bridges. Overall, MP2, {$\omega$}B97M-V, and B3LYP+D4 turned out to be the most reliable methods for the description of short-range NCIs even in strongly attractive/repulsive complexes. SAPT is also recommended in describing short-range NCIs only if the {$\delta$}MP2 correction has been included. The good performance of IPML for dimers at close-equilibrium and long-range conditions is not transferable to the short-range. We expect that SNCIAA will assist the development/improvement/validation of computational methods, such as DFT, force-fields, and ML models, in describing NCIs across entire potential energy surfaces (short-, intermediate-, and long-range NCIs) on the same footing.},
  file = {/Users/dasirianni/Zotero/storage/KMRRC86I/Electronic-structure-theory-on-modeling-short.html}
}

@article{vogiatzis2009,
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}

@article{vogiatzis2013,
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}

@article{vogiatzis2017,
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}

@article{voloshina2011,
  title = {On the Physisorption of Water on Graphene: A {{CCSD}}({{T}}) Study},
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}

@article{vukovic2014,
  title = {Molecular {{Friction-Induced Electroosmotic Phenomena}} in {{Thin Neutral Nanotubes}}},
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@article{vydrov2006,
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@article{vydrov2010,
  title = {Nonlocal van Der {{Waals}} Density Functional: {{The}} Simpler the Better},
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@article{wahba1965,
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}

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}

@article{wang2004,
  title = {Development and Testing of a General Amber Force Field},
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}

@article{wang2004a,
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}

@article{wang2006,
  title = {Automatic Atom Type and Bond Type Perception in Molecular Mechanical Calculations},
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}

@article{wang2006a,
  title = {Automatic Atom Type and Bond Type Perception in Molecular Mechanical Calculations},
  author = {Wang, Junmei and Wang, Wei and Kollman, Peter A and Case, David A},
  year = {2006},
  month = oct,
  journal = {Journal of Molecular Graphics and Modelling},
  volume = {25},
  number = {2},
  pages = {247--260},
  doi = {10.1016/j.jmgm.2005.12.005},
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}

@article{wang2008,
  title = {An Extended Multireference Study of the Electronic States of {\emph{Para}} -Benzyne},
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  langid = {english}
}

@article{wang2014,
  title = {Discovering Chemistry with an \textbackslash emphab Initio Nanoreactor},
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}

@article{wang2015,
  title = {The Benzene{$\cdots$}naphthalene Complex: {{A}} More Challenging System than the Benzene Dimer for Newly Developed Computational Methods},
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}

@article{wang2016,
  title = {Explicitly Correlated Second-Order {{M\o ller-Plesset}} Perturbation Theory in a {{Divide-Expand-Consolidate}} ({{DEC}}) Context},
  author = {Wang, Yang Min and H{\"a}ttig, Christof and Reine, Simen and Valeev, Edward and Kj{\ae}rgaard, Thomas and Kristensen, Kasper},
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}

@article{wang2016a,
  title = {Automated {{Discovery}} and {{Refinement}} of {{Reactive Molecular Dynamics Pathways}}},
  author = {Wang, Lee-Ping and McGibbon, Robert T and Pande, Vijay S and Mart{\'i}nez, Todd J},
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  month = jan,
  journal = {J. Chem. Theory Comput.},
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}

@article{wang2018,
  title = {Fragment-Based Quantum Mechanical Calculation of Protein-Protein Binding Affinities},
  author = {Wang, Yaqian and Liu, Jinfeng and Li, Jinjin and He, Xiao},
  year = {2018},
  month = apr,
  journal = {J. Comput. Chem.},
  volume = {39},
  number = {21},
  pages = {1617--1628},
  doi = {10.1002/jcc.25236},
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}

@article{wang2018a,
  title = {Fragment-Based Quantum Mechanical Calculation of Protein-Protein Binding Affinities},
  author = {Wang, Yaqian and Liu, Jinfeng and Li, Jinjin and He, Xiao},
  year = {2018},
  month = apr,
  journal = {J. Comput. Chem.},
  volume = {39},
  number = {21},
  pages = {1617--1628},
  doi = {10.1002/jcc.25236},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/F3PHXC7Q/DCEBEB38-8A10-4827-9AFA-CFCAB5874780.pdf}
}

@article{wang2019,
  title = {Iridium-{{Catalyzed Enantioselective C}}(Sp3)\textendash{{H Amidation Controlled}} by {{Attractive Noncovalent Interactions}}},
  author = {Wang, Hao and {ORCID: 0000-0003-1511-0635}, Yoonsu Park and Bai, Ziqian and {ORCID: 0000-0001-9069-0946}, Sukbok Chang and He, Gang and {ORCID: 0000-0002-5067-9889}, Gong Chen},
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  publisher = {{American Chemical Society}},
  doi = {10.1021/jacs.9b02811},
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}

@article{wang2019a,
  title = {Iridium-{{Catalyzed Enantioselective C}}(Sp3)\textendash{{H Amidation Controlled}} by {{Attractive Noncovalent Interactions}}},
  author = {Wang, Hao and Park, Yoonsu and Bai, Ziqian and Chang, Sukbok and He, Gang and Chen, Gong},
  year = {2019},
  month = apr,
  journal = {J. Am. Chem. Soc.},
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  number = {17},
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  publisher = {{American Chemical Society}},
  doi = {10.1021/jacs.9b02811},
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}

@article{wang2020,
  title = {Will {{Any Crap We Put}} into {{Graphene Increase Its Electrocatalytic Effect}}?},
  author = {Wang, Lu and Sofer, Zdenek and Pumera, Martin},
  year = {2020},
  month = jan,
  journal = {ACS Nano},
  volume = {14},
  number = {1},
  pages = {21--25},
  publisher = {{American Chemical Society}},
  doi = {10.1021/acsnano.9b00184},
  file = {/Users/dasirianni/Zotero/storage/2T7EMQ54/0B9BFFD7-FCFE-4C69-BD21-4AEB96ABA809.pdf}
}

@article{wang2023,
  title = {Predicting {{Biomolecular Binding Kinetics}}: {{A Review}}},
  shorttitle = {Predicting {{Biomolecular Binding Kinetics}}},
  author = {Wang, Jinan and Do, Hung N. and Koirala, Kushal and Miao, Yinglong},
  year = {2023},
  month = mar,
  journal = {J. Chem. Theory Comput.},
  pages = {acs.jctc.2c01085},
  issn = {1549-9618, 1549-9626},
  doi = {10.1021/acs.jctc.2c01085},
  urldate = {2023-04-05},
  abstract = {Biomolecular binding kinetics including the association (kon) and dissociation (koff) rates are critical parameters for therapeutic design of smallmolecule drugs, peptides, and antibodies. Notably, the drug molecule residence time or dissociation rate has been shown to correlate with their efficacies better than binding affinities. A wide range of modeling approaches including quantitative structure-kinetic relationship models, Molecular Dynamics simulations, enhanced sampling, and Machine Learning has been developed to explore biomolecular binding and dissociation mechanisms and predict binding kinetic rates. Here, we review recent advances in computational modeling of biomolecular binding kinetics, with an outlook for future improvements.},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/NG9HELRC/Wang et al. - 2023 - Predicting Biomolecular Binding Kinetics A Review.pdf}
}

@article{wang2023a,
  title = {Predicting {{Biomolecular Binding Kinetics}}: {{A Review}}},
  shorttitle = {Predicting {{Biomolecular Binding Kinetics}}},
  author = {Wang, Jinan and Do, Hung N. and Koirala, Kushal and Miao, Yinglong},
  year = {2023},
  month = apr,
  journal = {J. Chem. Theory Comput.},
  volume = {19},
  number = {8},
  pages = {2135--2148},
  publisher = {{American Chemical Society}},
  issn = {1549-9618},
  doi = {10.1021/acs.jctc.2c01085},
  urldate = {2023-07-06},
  abstract = {Biomolecular binding kinetics including the association (kon) and dissociation (koff) rates are critical parameters for therapeutic design of small-molecule drugs, peptides, and antibodies. Notably, the drug molecule residence time or dissociation rate has been shown to correlate with their efficacies better than binding affinities. A wide range of modeling approaches including quantitative structure-kinetic relationship models, Molecular Dynamics simulations, enhanced sampling, and Machine Learning has been developed to explore biomolecular binding and dissociation mechanisms and predict binding kinetic rates. Here, we review recent advances in computational modeling of biomolecular binding kinetics, with an outlook for future improvements.},
  file = {/Users/dasirianni/Zotero/storage/WIECGEX6/Wang et al. - 2023 - Predicting Biomolecular Binding Kinetics A Review.pdf}
}

@article{warne2011,
  title = {The Structural Basis for Agonist and Partial Agonist Action on a {$B$}1-Adrenergic Receptor},
  author = {Warne, Tony and Moukhametzianov, Rouslan and Baker, Jillian G and Nehm{\'e}, Rony and Edwards, Patricia C and Leslie, Andrew G W and Schertler, Gebhard F X and Tate, Christopher G},
  year = {2011},
  month = jan,
  journal = {Nature},
  volume = {469},
  number = {7329},
  pages = {241--244},
  publisher = {{Nature Publishing Group}},
  doi = {10.1038/nature09746},
  abstract = {Two papers by Brian Kobilka and colleagues describe the X-ray crystal structure of the human {$\beta$}2 adrenergic receptor ({$\beta$}2AR) bound to various agonists. {$\beta$}2AR is a member of the G protein coupled receptor (GPCR) family of membrane-spanning receptors that sense molecules outside the cell and activate internal signalling pathways. With a ubiquitous role in human physiology, GPCRs are prime targets for drug discovery. A third paper by Christopher Tate and his team describes crystal structures of a similar GPCR, the turkey {$\beta$}1-adrenergic receptor ({$\beta$}1AR), bound to full and partial agonists. Together, these new structures reveal the subtle structural changes that accompany agonist binding, showing how binding events inside and outside the cell membrane stabilize the receptor's active state. Agonist binding to {$\beta$}1AR is shown to induce a contraction of the catecholamine-binding pocket relative to the antagonist-bound receptor, and molecular-dynamics simulations of the {$\beta$}2AR agonist complex suggest that the agonist-bound active state spontaneously relaxes to an inactive-like state in the absence of a G protein. Here, the X-ray crystal structure of the {$\beta$}1 adrenergic receptor, a G-protein-coupled receptor, bound to four small molecules that either act as full agonists or partial agonists is solved. The structures show that agonist binding induces a contraction of the catecholamine-binding pocket relative to the antagonist-bound receptor. This work reveals the pharmacological differences between different ligand classes, which should facilitate the structure-based design of new drugs with predictable efficacies. {$\beta$}-adrenergic receptors ({$\beta$}ARs) are G-protein-coupled receptors (GPCRs) that activate intracellular G proteins upon binding catecholamine agonist ligands such as adrenaline and noradrenaline1,2. Synthetic ligands have been developed that either activate or inhibit {$\beta$}ARs for the treatment of asthma, hypertension or cardiac dysfunction. These ligands are classified as either full agonists, partial agonists or antagonists, depending on whether the cellular response is similar to that of the native ligand, reduced or inhibited, respectively. However, the structural basis for these different ligand efficacies is unknown. Here we present four crystal structures of the thermostabilized turkey (Meleagris gallopavo) {$\beta$}1-adrenergic receptor ({$\beta$}1AR-m23) bound to the full agonists carmoterol and isoprenaline and the partial agonists salbutamol and dobutamine. In each case, agonist binding induces a 1 \AA{} contraction of the catecholamine-binding pocket relative to the antagonist bound receptor. Full agonists can form hydrogen bonds with two conserved serine residues in transmembrane helix 5 (Ser5.42 and Ser5.46), but partial agonists only interact with Ser5.42 (superscripts refer to Ballesteros\textendash Weinstein numbering3). The structures provide an understanding of the pharmacological differences between different ligand classes, illuminating how GPCRs function and providing a solid foundation for the structure-based design of novel ligands with predictable efficacies.},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/4WBFL4H4/3D45A54C-2FD8-412F-8FD1-D6000F7912E0.pdf;/Users/dasirianni/Zotero/storage/J2WGWMCD/3D45A54C-2FD8-412F-8FD1-D6000F7912E0.pdf}
}

@article{warne2011a,
  title = {The Structural Basis for Agonist and Partial Agonist Action on a {$B$}1-Adrenergic Receptor},
  author = {Warne, Tony and Moukhametzianov, Rouslan and Baker, Jillian G and Nehm{\'e}, Rony and Edwards, Patricia C and Leslie, Andrew G W and Schertler, Gebhard F X and Tate, Christopher G},
  year = {2011},
  month = jan,
  journal = {Nature},
  volume = {469},
  number = {7329},
  pages = {241--244},
  publisher = {{Nature Publishing Group}},
  doi = {10.1038/nature09746},
  abstract = {Nature 469, 241 (2011). doi:10.1038/nature09746},
  file = {/Users/dasirianni/Zotero/storage/2TZFUH79/6015FDD9-8AD9-49B6-9E8A-D8AA907D0EF4.pdf}
}

@article{warne2011b,
  title = {The Structural Basis for Agonist and Partial Agonist Action on a {$B$}1-Adrenergic Receptor},
  author = {Warne, Tony and Moukhametzianov, Rouslan and Baker, Jillian G and Nehm{\'e}, Rony and Edwards, Patricia C and Leslie, Andrew G W and Schertler, Gebhard F X and Tate, Christopher G},
  year = {2011},
  month = jan,
  journal = {Nature},
  volume = {469},
  number = {7329},
  pages = {241--244},
  doi = {10.1038/nature09746},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/6H357TDY/276CFECA-6882-48F5-A7F9-D40A001B9A8C.pdf}
}

@article{warne2019,
  title = {Molecular Basis for High-Affinity Agonist Binding in {{GPCRs}}},
  author = {Warne, Tony and Edwards, Patricia C and Dor{\'e}, Andrew S and Leslie, Andrew G W and Tate, Christopher G},
  year = {2019},
  journal = {Science},
  volume = {364},
  pages = {775--778},
  file = {/Users/dasirianni/Zotero/storage/NIUDJS4E/AFBEA812-2B98-4875-9007-AF52B3A236A1.pdf}
}

@article{warne2019a,
  title = {Molecular Basis for High-Affinity Agonist Binding in {{GPCRs}}},
  author = {Warne, Tony and Edwards, Patricia C and Dor{\'e}, Andrew S and Leslie, Andrew G W and Tate, Christopher G},
  year = {2019},
  month = may,
  journal = {Science},
  volume = {364},
  pages = {775--778},
  file = {/Users/dasirianni/Zotero/storage/4GNFXT36/A25BBBE5-C542-457C-A942-28B4702C80F1.pdf}
}

@article{warne2019b,
  title = {Molecular Basis for High-Affinity Agonist Binding in {{GPCRs}}},
  author = {Warne, Tony and Edwards, Patricia C and Dor{\'e}, Andrew S and Leslie, Andrew G W and Tate, Christopher G},
  year = {2019},
  month = may,
  journal = {Science},
  volume = {364},
  number = {6442},
  pages = {775--778},
  file = {/Users/dasirianni/Zotero/storage/KVWJNAQI/847D32EC-81D9-451C-BBAF-C187CF1295A8.pdf}
}

@article{weigend2002,
  title = {A Fully Direct {{RI-HF}} Algorithm: {{Implementation}}, Optimised Auxiliary Basis Sets, Demonstration of Accuracy and Efficiency},
  author = {Weigend, Florian},
  year = {2002},
  month = aug,
  journal = {Phys. Chem. Chem. Phys.},
  volume = {4},
  number = {18},
  pages = {4285--4291},
  doi = {10.1039/b204199p},
  file = {/Users/dasirianni/Zotero/storage/8N3ZURM2/03FEB80C-35A0-4A41-8D44-A6877615211D.pdf}
}

@article{weigend2005,
  title = {Balanced Basis Sets of Split Valence, Triple Zeta Valence and Quadruple Zeta Valence Quality for {{H}} to {{Rn}}: {{Design}} and Assessment of Accuracy},
  author = {Weigend, Florian and Ahlrichs, Reinhart},
  year = {2005},
  journal = {Phys. Chem. Chem. Phys.},
  volume = {7},
  number = {18},
  pages = {3297--3305},
  publisher = {{The Royal Society of Chemistry}},
  doi = {10.1039/B508541A},
  abstract = {Gaussian basis sets of quadruple zeta valence quality for Rb\textendash Rn are presented, as well as bases of split valence and triple zeta valence quality for H\textendash Rn. The latter were obtained by (partly) modifying bases developed previously. A large set of more than 300 molecules representing (nearly) all elements\textemdash except lanthanides\textemdash in their common oxidation states was used to assess the quality of the bases all across the periodic table. Quantities investigated were atomization energies, dipole moments and structure parameters for Hartree\textendash Fock, density functional theory and correlated methods, for which we had chosen M\o ller\textendash Plesset perturbation theory as an example. Finally recommendations are given which type of basis set is used best for a certain level of theory and a desired quality of results.},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/V2WG2V39/Phys. Chem. Chem. Phys. 2005 Weigend.pdf}
}

@article{wellawatte2023,
  title = {A {{Perspective}} on {{Explanations}} of {{Molecular Prediction Models}}},
  author = {Wellawatte, Geemi P. and Gandhi, Heta A. and Seshadri, Aditi and White, Andrew D.},
  year = {2023},
  month = apr,
  journal = {J. Chem. Theory Comput.},
  volume = {19},
  number = {8},
  pages = {2149--2160},
  publisher = {{American Chemical Society}},
  issn = {1549-9618},
  doi = {10.1021/acs.jctc.2c01235},
  urldate = {2023-07-06},
  abstract = {Chemists can be skeptical in using deep learning (DL) in decision making, due to the lack of interpretability in ``black-box'' models. Explainable artificial intelligence (XAI) is a branch of artificial intelligence (AI) which addresses this drawback by providing tools to interpret DL models and their predictions. We review the principles of XAI in the domain of chemistry and emerging methods for creating and evaluating explanations. Then, we focus on methods developed by our group and their applications in predicting solubility, blood\textendash brain barrier permeability, and the scent of molecules. We show that XAI methods like chemical counterfactuals and descriptor explanations can explain DL predictions while giving insight into structure\textendash property relationships. Finally, we discuss how a two-step process of developing a black-box model and explaining predictions can uncover structure\textendash property relationships.},
  file = {/Users/dasirianni/Zotero/storage/GVU9NV64/Wellawatte et al. - 2023 - A Perspective on Explanations of Molecular Predict.pdf;/Users/dasirianni/Zotero/storage/A3IC48EX/acs.jctc.html}
}

@article{wellendorff2012,
  title = {Density Functionals for Surface Science: {{Exchange-correlation}} Model Development with {{Bayesian}} Error Estimation},
  author = {Wellendorff, Jess and Lundgaard, Keld T and M{\o}gelh{\o}j, Andreas and Petzold, Vivien and Landis, David D and N{\o}rskov, Jens K and Bligaard, Thomas and Jacobsen, Karsten W},
  year = {2012},
  month = jun,
  journal = {Phys. Rev. B.},
  volume = {85},
  number = {23},
  pages = {235149--16},
  publisher = {{American Physical Society}},
  doi = {10.1103/PhysRevB.85.235149},
  abstract = {A methodology for semiempirical density functional optimization, using regularization and cross-validation methods from machine learning, is developed. We demonstrate that such methods enable well-behaved exchange-correlation approximations in very flexible model spaces, thus avoiding the overfitting found when standard least-squares methods are applied to high-order polynomial expansions. A general-purpose density functional for surface science and catalysis studies should accurately describe bond breaking and formation in chemistry, solid state physics, and surface chemistry, and should preferably also include van der Waals dispersion interactions. Such a functional necessarily compromises between describing fundamentally different types of interactions, making transferability of the density functional approximation a key issue. We investigate this trade-off between describing the energetics of intramolecular and intermolecular, bulk solid, and surface chemical bonding, and the developed optimization method explicitly handles making the compromise based on the directions in model space favored by different materials properties. The approach is applied to designing the Bayesian error estimation functional with van der Waals correlation (BEEF\textbackslash char21vdW), a semilocal approximation with an additional nonlocal correlation term. Furthermore, an ensemble of functionals around BEEF\textbackslash char21vdW comes out naturally, offering an estimate of the computational error. An extensive assessment on a range of data sets validates the applicability of BEEF\textbackslash char21vdW to studies in chemistry and condensed matter physics. Applications of the approximation and its Bayesian ensemble error estimate to two intricate surface science problems support this.},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/JTD4ECKZ/FB409958-59AF-48C8-859E-6FF4C509A881.pdf;/Users/dasirianni/Zotero/storage/L2A96WPV/FB409958-59AF-48C8-859E-6FF4C509A881.pdf}
}

@article{wenthold1994,
  title = {Biradical {{Thermochemistry}} from {{Collision-Induced Dissociation Threshold Energy Measurements}}. {{Absolute Heats}} of {{Formation}} of Ortho-, Meta-, and Para-{{Benzyne}}},
  author = {Wenthold, Paul G. and Squires, Robert R.},
  year = {1994},
  month = jul,
  journal = {J. Am. Chem. Soc.},
  volume = {116},
  number = {14},
  pages = {6401--6412},
  issn = {0002-7863, 1520-5126},
  doi = {10.1021/ja00093a047},
  urldate = {2022-04-08},
  abstract = {The absolute heats of formation of 1,2-, 1,3-, and 1,4-dehydrobenzene (ortho-, meta-, and para-benzyne) have been determined from measurements of the threshold energies for collision-induced dissociation (CID) of ortho-, meta-, and para-chlorophenyl anions in a flowing afterglow-triple quadrupole apparatus. The 298 K heats of formation for ortho-, meta-, and para-benzyne derived in this manner are 106.6 {$\pm$} 3.0, 122.0 {$\pm$} 3.1, and 137.3 {$\pm$} 3.3 kcal/mol, respectively. The values for meta- and para-benzyne are higher than those reported previously (Wenthold, P. G.; Paulino, J. A.; Squires, R. R., J. Am. Chem. Soc. 1991,113, 7414) but are in excellent agreement with recently reported MCSCF and Cl calculations. Several control experiments are described which demonstrate that the earlier results for meta- and para-benzyne suffered from an acid-catalyzed isomerization of the reactant chlorophenyl anions in the flowing afterglow prior to CID threshold analysis. It is shown that CID threshold measurements with chlorophenyl-c/* anions are necessary in order to obtain the correct dissociation energies for the isomerically pure species. The gas-phase acidities of the meta and para positions of chlorobenzene were determined at 298 K using the silane cleavage method to be 391.1 {$\pm$} 2.0 and 393.9 {$\pm$} 2.0 kcal/mol, respectively. The heats of formation for the benzynes determined in this study are used to derive the gas-phase acidity of the 2-position of mefo-benzyne (365 {$\pm$} 3 kcal/mol) and the ortho, meta, and para C-H bond strengths in phenyl radical (79.9 {$\pm$}3.1,95.3 {$\pm$} 3.2, and 110.6 {$\pm$} 3.4 kcal/mol, respectively). The cycloaromatization of c/\'i-3-hexene-1,5-diyne to para-benzyne (the Bergman cyclization) is calculated to be endothermic by 13 kcal/mol.},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/MGEZVGY2/Wenthold and Squires - 1994 - Biradical Thermochemistry from Collision-Induced D.pdf}
}

@article{wenthold1996,
  title = {O-, m-, and p-{{Benzyne Negative Ions}} in the {{Gas Phase}}:\, {{Synthesis}}, {{Authentication}}, and {{Thermochemistry}}},
  shorttitle = {O-, m-, and p-{{Benzyne Negative Ions}} in the {{Gas Phase}}},
  author = {Wenthold, Paul G. and Hu, Jun and Squires, Robert R.},
  year = {1996},
  month = jan,
  journal = {J. Am. Chem. Soc.},
  volume = {118},
  number = {47},
  pages = {11865--11871},
  publisher = {{American Chemical Society}},
  issn = {0002-7863},
  doi = {10.1021/ja960663+},
  urldate = {2022-04-29},
  abstract = {The isomeric m- and p-benzyne anions have been generated in the gas phase in a flowing afterglow-triple quadrupole instrument from the reactions of molecular fluorine (F2) with m- and p-(trimethylsilyl)phenyl anions. The mechanism of the F2 reaction involves electron transfer from the (trimethylsilyl)phenyl anion to F2, followed by nucleophilic attack on the resulting (trimethylsilyl)phenyl radical by the nascent F- formed within the intermediate ion/molecule complex. The structures of o-, m-, and p-benzyne anion are unambiguously identified by a classical derivatization scheme wherein the ions are first converted to the corresponding o-, m-, and p-nitrobenzoates by stepwise addition of CO2 and NO2. These derivatives are then identified by forming proton-bound dimers of each ion with CHF2CO2H, and comparing the O2NC6H4CO2-/CHF2CO2- yield ratios obtained by collision-induced dissociation (CID) with those obtained from analogous experiments with the authentic nitrobenzoate ions. Estimates of the electron affinities of m- and p-benzyne have been determined by the kinetic method. Adducts of SO2 with phenide ion and each of the isomeric benzyne anions are formed that produce measurable yields of SO2\textbullet - and the corresponding C6Hn- ion upon CID. A calibration relation is derived between the CID yield ratios obtained for the C6H5SO2- and o-C6H4SO2\textbullet - adducts and the known electron affinities of phenyl radical (25.3 {$\pm$} 0.1 kcal/mol) and o-benzyne (12.9 {$\pm$} 0.2 kcal/mol). The measured CID ratios for the m- and p-benzyne SO2 adducts are then combined with this relation to obtain EA(m-benzyne) = 19.5 {$\pm$} 0.3 kcal/mol and EA(p-benzyne) = 28.8 {$\pm$} 0.5 kcal/mol. These data are used to derive the following gas-phase acidities for the different ring positions of phenyl radical and the corresponding C-H bond strengths for the phenide ion ({$\Delta$}Hacid(C6H5), DH298[C6H4--H], kcal/mol):\, ortho 378.2 {$\pm$} 3.1, 93.7 {$\pm$} 3.1; meta 386.9 {$\pm$} 3.1, 102.4 {$\pm$} 3.1; para 393.5 {$\pm$} 2.9, 109.0 {$\pm$} 2.9.},
  file = {/Users/dasirianni/Zotero/storage/7MAGE96Q/Wenthold et al. - 1996 - o-, m-, and p-Benzyne Negative Ions in the Gas Pha.pdf;/Users/dasirianni/Zotero/storage/FQFJLP8D/ja960663+.html}
}

@article{werner1980,
  title = {A Quadratically Convergent Multiconfiguration\textendash Self-Consistent Field Method with Simultaneous Optimization of Orbitals and {{CI}} Coefficients},
  author = {Werner, Hans-Joachim and Meyer, Wilfried},
  year = {1980},
  journal = {J. Chem. Phys.},
  volume = {73},
  number = {5},
  pages = {2342},
  doi = {10.1063/1.440384},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/7RU854LF/J. Chem. Phys. 1980 Werner.pdf}
}

@article{werner1981,
  title = {A Quadratically Convergent {{MCSCF}} Method for the Simultaneous Optimization of Several States},
  author = {Werner, Hans-Joachim},
  year = {1981},
  journal = {J. Chem. Phys.},
  volume = {74},
  number = {10},
  pages = {5794},
  doi = {10.1063/1.440892},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/64EV3A2Y/J. Chem. Phys. 1981 Werner.pdf}
}

@article{werner1985,
  title = {A Second Order Multiconfiguration {{SCF}} Procedure with Optimum Convergence},
  author = {Werner, Hans-Joachim and Knowles, Peter J},
  year = {1985},
  journal = {J. Chem. Phys.},
  volume = {82},
  number = {11},
  pages = {5053},
  doi = {10.1063/1.448627},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/2EZGGQWG/J. Chem. Phys. 1985 Werner.pdf}
}

@article{werner2003,
  title = {Fast Linear Scaling Second-Order {{M\o ller-Plesset}} Perturbation Theory ({{MP2}}) Using Local and Density Fitting Approximations},
  author = {Werner, Hans-Joachim and Manby, Frederick R and Knowles, Peter J},
  year = {2003},
  journal = {J. Chem. Phys.},
  volume = {118},
  number = {18},
  pages = {8149--8160},
  doi = {10.1063/1.1564816},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/BMH6RNH5/J. Chem. Phys. 2003 Werner.pdf;/Users/dasirianni/Zotero/storage/G44ZA8WQ/J. Chem. Phys. 2003 Werner.pdf}
}

@article{werner2007,
  title = {General Orbital Invariant {{MP2-F12}} Theory},
  author = {Werner, Hans-Joachim and Adler, Thomas B and Manby, Frederick R},
  year = {2007},
  journal = {J. Chem. Phys.},
  volume = {126},
  number = {16},
  pages = {164102},
  doi = {10.1063/1.2712434},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/PVLY4SJE/J. Chem. Phys. 2007 Werner.pdf;/Users/dasirianni/Zotero/storage/T2N4SCDD/J. Chem. Phys. 2007 Werner.pdf}
}

@article{white1992,
  title = {Density {{Matrix Formulation}} for {{Quantum Renormalization Groups}}},
  author = {White, Steven R},
  year = {1992},
  journal = {Phys. Rev. Lett.},
  volume = {69},
  pages = {2863--2866},
  abstract = {A generalization of the numerical renormalization-group procedure used first by Wilson for the Kondo problem is presented. It is shown that this formulation is optimal in a certain sense. As a demonstration of the effectiveness of this approach, results from numerical real-space renormalization-group calculations for Heisenberg chains are presented.},
  file = {/Users/dasirianni/Zotero/storage/9HTI3IXB/02BE742B-6704-41B3-8127-774398FA45FC.pdf}
}

@article{white1993,
  title = {Density-Matrix Algorithms for Quantum Renormalilzation Groups},
  author = {White, Steven R},
  year = {1993},
  journal = {Phys. Rev. B.},
  volume = {48},
  pages = {10345},
  abstract = {A formulation of numerical real space renormalization groups for quantum many-body problems is presented and several algorithms utilizing this formulation are outlined. The methods are presented and demonstrated using S = 1/2 and S = 1 Heisenberg chains as test cases. The key idea of the formulation is that rather than keep the lowest-lying eigenstates of the Hamiltonian in forming a new effective Hamiltonian of a block of sites, one should keep the most significant eigenstates of the block density matrix, obtained from diagonalizing the Hamiltonian of a larger section of the lattice which includes the block. This approach is much more accurate than the standard approach; for example, energies for the S = 1 Heisenberg chain can be obtained to an accuracy of at least 10 The method can be applied to almost any one-dimensional quantum lattice system, and can provide a wide variety of static properties.},
  file = {/Users/dasirianni/Zotero/storage/6SYCUDED/F8D06755-F7A5-49F7-99CC-B013D3CCE451.pdf}
}

@article{whitten1973,
  title = {Coulombic Potential Energy Integrals and Approximations},
  author = {Whitten, J L},
  year = {1973},
  journal = {J. Chem. Phys.},
  volume = {58},
  number = {10},
  pages = {4496--7},
  doi = {10.1063/1.1679012},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/WQWJHIJU/336E432E-2339-464D-A615-BCDFABC1B8EF.pdf}
}

@article{whitten2017,
  title = {Electron Correlation by Polarization of Interacting Densities},
  author = {Whitten, Jerry L},
  year = {2017},
  month = feb,
  journal = {J. Chem. Phys.},
  volume = {146},
  number = {6},
  pages = {064113--11},
  doi = {10.1063/1.4975329},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/IU2CCVMH/9EAC89FA-28C1-445A-B08C-F3E4D3DDB27F.pdf}
}

@article{willow2013,
  title = {Convergence {{Acceleration}} of {{Parallel Monte Carlo Second-Order Many-Body Perturbation Calculations Using Redundant Walkers}}},
  author = {Willow, Soohaeng Yoo and Hermes, Matthew R and Kim, Kwang S and Hirata, So},
  year = {2013},
  month = oct,
  journal = {J. Chem. Theory Comput.},
  volume = {9},
  number = {10},
  pages = {4396--4402},
  doi = {10.1021/ct400557z},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/9UEBD7ID/J. Chem. Theory Comput. 2013 Willow.pdf;/Users/dasirianni/Zotero/storage/JYUZQ9Y8/J. Chem. Theory Comput. 2013 Willow.pdf}
}

@article{willow2014,
  title = {Communication: {{Stochastic}} Evaluation of Explicitly Correlated Second-Order Many-Body Perturbation Energy},
  author = {Willow, Soohaeng Yoo and Zhang, Jinmei and Valeev, Edward F and Hirata, So},
  year = {2014},
  journal = {J. Chem. Phys.},
  volume = {140},
  pages = {031101},
  doi = {10.1063/1.4862255},
  abstract = {(1) For a closed-shell molecule, the latter is given as (2). with (3). (4). (5). where is a geminal amplitude, f 12 is the correlation factor, which is an explicit function of the electron-electron distance r 12, and is the Fock operator of the nth electron. ...},
  file = {/Users/dasirianni/Zotero/storage/7DJNEMCS/J. Chem. Phys. 2014 Willow.pdf}
}

@article{willow2016,
  title = {Why {{Is MP2-Water}} ``{{Cooler}}'' and ``{{Denser}}'' than {{DFT-Water}}?},
  author = {Willow, Soohaeng Yoo and Zeng, Xiao Cheng and Xantheas, Sotiris S and Kim, Kwang S and Hirata, So},
  year = {2016},
  month = feb,
  journal = {J. Phys. Chem. Lett.},
  pages = {680--684},
  doi = {10.1021/acs.jpclett.5b02430},
  langid = {english},
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}

@book{wilson1980,
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}

@book{wilson2007,
  title = {Electron {{Correlation Methodology}}},
  editor = {Wilson, Angela K. and Peterson, Kirk A.},
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  urldate = {2022-02-21},
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}

@book{wilson2008,
  title = {Progress in {{Theoretical Chemistry}} and {{Physics}}},
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}

@article{witte2014,
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@article{woodward1965,
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@article{wright2013,
  title = {Essential Concepts and Underlying Theories from Physics, Chemistry, and Mathematics for ``Biochemistry and Molecular Biology'' Majors},
  author = {Wright, Ann and Provost, Joseph and {Roecklein-Canfield}, Jennifer A. and Bell, Ellis},
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  doi = {10.1002/bmb.20728},
  urldate = {2022-07-18},
  abstract = {Over the past two years, through an NSF RCN UBE grant, the ASBMB has held regional workshops for faculty members from around the country. The workshops have focused on developing lists of Core Principles or Foundational Concepts in Biochemistry and Molecular Biology, a list of foundational skills, and foundational concepts from Physics, Chemistry, and Mathematics that all Biochemistry or Molecular Biology majors must understand to complete their major coursework. The allied fields working group created a survey to validate foundational concepts from Physics, Chemistry, and Mathematics identified from participant feedback at various workshops. One-hundred twenty participants responded to the survey and 68\% of the respondents answered yes to the question: ``We have identified the following as the core concepts and underlying theories from Physics, Chemistry, and Mathematics that Biochemistry majors or Molecular Biology majors need to understand after they complete their major courses: 1) mechanical concepts from Physics, 2) energy and thermodynamic concepts from Physics, 3) critical concepts of structure from chemistry, 4) critical concepts of reactions from Chemistry, and 5) essential Mathematics. In your opinion, is the above list complete?'' Respondents also delineated subcategories they felt should be included in these broad categories. From the results of the survey and this analysis the allied fields working group constructed a consensus list of allied fields concepts, which will help inform Biochemistry and Molecular Biology educators when considering the ASBMB recommended curriculum for Biochemistry or Molecular Biology majors and in the development of appropriate assessment tools to gauge student understanding of how these concepts relate to biochemistry and molecular biology. \textcopyright{} 2013 by The International Union of Biochemistry and Molecular Biology, 41(5):302\textendash 308, 2013},
  langid = {english},
  keywords = {assessment and the design of probes for student understanding and learning,assessment of educational activities,curriculum assessment},
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}

@article{xu2019,
  title = {Resonance Promoted Ring-Opening Metathesis Polymerization of Twisted Amides},
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  publisher = {{Royal Society of Chemistry}},
  doi = {10.1039/C9SC03602D},
  abstract = {Chemical Science (2019), 00, 1-6, doi:10.1039/C9SC03602D},
  langid = {english},
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}

@article{yamanaka2006,
  title = {Multireference Density Functional Theory with Orbital-Dependent Correlation Corrections},
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}

@article{yanai2009,
  title = {Accelerating Convergence in Iterative Solution for Large-Scale Complete Active Space Self-Consistent-Field Calculations},
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}

@article{yang2006,
  title = {Density-Functional Calculation of Methane Adsorption on Graphite (0001)},
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}

@article{yang2006a,
  title = {Complexometric {{Titration}} of {{Aluminum}} and {{Magnesium Ions}} in {{Commercial Antacids}}. {{An Experiment}} for {{General}} and {{Analytical Chemistry Laboratories}}},
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}

@article{yang2006b,
  title = {Complexometric {{Titration}} of {{Aluminum}} and {{Magnesium Ions}} in {{Commercial Antacids}}. {{An Experiment}} for {{General}} and {{Analytical Chemistry Laboratories}}},
  author = {Yang, Shui-Ping and Tsai, Ruei-Ying},
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}

@article{yang2019,
  title = {Analyzing {{Learned Molecular Representations}} for {{Property Prediction}}},
  author = {Yang, Kevin and Swanson, Kyle and Jin, Wengong and Coley, Connor and Eiden, Philipp and Gao, Hua and {Guzman-Perez}, Angel and Hopper, Timothy and Kelley, Brian and Mathea, Miriam and Palmer, Andrew and Settels, Volker and Jaakkola, Tommi and Jensen, Klavs and Barzilay, Regina},
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  issn = {1549-9596},
  doi = {10.1021/acs.jcim.9b00237},
  urldate = {2023-05-22},
  abstract = {Advancements in neural machinery have led to a wide range of algorithmic solutions for molecular property prediction. Two classes of models in particular have yielded promising results: neural networks applied to computed molecular fingerprints or expert-crafted descriptors and graph convolutional neural networks that construct a learned molecular representation by operating on the graph structure of the molecule. However, recent literature has yet to clearly determine which of these two methods is superior when generalizing to new chemical space. Furthermore, prior research has rarely examined these new models in industry research settings in comparison to existing employed models. In this paper, we benchmark models extensively on 19 public and 16 proprietary industrial data sets spanning a wide variety of chemical end points. In addition, we introduce a graph convolutional model that consistently matches or outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary data sets. Our empirical findings indicate that while approaches based on these representations have yet to reach the level of experimental reproducibility, our proposed model nevertheless offers significant improvements over models currently used in industrial workflows.},
  file = {/Users/dasirianni/Zotero/storage/ZMJ9XVW8/Yang et al. - 2019 - Analyzing Learned Molecular Representations for Pr.pdf}
}

@article{yang2019a,
  title = {Analyzing {{Learned Molecular Representations}} for {{Property Prediction}}},
  author = {Yang, Kevin and Swanson, Kyle and Jin, Wengong and Coley, Connor and Eiden, Philipp and Gao, Hua and {Guzman-Perez}, Angel and Hopper, Timothy and Kelley, Brian and Mathea, Miriam and Palmer, Andrew and Settels, Volker and Jaakkola, Tommi and Jensen, Klavs and Barzilay, Regina},
  year = {2019},
  month = aug,
  journal = {J. Chem. Inf. Model.},
  volume = {59},
  number = {8},
  pages = {3370--3388},
  issn = {1549-9596, 1549-960X},
  doi = {10.1021/acs.jcim.9b00237},
  urldate = {2023-05-22},
  abstract = {Advancements in neural machinery have led to a wide range of algorithmic solutions for molecular property prediction. Two classes of models in particular have yielded promising results: neural networks applied to computed molecular fingerprints or expert-crafted descriptors and graph convolutional neural networks that construct a learned molecular representation by operating on the graph structure of the molecule. However, recent literature has yet to clearly determine which of these two methods is superior when generalizing to new chemical space. Furthermore, prior research has rarely examined these new models in industry research settings in comparison to existing employed models. In this paper, we benchmark models extensively on 19 public and 16 proprietary industrial data sets spanning a wide variety of chemical end points. In addition, we introduce a graph convolutional model that consistently matches or outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary data sets. Our empirical findings indicate that while approaches based on these representations have yet to reach the level of experimental reproducibility, our proposed model nevertheless offers significant improvements over models currently used in industrial workflows.},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/2P78W9IK/Yang et al. - 2019 - Analyzing Learned Molecular Representations for Pr.pdf}
}

@article{yim2004,
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}

@article{yu2016,
  title = {Perspective: {{Kohn-Sham}} Density Functional Theory Descending a Staircase},
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}

@article{zarrabi2021,
  title = {Aluminum({{III}}) Porphyrin: {{A}} Unique Building Block for Artificial Photosynthetic Systems},
  shorttitle = {Aluminum({{III}}) Porphyrin},
  author = {Zarrabi, Niloofar and Poddutoori, Prashanth K.},
  year = {2021},
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  journal = {Coordination Chemistry Reviews},
  volume = {429},
  pages = {213561},
  issn = {00108545},
  doi = {10.1016/j.ccr.2020.213561},
  urldate = {2023-02-16},
  abstract = {Despite being the most abundant metal on the Earth, aluminum(III) metal ion centered porphyrin (AlPor, where Por = Porphyrin) derivatives have received much less attention compared to the transition metal porphyrin derivatives. The exceptional dual bonding features, (i) the axial hydroxide readily reacts with carboxylic acid or alcohol and (ii) the Lewis acid Al center forms an adduct with a Lewis base such as pyridine or imidazole, make the AlPor a unique building block for the construction of `axial-bonding' type multicomponent donor\textendash acceptor systems for a variety of applications. Additionally, due to the rich redox chemistry and optical properties, the AlPor can act as either a photosensitizing electron acceptor or electron donor in donor\textendash acceptor systems. Unlike the zinc(II) porphyrin (ZnPor), the AlPor based donor\textendash acceptor provides an axial topology to investigate the sequential photoinduced energy transfer (EnT) and/or electron transfer (ET) processes in perpendicular to the porphyrin ring. This review surveys AlPor based multicomponent donor\textendash acceptor systems designed to mimic the various components of natural photosynthesis to develop an artificial photosynthetic system for tapping solar energy. Additionally, the review examines the photocatalytic behavior of AlPor towards solar fuel production. Finally, we will discuss the similarities and differences between the `axial-bonding' type AlPor and ZnPor systems.},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/NWI4DJ2A/Zarrabi and Poddutoori - 2021 - Aluminum(III) porphyrin A unique building block f.pdf}
}

@article{zhang2006,
  title = {A {{Triplet Mechanism}} for the {{Formation}} of {{Cyclobutane Pyrimidine Dimers}} in {{UV-Irradiated DNA}}},
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}

@article{zhang2009,
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  abstract = {Abstract We develop and validate a density functional , XYG3, based on the adiabatic connection formalism and the G\"orling\textendash Levy coupling-constant perturbation expansion to the second order (PT2). XYG3 is a doubly hybrid functional , containing 3 mixing parameters. It ...},
  langid = {english},
  pmcid = {PMC2664054},
  pmid = {19276116},
  file = {/Users/dasirianni/Zotero/storage/D8EL5CFI/Proc. Natl. Acad. Sci. 2009 Zhang.pdf;/Users/dasirianni/Zotero/storage/G63Z63QY/Proc. Natl. Acad. Sci. 2009 Zhang.pdf}
}

@article{zhang2015,
  title = {Spin-Flip, Tensor Equation-of-Motion Configuration Interaction with a Density-Functional Correction: {{A}} Spin-Complete Method for Exploring Excited-State Potential Energy Surfaces},
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  urldate = {2022-06-09},
  abstract = {We revisit the formalism of the spin-adapted, spin-flip (SA-SF) configuration-interaction singles (CIS) method based on a tensor equation-of-motion formalism that affords proper spin eigenstates without sacrificing single-reference simplicity. Matrix elements for SA-SF-CIS are then modified in a manner similar to collinear spin-flip time-dependent density functional theory (SF-TDDFT), to include a DFT exchange-correlation correction. The performance of this method, which we call SA-SF-DFT, is evaluated numerically and we find that it systematically improves the energies of electronic states that exhibit significant spin contamination within the conventional SF-TDDFT approach. The new method cures the state assignment problem that plagues geometry optimizations and ab initio molecular dynamics simulations using traditional SF-TDDFT, without sacrificing computational efficiency, and furthermore provides correct topology at conical intersections, including those that involve the ground state, unlike conventional TDDFT. As such, SA-SF-DFT appears to be a promising method for generating excited-state potential energy surfaces at DFT cost.}
}

@article{zhang2016,
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}

@article{zhang2018,
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@article{zhao2002,
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  file = {/Users/dasirianni/Zotero/storage/A5W8MQXE/Nanotechnology 2002 Zhao.pdf;/Users/dasirianni/Zotero/storage/GIJMRDEX/Nanotechnology 2002 Zhao.pdf}
}

@article{zhao2006,
  title = {Design of {{Density Functionals}} by {{Combining}} the {{Method}} of {{Constraint Satisfaction}} with {{Parametrization}} for {{Thermochemistry}}, {{Thermochemical Kinetics}}, and {{Noncovalent Interactions}}},
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@article{zhao2008,
  title = {The {{M06}} Suite of Density Functionals for Main Group Thermochemistry, Thermochemical Kinetics, Noncovalent Interactions, Excited States, and Transition Elements: Two New Functionals and Systematic Testing of Four {{M06-class}} Functionals and 12 Other Functionals},
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}

@article{ziegler2008,
  title = {A Revised Electronic {{Hessian}} for Approximate Time-Dependent Density Functional Theory},
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@misc{zotero-1496,
  title = {Levels of Symmetry Adapted Perturbation Theory ({{SAPT}}). {{I}}. {{Efficiency}} and Performance for Interaction Energies: {{The Journal}} of {{Chemical Physics}}: {{Vol}} 140, {{No}} 9},
  urldate = {2022-06-30

license_type: permissive

branch_name: refs/heads/master

extension: bib


text:
},
  howpublished = {https://aip.scitation.org/doi/full/10.1063/1.4867135?mimetype=application\%2Fpdf\&crawler=true}
}

@misc{zotero-1552,
  title = {Aluminum({{III}}) Porphyrin: {{A}} Unique Building Block for Artificial Photosynthetic Systems | {{Elsevier Enhanced Reader}}},
  shorttitle = {Aluminum({{III}}) Porphyrin},
  doi = {10.1016/j.ccr.2020.213561},
  urldate = {2023-02-14},
  howpublished = {https://reader.elsevier.com/reader/sd/pii/S0010854520304628?token=7C1EF19B0BEE504B38500D8CD6C2204C40E78F37F05D86FA70113CF03694D82B970FF974A8C257887BCF8D8577C32590\&originRegion=us-east-1\&originCreation=20230214202353},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/5HEFL4NQ/Aluminum(III) porphyrin A unique building block f.pdf}
}

@misc{zotero-1647,
  title = {Automated {{Transition State Searches}} without {{Evaluating}} the {{Hessian}}},
  doi = {10.1021/ct300659d},
  urldate = {2023-06-13},
  howpublished = {https://pubs.acs.org/doi/epdf/10.1021/ct300659d},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/FHU539AF/ct300659d.html}
}

@misc{zotero-1656,
  title = {Optical Properties of Human Skin, Subcutaneous and Mucous Tissues in the Wavelength Range from 400 to 2000\,Nm - {{IOPscience}}},
  urldate = {2023-06-16},
  howpublished = {https://iopscience.iop.org/article/10.1088/0022-3727/38/15/004}
}

@misc{zotero-1657,
  title = {Optical Properties of Human Skin, Subcutaneous and Mucous Tissues in the Wavelength Range from 400 to 2000\,Nm - {{IOPscience}}},
  urldate = {2023-06-16},
  howpublished = {https://iopscience.iop.org/article/10.1088/0022-3727/38/15/004}
}

@misc{zotero-1662,
  title = {Reliable {{Gas Phase Reaction Rates}} at {{Affordable Cost}} by {{Means}} of the {{Parameter-Free JunChS-F12 Model Chemistry}}},
  doi = {10.1021/acs.jctc.3c00343},
  urldate = {2023-06-28},
  howpublished = {https://pubs.acs.org/doi/epdf/10.1021/acs.jctc.3c00343},
  langid = {english}
}

@misc{zotero-1991,
  title = {{{IJMS}} | {{Free Full-Text}} | {{Polymorphism}} of {{Butyl Ester}} of {{Oleanolic Acid}}\—{{The Dominance}} of {{Dispersive Interactions}} over {{Electrostatic}}},
  urldate = {2023-07-06},
  howpublished = {https://www.mdpi.com/1422-0067/24/7/6572},
  file = {/Users/dasirianni/Zotero/storage/3HM9D9J8/6572.html}
}

@book{zotero-4,
  title = {The {{Stanford Encyclopedia}} of {{Philosophy}}},
  publisher = {{Metaphysics Research Lab, Stanford University}}
}

@book{zotero-592,
  title = {The {{Theory}} of {{Intermolecular Forces}}}
}

@article{zuilhof2018,
  title = {Writing {{Theory}} and {{Modeling Papers}} for {{Langmuir}}: {{The Good}}, the {{Bad}}, and the {{Ugly}}},
  author = {Zuilhof, Han and Yu, Shu-Hong and Sholl, David S},
  year = {2018},
  month = jan,
  journal = {Langmuir},
  volume = {34},
  number = {5},
  pages = {1817--1818},
  doi = {10.1021/acs.langmuir.7b04236},
  langid = {english},
  file = {/Users/dasirianni/Zotero/storage/QCKZGEPE/3735D05D-CEC2-4F92-B19D-69B555B06878.pdf}
}

repository: dsirianni/hiTeX

repo_name: dsirianni/hiTeX


text:
package da

import (
	"github.com/stretchr/testify/assert"
	"testing"
)

func TestBaseDevice_Parameters(t *testing.T) {
	t.Run("HasCapability returns true if capability is found", func(t *testing.T) {
		c := Capability(0x01)

		b := BaseDevice{
			DeviceCapabilities: []Capability{c},
		}

		assert.True(t, b.HasCapability(c))
	})

	t.Run("HasCapability returns false if capability is not found", func(t *testing.T) {
		c := Capability(0x01)

		b := BaseDevice{
			DeviceCapabilities: []Capability{},
		}

		assert.False(t, b.HasCapability(c))
	})
}

repository: ekmixon/da

repo_name: ekmixon/da

extension: go


text:
require recipes-samples/images/rpb-weston-image.bb

CORE_IMAGE_BASE_INSTALL += " \
    libexif \
    chromium-wayland \
    ${@bb.utils.contains('MACHINE_FEATURES', 'optee', 'optee-aes-decryptor ocdmi portmap', '', d)} \
    "

license: MIT

extension: bb


text:
package main

import "fmt"

func merge(nums1 []int, m int, nums2 []int, n int) {
	index1 := m - 1
	index2 := n - 1
	index3 := m + n - 1
	for {
		if index1 < 0 || index2 < 0 {
			break
		}
		if nums1[index1] > nums2[index2] {
			nums1[index3] = nums1[index1]
			index1--
			index3--
		} else {
			nums1[index3] = nums2[index2]
			index2--
			index3--
		}
	}
	for ; index2 >= 0; {
		nums1[index3] = nums2[index2]
		index2--
		index3--
	}
	fmt.Println(nums1)
}

func main() {
	merge([]int{1, 2, 3, 0, 0, 0}, 3, []int{2, 5, 6}, 3)
	merge([]int{0}, 0, []int{1}, 1)
}

repository: xiaoyusilen/leetcode

repo_name: xiaoyusilen/leetcode