The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Martin Headgordon - One of the best experts on this subject based on the ideXlab platform.
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revealing the nature of electron correlation in transition metal complexes with symmetry breaking and Chemical Intuition
Journal of Chemical Physics, 2021Co-Authors: James Shee, Matthias Loipersberger, Diptarka Hait, Joonho Lee, Martin HeadgordonAbstract:In this work, we provide a nuanced view of electron correlation in the context of transition metal complexes, reconciling computational characterization via spin and spatial symmetry breaking in single-reference methods with qualitative concepts from ligand-field and molecular orbital theories. These insights provide the tools to reliably diagnose the multi-reference character, and our analysis reveals that while strong (i.e., static) correlation can be found in linear molecules (e.g., diatomics) and weakly bound and antiferromagnetically coupled (monometal-noninnocent ligand or multi-metal) complexes, it is rarely found in the ground-states of mono-transition-metal complexes. This leads to a picture of static correlation that is no more complex for transition metals than it is, e.g., for organic biradicaloids. In contrast, the ability of organometallic species to form more complex interactions, involving both ligand-to-metal σ-donation and metal-to-ligand π-backdonation, places a larger burden on a theory’s treatment of dynamic correlation. We hypothesize that Chemical bonds in which inter-electron pair correlation is non-negligible cannot be adequately described by theories using MP2 correlation energies and indeed find large errors vs experiment for carbonyl-dissociation energies from double-hybrid density functionals. A theory’s description of dynamic correlation (and to a less important extent, delocalization error), which affects relative spin-state energetics and thus spin symmetry breaking, is found to govern the efficacy of its use to diagnose static correlation.
Berend Smit - One of the best experts on this subject based on the ideXlab platform.
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capturing Chemical Intuition in synthesis of metal organic frameworks
Nature Communications, 2019Co-Authors: Seyed Mohamad Moosavi, Arunraj Chidambaram, Leopold Talirz, Maciej Haranczyk, Kyriakos C. Stylianou, Berend SmitAbstract:We report a methodology using machine learning to capture Chemical Intuition from a set of (partially) failed attempts to synthesize a metal-organic framework. We define Chemical Intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the highest surface area reported to date. We illustrate the importance of quantifying this Chemical Intuition for the synthesis of novel materials.
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Capturing Chemical Intuition in synthesis of metal-organic frameworks
Nature Publishing Group, 2019Co-Authors: Seyed Mohamad Moosavi, Arunraj Chidambaram, Leopold Talirz, Maciej Haranczyk, Kyriakos C. Stylianou, Berend SmitAbstract:Synthetic chemists develop a "Chemical Intuition" over years of experience in the lab. Here the authors combine machine learning of (partially) failed experiments with robotic synthesis to capture this Intuition used in searching for the optimal synthesis conditions of metal-organic frameworks
Matthew G. Davidson - One of the best experts on this subject based on the ideXlab platform.
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Automation of route identification and optimisation based on data-mining and Chemical Intuition.
Faraday Discussions, 2017Co-Authors: Alexei A. Lapkin, Philipp-maximilian Jacob, Parminder Kaur Heer, Marc Hutchby, William B. Cunningham, Steven D. Bull, Matthew G. DavidsonAbstract:Data-mining of Reaxys and network analysis of the combined literature and in-house reactions set were used to generate multiple possible reaction routes to convert a bio-waste feedstock, limonene, into a pharmaceutical API, paracetamol. The network analysis of data provides a rich knowledge-base for generation of the initial reaction screening and development programme. Based on the literature and the in-house data, an overall flowsheet for the conversion of limonene to paracetamol was proposed. Each individual reaction–separation step in the sequence was simulated as a combination of the continuous flow and batch steps. The linear model generation methodology allowed us to identify the reaction steps requiring further Chemical optimisation. The generated model can be used for global optimisation and generation of environmental and other performance indicators, such as cost indicators. However, the identified further challenge is to automate model generation to evolve optimal multi-step Chemical routes and optimal process configurations.
Gemma C. Solomon - One of the best experts on this subject based on the ideXlab platform.
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An approach to develop Chemical Intuition for atomistic electron transport calculations using basis set rotations.
The Journal of chemical physics, 2016Co-Authors: Anders Borges, Gemma C. SolomonAbstract:Single molecule conductance measurements are often interpreted through computational modeling, but the complexity of these calculations makes it difficult to directly link them to simpler concepts and models. Previous work has attempted to make this connection using maximally localized Wannier functions and symmetry adapted basis sets, but their use can be ambiguous and non-trivial. Starting from a Hamiltonian and overlap matrix written in a hydrogen-like basis set, we demonstrate a simple approach to obtain a new basis set that is Chemically more intuitive and allows interpretation in terms of simple concepts and models. By diagonalizing the Hamiltonians corresponding to each atom in the molecule, we obtain a basis set that can be partitioned into pseudo-σ and −π and allows partitioning of the Landuaer-Buttiker transmission as well as create simple Huckel models that reproduce the key features of the full calculation. This method provides a link between complex calculations and simple concepts and models to provide Intuition or extract parameters for more complex model systems.
C. Oliver Kappe - One of the best experts on this subject based on the ideXlab platform.
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Anthropogenic reaction parameters-the missing link between Chemical Intuition and the available Chemical space
Chemical Society reviews, 2014Co-Authors: György M. Keserű, Tibor Soós, C. Oliver KappeAbstract:How do skilled synthetic chemists develop good intuitive expertise? Why can we only access such a small amount of the available Chemical space—both in terms of the reactions used and the Chemical scaffolds we make? We argue here that these seemingly unrelated questions have a common root and are strongly interdependent. We performed a comprehensive analysis of organic reaction parameters dating back to 1771 and discovered that there are several anthropogenic factors that limit reaction parameters and thus the scope of synthetic chemistry. Nevertheless, many of the anthropogenic limitations such as narrow parameter space and the opportunity for rapid and clear feedback on the progress of reactions appear to be crucial for the acquisition of valid and reliable Chemical Intuition. In parallel, however, all of these same factors represent limitations for the exploration of available chemistry space and we argue that these are thus at least partly responsible for limited access to new chemistries. We advocate, therefore, that the present anthropogenic boundaries can be expanded by a more conscious exploration of “off-road” chemistry that would also extend the intuitive knowledge of trained chemists.