Anne-Clémence Corminboeuf

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Chiral ligands are important components in asymmetric homogeneous catalysis, but their synthesis and screening can be both time-consuming and resource-intensive. Data-driven approaches, in contrast to screening procedures based on intuition, have the poten ...

Linear free energy scaling relationships (LFESRs) and volcano plots are routinely used to assess the performance of heterogeneous electrocatalysts and have only recently been concretely exploited in homogeneous catalysis. These tools efficiently compare an ...

The electronic charge density plays a central role in determining the behavior of matter at the atomic scale, but its computational evaluation requires demanding electronic-structure calculations. We introduce an atom-centered, symmetry-adapted framework t ...

The vast chemical space of metal and ligand combinations in Transition Metal Complexes (TMCs) gives rise to a rich variety of electronic excited states with local and non-local character such as intra-ligand (IL), metal-centered (MC), metal-to-ligand (MLCT ...

The creation and maintenance of crystallographic data repositories is one of the greatest data-related achievements in chemistry. Platforms such as the Cambridge Structural Database host what is likely the most diverse collection of synthesizable molecules ...

Here we present a molecular architecture that can reversibly change the geometric conformation of its π-system backbone via irradiation with two different wavelengths. The proposed ‘molecular actuator’ consists of a photoswitchable azobenzene orthogonally ...

Recently, we introduced a class of molecular representations for kernel-based regression methods─the spectrum of approximated Hamiltonian matrices (SPAHM)─that takes advantage of lightweight one-electron Hamiltonians traditionally used as a self-consistent ...

Physics-based representations constructed using only atomic positions and nuclear charges (also known as quantum machine learning, QML) allow for the reliable and efficient inference of molecular properties from training data. Chemistry is a science rooted ...

The trigonal planar geometry of the nitrogen atom in commonly used phosphoramidite ligands is not in line with the traditional valence shell electron pair repulsion (VSEPR) model. In this work, the effects governing nitrogen configuration in several substi ...

Progress in the atomic-scale modeling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomic forces that work by either solving the electronic structure problem explici ...

Group 9 metals, in particular Rh III complexes with cyclopentadienyl ligands, are competent C–H activation catalysts. Recently, a Cp*Rh III catalyzed reaction of alkenes with N -enoxyphthalimides showed divergent outcome based on the solvent, with carboami ...

Structurally and conformationally diverse databases are needed to train accurate neural networks or kernel-based potentials capable of exploring the complex free energy landscape of flexible functional organic molecules. Curating such databases for species ...

Given the computational resources available today, data-driven approaches can propel the next leap forward in catalyst design. Using a data-driven inspired workflow consisting of data generation, statistical analysis, and dimensionality reduction algorithm ...

The two pi-systems of allene can combine into helical molecular orbitals (MOs), yet the helicity is lost in the pi-pi* transitions due to excited state mixing. In spiroconjugated molecules the relative orientation of the two pi-systems is different and con ...

The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of methods has been pr ...

Carbon nanostructures that feature two-dimensional extended nanosheets are important components for technological applications such as high-performance composites, lithium-ion storage, photovoltaics and nanoelectronics. Chemical functionalization would ren ...

Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes. Immobilizing the active Lewis sites to a solid support, especially to porous scaffolds, ...

For the past two decades, linear free energy scaling relationships and volcano plots have seen frequent use as computational tools that aid in understanding and predicting the catalytic behavior of heterogeneous and electrocatalysts. Based on Sabatier's pr ...

Despite recent progress in the chemistry of frustrated Lewis pairs (FLPs), direct FLP-catalyzed hydrogenation of CO2 remains elusive. From a near-infinite array of plausible Lewis pairs, it is challenging to identify individual combinations that are approp ...

Here, a novel deep blue emitter SBABz4 for use in organic light-emitting diodes (OLED) is investigated. The molecular design of the emitter enables thermally activated delayed fluorescence (TADF), which we examine by temperature-dependent time-resolved ele ...

Anne-Clémence Corminboeuf

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Reaction-Agnostic Featurization of Bidentate Ligands for Bayesian Ridge Regression of Enantioselectivity

Exploring the Limitation of Molecular Water Oxidation Catalysts

Transferable Machine-Learning Model of the Electron Density

Optical absorption properties of metal-organic frameworks: solid stateversusmolecular perspective

cell2mol: encoding chemistry to interpret crystallographic data

Photochromic Torsional Switch (PTS): a Light-Driven Actuator for the Dynamic Tuning of π-Conjugation Extension

SPAHM(a,b): Encoding the Density Information from Guess Hamiltonian in Quantum Machine Learning Representations

Physics-based representations for machine learning properties of chemical reactions

What governs nitrogen configuration in substituted aminophosphines?

i-PI 2.0: A universal force engine for advanced molecular simulations

Mapping Catalyst‐Solvent Interplay in Competing Carboamination/Cyclopropanation Reactions

From Organic Fragments to Photoswitchable Catalysts: The OFF-ON Structural Repository for Transferable Kernel-Based Potentials

Data-powered augmented volcano plots for homogeneous catalysis

Helical electronic transitions of spiroconjugated molecules

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

Functional carbon nanosheets prepared from hexayne amphiphile monolayers at room temperature

Engineering Frustrated Lewis Pair Active Sites in Porous Organic Scaffolds for Catalytic CO2 Hydrogenation

The Genesis of Molecular Volcano Plots

Design of Frustrated Lewis Pair Catalysts for Direct Hydrogenation of CO2

Getting the Right Twist: Influence of Donor-Acceptor Dihedral Angle on Exciton Kinetics and Singlet-Triplet Gap in Deep Blue Thermally Activated Delayed Fluorescence Emitter