Publications by Rubén Laplaza Solanas

SPOCK Tool for Constructing Empirical Volcano Diagrams from Catalytic Data

Anne-Clémence Corminboeuf, Rubén Laplaza Solanas

Volcano plots, stemming from the Sabatier principle, visualize descriptor-performance relationships, allowing rational catalyst design. Manually drawn volcanoes originating from experimental studies are potentially prone to human bias as no guidelines or m ...

2025

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

Anne-Clémence Corminboeuf, Friedrich Eisenbrand, Puck Elisabeth van Gerwen, Ksenia Briling, Rubén Laplaza Solanas, Jan Weinreich

Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

IOP Publishing Ltd2025

Outstanding Reviewers for digital Discovery in 2024

Rubén Laplaza Solanas

We would like to take this opportunity to thank all of Digital Discovery's reviewers for helping to preserve quality and integrity in chemical science literature. We would also like to highlight the Outstanding Reviewers for Digital Discovery in 2024. ...

ROYAL SOC CHEMISTRY2025

A genetic optimization strategy with generality in asymmetric organocatalysis as a primary target

Anne-Clémence Corminboeuf, Puck Elisabeth van Gerwen, Simone Gallarati, Rubén Laplaza Solanas

A catalyst possessing a broad substrate scope, in terms of both turnover and enantioselectivity, is sometimes called "general". Despite their great utility in asymmetric synthesis, truly general catalysts are difficult or expensive to discover via traditio ...

Royal Soc Chemistry2024

Inverse Design of Singlet-Fission Materials with Uncertainty-Controlled Genetic Optimization

Jacob Terence Blaskovits, Rubén Laplaza Solanas

Singlet fission has shown potential for boosting the efficiency of solar cells, but the scarcity of suitable molecular materials hinders its implementation. We introduce an uncertainty-controlled genetic algorithm (ucGA) based on ensemble machine learning ...

Wiley2024

Cost-informed Bayesian reaction optimization †

Anne-Clémence Corminboeuf, Jérôme Waser, Rubén Laplaza Solanas, Alexandre Alain Schöpfer, Jan Weinreich

Bayesian optimization (BO) is an efficient method for solving complex optimization problems, including those in chemical research, where it is gaining significant popularity. Although effective in guiding experimental design, BO does not account for experi ...

Royal Society of Chemistry (RSC)2024

Enantiospecific Synthesis of Planar Chiral Rhodium and Iridium Cyclopentadienyl Complexes: Enabling Streamlined and Computer-Guided Access to Highly Selective Catalysts for Asymmetric C-H Functionalizations

Rosario Scopelliti, Anne-Clémence Corminboeuf, Matthew Wodrich, Nicolai Cramer, Farzaneh Fadaei Tirani, Aragorn Nathan Laverny, Rubén Laplaza Solanas

Chiral cyclopentadienyl (CpX) metal complexes are frequently used in asymmetric catalysis by virtue of their high reactivity and selectivity. Planar-chiral-only rhodium and iridium cyclopentadienyl complexes are particularly promising due to unrestricted c ...

2024

Microkinetic Molecular Volcano Plots for Enhanced Catalyst Selectivity and Activity Predictions

Anne-Clémence Corminboeuf, Matthew Wodrich, Shubhajit Das, Rubén Laplaza Solanas

Molecular volcano plots, which facilitate the rapid prediction of the activity and selectivity of prospective catalysts, have emerged as powerful tools for computational catalysis. Here, we integrate microkinetic modeling into the volcano plot framework to ...

Amer Chemical Soc2024

Overcoming the Pitfalls of Computing Reaction Selectivity from Ensembles of Transition States

Anne-Clémence Corminboeuf, Matthew Wodrich, Rubén Laplaza Solanas

The prediction of reaction selectivity is a challenging task for computational chemistry, not only because many molecules adopt multiple conformations but also due to the exponential relationship between effective activation energies and rate constants. To ...

2024

3DReact: Geometric Deep Learning for Chemical Reactions

Anne-Clémence Corminboeuf, Puck Elisabeth van Gerwen, Ksenia Briling, Rubén Laplaza Solanas, Andreas Krause

Geometric deep learning models, which incorporate the relevant molecular symmetries within the neural network architecture, have considerably improved the accuracy and data efficiency of predictions of molecular properties. Building on this success, we int ...

2024

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

Anne-Clémence Corminboeuf, Matthew Wodrich, Jérôme Waser, Rubén Laplaza Solanas, Alexandre Alain Schöpfer

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 ...

Amer Chemical Soc2024

Assessment of fine-tuned large language models for real-world chemistry and material science applications

Anne-Clémence Corminboeuf, Berend Smit, Kevin Maik Jablonka, Sauradeep Majumdar, Rubén Laplaza Solanas, Beatriz Bueno Mouriño

The current generation of large language models (LLMs) has limited chemical knowledge. Recently, it has been shown that these LLMs can learn and predict chemical properties through fine-tuning. Using natural language to train machine learning models opens ...

ROYAL SOC CHEMISTRY2024

Automated prediction of ground state spin for transition metal complexes

Anne-Clémence Corminboeuf, Yuri Cho, Rubén Laplaza Solanas

Exploiting crystallographic data repositories for large-scale quantum chemical computations requires the rapid and accurate extraction of the molecular structure, charge and spin from the crystallographic information file. Here, we develop a general approa ...

2024

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

Anne-Clémence Corminboeuf, Jacob Terence Blaskovits, Shubhajit Das, Rubén Laplaza Solanas

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, ...

Amer Chemical Soc2024

Data-Driven Discovery of Organic Electronic Materials Enabled by Hybrid Top-Down/Bottom-Up Design

Anne-Clémence Corminboeuf, Sergio Vela Llausi, Jacob Terence Blaskovits, Rubén Laplaza Solanas

The high-throughput exploration and screening of molecules for organic electronics involves either a 'top-down' curation and mining of existing repositories, or a 'bottom-up' assembly of user-defined fragments based on known synthetic templates. Both are t ...

Wiley-V C H Verlag Gmbh2023

Reply to Comment on 'Physics-based representations for machine learning properties of chemical reactions'

Anne-Clémence Corminboeuf, Matthew Wodrich, Puck Elisabeth van Gerwen, Rubén Laplaza Solanas

Recently, we published an article in this journal that explored physics-based representations in combination with kernel models for predicting reaction properties (i.e. TS barrier heights). In an anonymous comment on our contribution, the authors argue, am ...

2023

Genetic Algorithms for the Discovery of Homogeneous Catalysts

Anne-Clémence Corminboeuf, Puck Elisabeth van Gerwen, Simone Gallarati, Rubén Laplaza Solanas, Alexandre Alain Schöpfer

In this account, we discuss the use of genetic algorithms in the inverse design process of homogeneous catalysts for chemical transformations. We describe the main components of evolutionary experiments, specifically the nature of the fitness function to o ...

2023

Toward in silico Catalyst Optimization

Anne-Clémence Corminboeuf, Matthew Wodrich, Nicolai Cramer, Rubén Laplaza Solanas

In this minireview, we overview a computational pipeline developed within the framework of NCCR Catalysis that can be used to successfully reproduce the enantiomeric ratios of homogeneous catalytic reactions. At the core of this pipeline is the SCINE Molas ...

SWISS CHEMICAL SOC2023

OSCAR: an extensive repository of chemically and functionally diverse organocatalysts

Anne-Clémence Corminboeuf, Alberto Fabrizio, Puck Elisabeth van Gerwen, Sergio Vela Llausi, Simone Gallarati, Rubén Laplaza Solanas

The automated construction of datasets has become increasingly relevant in computational chemistry. While transition-metal catalysis has greatly benefitted from bottom-up or top-down strategies for the curation of organometallic complexes libraries, the fi ...

ROYAL SOC CHEMISTRY2022

Genetic Optimization of Homogeneous Catalysts

Anne-Clémence Corminboeuf, Simone Gallarati, Rubén Laplaza Solanas

We present the NaviCatGA package, a versatile genetic algorithm capable of optimizing molecular catalyst structures using well-suited fitness functions to achieve a set of targeted properties. The flexibility and generality of this tool are validated and d ...

2022