Mapping Boryl Radical Properties and Reactivity Using Machine Learning: The B‐Rad and React‐B‐Rad Maps

Angewandte Chemie, vol. 137

Abstract

Abstract Boryl radicals have become indispensable in organic synthesis, yet, translating their complex steric and electronic properties into actionable reactivity insights remains challenging. Herein, we present a comprehensive classification of boryl radicals, including a publicly accessible database of 141 neutral 7e‐4c boryl radicals, each parametrized by a set of electronic and steric features derived from DFT calculations. Unsupervised machine learning ( k‐ means clustering) and dimensionality reduction (PCA/UMAP) condense this high dimensional descriptor space into the “B‐rad map”, capturing trends in sterics and electronics among the resulting five clusters. Global electrophilicity ( ω ) and nucleophilicity (N) indices are overlaid to create a polarity‑annotated guide, while DFT‑computed activation free energies for six benchmark reactions (HAT, radical addition, and XAT for two different substrates) yield the React‑B‑rad maps that directly link intrinsic properties to specific reaction performance. To demonstrate predictive power, supervised machine learning models (random forest) are trained on the descriptors and successfully predict radical reactivity regimes across all reaction types. Overall, this integrated, machine‐learning‐driven platform can serve as both a practical guide for experimental decision‐making and a foundation for data‐driven discovery, paving the way towards rational design and virtual screening of boryl‐radical reagents for diverse synthetic applications.

Authors 7

1. Beatriz Peñín

   Universidad de La Rioja

   Affiliation as printed

   Department of Chemistry Instituto de Investigación Química de la Universidad de La Rioja (IQUR) Universidad de La Rioja Madre de Dios 53 Logroño 26006 Spain

   Both authors contributed equally to this work

2. Nil Sanosa

   Universidad de La Rioja

   Affiliation as printed

   Department of Chemistry Instituto de Investigación Química de la Universidad de La Rioja (IQUR) Universidad de La Rioja Madre de Dios 53 Logroño 26006 Spain

   Both authors contributed equally to this work

3. Cecilia Merino‐Robledillo

   Universidad de La Rioja

   Affiliation as printed

   Department of Chemistry Instituto de Investigación Química de la Universidad de La Rioja (IQUR) Universidad de La Rioja Madre de Dios 53 Logroño 26006 Spain

4. Aimara García‐Camacho

   Universidad de La Rioja

   Affiliation as printed

   Department of Chemistry Instituto de Investigación Química de la Universidad de La Rioja (IQUR) Universidad de La Rioja Madre de Dios 53 Logroño 26006 Spain

5. Diego Sampedro

   Universidad de La Rioja

   Affiliation as printed

   Department of Chemistry Instituto de Investigación Química de la Universidad de La Rioja (IQUR) Universidad de La Rioja Madre de Dios 53 Logroño 26006 Spain

6. Julian A. Hueffel corresponding Aachen Department of Chemistry Institute of Organic Chemistry

   RWTH Aachen University

   Affiliation as printed

   Department of Chemistry Institute of Organic Chemistry RWTH Aachen University Landoltweg 1 52074 Aachen Germany

   Department of Chemistry Institute of Organic Chemistry, RWTH Aachen University, Landoltweg 1, 52074 Aachen, Germany

7. Ignacio Funes‐Ardoiz corresponding

   Universidad de La Rioja

   Affiliation as printed

   Department of Chemistry Instituto de Investigación Química de la Universidad de La Rioja (IQUR) Universidad de La Rioja Madre de Dios 53 Logroño 26006 Spain