Nature Search

A comprehensive mapping of zeolite–template chemical space

ZeoBind is developed for high-throughput molecule screening in zeolite synthesis. Here 2.3 million organic structure-directing agents are enumerated and predictive models for binding affinity are developed; the screening is experimentally validated for two zeolites.

Mingrou Xie
Daniel Schwalbe-Koda
Rafael Gómez-Bombarelli
Research07 Aug 2025
Nature Computational Science

Volume: 5, P: 661-674
A generative diffusion model for amorphous materials

Kai Yang
Daniel Schwalbe-Koda
ResearchOpen Access10 Dec 2025
npj Computational Materials

Volume: 12, P: 1-10
Model-free estimation of completeness, uncertainties, and outliers in atomistic machine learning using information theory

Dataset analysis or uncertainty quantification (UQ) in atomistic machine learning (ML) often rely on model-based heuristics. Here, the authors present a model-free, information theoretical approach to estimate errors, UQ, and outliers for ML-driven simulations.

Daniel Schwalbe-Koda
Sebastien Hamel
Vincenzo Lordi
ResearchOpen Access29 Apr 2025
Nature Communications

Volume: 16, P: 1-13
Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks

Neural Networks are known to perform poorly outside of their training domain. Here the authors propose an inverse sampling strategy to train neural network potentials enabling to drive atomistic systems towards high-likelihood and high-uncertainty configurations without the need for molecular dynamics simulations.

Daniel Schwalbe-Koda
Aik Rui Tan
Rafael Gómez-Bombarelli
ResearchOpen Access24 Aug 2021
Nature Communications

Volume: 12, P: 1-12
Approaching enzymatic catalysis with zeolites or how to select one reaction mechanism competing with others

Approaching the level of molecular recognition of enzymes with solid catalysts is a challenging goal. Here, the authors present a computational methodology that guides the selection of the most adequate zeolite frameworks for target reactions.

Pau Ferri
Chengeng Li
Avelino Corma
ResearchOpen Access19 May 2023
Nature Communications

Volume: 14, P: 1-13
Downregulation of chemokine receptor 9 facilitates CD4⁺CD8αα⁺ intraepithelial lymphocyte development

Peripheral CD4⁺ T cells can develop into Intestinal intraepithelial lymphocytes (IEL) in the lamina propria. Here the authors characterise how IEL generation from CD4⁺ T cells is regulated and show using scRNA sequencing that Ccr9 is involved in this process through limiting IEL precursor differentiation.

Keiko Ono
Tomohisa Sujino
Takanori Kanai
ResearchOpen Access24 Aug 2023
Nature Communications

Volume: 14, P: 1-15
Deposition of topological silicene, germanene and stanene on graphene-covered SiC substrates

Filipe Matusalem
Daniel S. Koda
Lara K. Teles
ResearchOpen Access16 Nov 2017
Scientific Reports

Volume: 7, P: 1-7
MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices

Tagging live single cells and nuclei with lipid- or cholesterol-modified oligonucleotides enables massive scRNA-seq sample multiplexing, identifies doublets and recovers cells with low RNA content.

Christopher S. McGinnis
David M. Patterson
Zev J. Gartner
Research17 Jun 2019
Nature Methods

Volume: 16, P: 619-626
Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

Data-driven approaches based on high-throughput capabilities and machine learning hold promise in revolutionizing human-centred materials discovery for sustainability and decarbonization. This Review examines the strengths and limitations of different traditional and emerging approaches to demonstrate their inherent connection and highlight the evolving paradigms of materials design.

Jiayu Peng
Daniel Schwalbe-Koda
Yang Shao-Horn
Reviews24 Aug 2022
Nature Reviews Materials

Volume: 7, P: 991-1009
Graph similarity drives zeolite diffusionless transformations and intergrowth

Zeolites are industrially useful catalysts, but their synthesis is poorly understood and many predicted structures remain unsynthesized. Machine learning and graph theory are used respectively to mine the literature on zeolite transformations and to predict similar zeolite pairs that may easily be transformed into each other.

Daniel Schwalbe-Koda
Zach Jensen
Rafael Gómez-Bombarelli
Research07 Oct 2019
Nature Materials

Volume: 18, P: 1177-1181
Thermodynamics and electronic structure of adsorbed and intercalated plumbene in graphene/hexagonal SiC heterostructures

Simone Brozzesi
Paola Gori
Olivia Pulci
ResearchOpen Access05 Feb 2024
Scientific Reports

Volume: 14, P: 1-12
Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning

James Damewood
Daniel Schwalbe-Koda
Rafael Gómez-Bombarelli
ResearchOpen Access08 Apr 2022
npj Computational Materials

Volume: 8, P: 1-10

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