High-Throughput Prediction of Exfoliable Non-van der Waals Materials from a Universal Potential

Exfoliation and cleavage create two-dimensional (2D) materials and surfaces with physical and chemical properties distinct from their bulk parents. The rising class of non-van der Waals (non-vdW) 2D materials derived from non-layered crystals provides a fascinating platform, expanding the landscape of low-dimensional materials. Current computational models, however, provide limited guidance: existing descriptors are largely tailored to vdW layered systems. Here, we introduce a general framework predicting crystal cleavage and exfoliable 2D subunits directly from bulk structures. At its core is a universal eXfoliation and Cleavage Potential (XCP) enabling large-scale screening of diverse materials at negligible computational cost. Applying this approach, we obtain 44,030 cleavable surfaces and candidate non-vdW 2D materials from which we investigate - according to our criteria - 2531 likely exfoliable ones using high-throughput density functional theory. A large fraction of these candidates is found to be dynamically and thermodynamically stable, while showing negligible overlap with existing 2D materials databases. Our study thus opens a systematic route to explore and design 2D materials with high chemical and structural diversity.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2026-08-25
DOI
https://doi.org/10.1038/s41467-026-76806-8
Primary Topic
2D Materials and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

High-Throughput Prediction of Exfoliable Non-van der Waals Materials from a Universal Potential

Carsten Timm, Rico Friedrich, Tom Barnowsky
Nature Communications
2D Materials and Applications
article

High-Throughput Prediction of Exfoliable Non-van der Waals Materials from a Universal Potential

Carsten Timm, Rico Friedrich, Tom Barnowsky
article en

Abstract

Exfoliation and cleavage create two-dimensional (2D) materials and surfaces with physical and chemical properties distinct from their bulk parents. The rising class of non-van der Waals (non-vdW) 2D materials derived from non-layered crystals provides a fascinating platform, expanding the landscape of low-dimensional materials. Current computational models, however, provide limited guidance: existing descriptors are largely tailored to vdW layered systems. Here, we introduce a general framework predicting crystal cleavage and exfoliable 2D subunits directly from bulk structures. At its core is a universal eXfoliation and Cleavage Potential (XCP) enabling large-scale screening of diverse materials at negligible computational cost. Applying this approach, we obtain 44,030 cleavable surfaces and candidate non-vdW 2D materials from which we investigate - according to our criteria - 2531 likely exfoliable ones using high-throughput density functional theory. A large fraction of these candidates is found to be dynamically and thermodynamically stable, while showing negligible overlap with existing 2D materials databases. Our study thus opens a systematic route to explore and design 2D materials with high chemical and structural diversity.

Nature CommunicationsVol. 17(1)
Helmholtz-Zentrum Dresden-Rossendorf (DE), Complexity and Topology in Quantum Matter (DE), Technische Universität Dresden (DE)
Deutsche Forschungsgemeinschaft, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf
Openalex Percentile: Top 23%
2D Materials and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.