English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Intermolecular and long-range interactions are central to phenomena asdiverse as gene regulation, topological states of quantum materials,electrolyte transport in batteries, and the universal solvation properties ofwater. We present a set of challenge problems for preserving intermolecularinteractions and structural motifs in machine-learning approaches to chemicalproblems, through the use of a recently published dataset of 4.95 million waterclusters held together by hydrogen bonding interactions and resulting in longerrange structural patterns. The dataset provides spatial coordinates as well astwo types of graph representations, to accommodate a variety ofmachine-learning practices.

HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data