Ligand-Controlled Phonon Dynamics in CsPbBr

Seungjun Cha, Chen Wang, Victor Fung, Guoxiang Hu

Abstract read

In one paragraph

Article in JACS Au, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Seungjun ChaSchool of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.ORCID https://orcid.org/0009-0003-0129-3458

Chen WangDepartment of Chemistry and Biochemistry, Queens College, City University of New York, New York, New York 11367, United States.ORCID https://orcid.org/0000-0002-4296-6888

Victor FungSchool of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.ORCID https://orcid.org/0000-0002-3347-6983

Guoxiang HuSchool of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.ORCID https://orcid.org/0000-0003-2942-8564

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Halide perovskite nanocrystals are leading candidates for next-generation optoelectronics, yet the role of surface ligands in controlling their phonon dynamics remains poorly understood. These lattice dynamics critically govern energy up-conversion, phonon-assisted anti-Stokes emission, and nonradiative relaxation. Conventional ab initio methods, while accurate, are computationally infeasible for experimentally relevant nanocrystal sizes that require thousands of atoms to capture realistic ligand shells and dynamic disorder. Here, we introduce a machine-learned interatomic potential fine-tuned on small CsPbBr

Indexed as

halide perovskitesmachine learning potentialsmolecular dynamicsnanocrystalsphononssurface ligands

Identifiers

PMID42212078

DOI10.1021/jacsau.6c00434

PMCPMC13213489

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.