Evidence map›Paper›PMID 42024646›Full record

ArticleJournal of chemical theory and computation2026

Structure Prediction of Organic/Inorganic Interfaces with Genarris.

Haoran Ni, Kevin Larkin, Wen Wen, Saeed Moayedpour, Rithwik Tom, Imanuel Bier, Derek Dardzinski, Noa Marom

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Who cites it

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

8 authors.

Haoran NiDepartment of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States.
Kevin LarkinDepartment of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States.ORCID 0000-0002-8239-2292
Wen WenDepartment of Chemistry, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States.
Saeed MoayedpourDepartment of Chemistry, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States.
Rithwik TomDepartment of Physics, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States.
Imanuel BierDepartment of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States.ORCID 0000-0003-1084-770X
Derek DardzinskiDepartment of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States.
Noa MaromDepartment of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States.ORCID 0000-0002-1508-1312

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organic/inorganic interfaces perform critical functions in organic electronic devices, and their structure can affect device performance. In addition, interactions with the substrate can promote the growth of otherwise metastable thin-film structures by epitaxial templating. Predicting the structure of organic/inorganic interfaces by computer simulations can aid in the design of interfaces with desirable properties. We present Genarris Interfaces, a structure generator for organic/inorganic interfaces. Genarris Interfaces uses epitaxy matrices to impose commensurism with the substrate. Film structures are generated in all layer groups that are compatible with the substrate symmetry and the requested number of molecules per unit cell. Clustering and down-selection are performed to reduce the number of structures while maintaining the diversity of packing motifs. Finally, relaxation and stability ranking are performed using dispersion-inclusive density functional theory (DFT). We demonstrate the application of Genarris for the interfaces of PTCDA on Ag(111), TCNE on Au(111), and naphthalene on Cu(111). In all cases, we find generated structures that resemble experimental scanning tunneling microscopy (STM) images. The electronic structure agrees well with spectroscopy experiments, where available. We envision Genarris Interfaces being used to predict the structure of organic/inorganic interfaces, to generate initial populations for other structure prediction algorithms, and to generate data sets for training machine learning models.

Identifiers

PMID42024646
PMCPMC13173537

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.