Evidence map›Paper›PMID 37768927›Full record

ArticleThe journal of physical chemistry. A2023

Leveling the Mountain Range of Excited-State Benchmarking through Multistate Density Functional Theory.

Hong Zhu, Ruoqi Zhao, Yangyi Lu, Meiyi Liu, Jun Zhang, Jiali Gao

Open access · greenAbstract read
In one paragraph

Article in The journal of physical chemistry. A, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Excited-State Energy Decomposition Analysis.Annual reports in computational chemistry · 2025
    Article
  2. Article
  3. Multistate Density Functional Theory: Theory, Methods, and Applications.Wiley interdisciplinary reviews. Computational molecular science
    Article
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

6 authors at 3 institutions in 2 countries.

Hong ZhuSchool of Chemical Biology & Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, Guangdong 518055, China.
Ruoqi ZhaoInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, Guangdong 518055, China.
Yangyi LuInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, Guangdong 518055, China.ORCID 0000-0002-1602-1661
Meiyi LiuInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, Guangdong 518055, China.
Jun ZhangInstitute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, Guangdong 518055, China.ORCID 0000-0001-9093-9430
Jiali GaoSchool of Chemical Biology & Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, Guangdong 518055, China.ORCID 0000-0003-0106-7154
Shenzhen Bay Laboratory · CNPeking University · CNUniversity of Minnesota · US

Funding

BIOMOLECULAR INTERACTIONS AND ENZYMATIC PROCESSESR01GM046736 · NIGMS · UNIVERSITY OF MINNESOTA TWIN CITIES · PI JIALI GAO · 1993 to 2026
$6.5M
NIGMS NIH HHS R01 GM046736
6 · The paper itself

Abstract

The performance of multistate density functional theory (MSDFT) with nonorthogonal state interaction (NOSI) is assessed for 100 vertical excitation energies against the theoretical best estimates extracted to the full configuration interaction accuracy on the database developed by Loos et al. in 2018 (Loos2018). Two optimization techniques, namely, block-localized excitation and target state optimization, are examined along with two ways of estimating the transition density functional (TDF) for the correlation energy of the Hamiltonian matrix density functional. The results from the two optimization methods are similar. It was found that MSDFT-NOSI using the spin-multiplet degeneracy constraint for the TDF of spin-coupling interaction, along with the M06-2X functional, yields a root-mean-square error (RMSE) of 0.22 eV, which performs noticeably better than time-dependent density functional theory (DFT) at an RMSE of 0.43 eV using the same functional and basis set on the Loos2018 database. In comparison with wave function theory, NOSI has smaller errors than CIS(D

Identifiers

PMID37768927
PMCPMC12747311
OpenAlexW4387129621

What OpenQuestion holds

Textmetadata
LicenceTDM
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.