Evidence map›Paper›PMID 39464385›Full record

ReviewFrontiers in chemistry2024

Computational applications for the discovery of novel antiperovskites and chalcogenide perovskites: a review.

Ming Sheng, Suqin Wang, Hui Zhu, Zhuang Liu, Guangtao Zhou

Abstract readReview
In one paragraph

Review in Frontiers in chemistry, 2024. 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

5 authors.

Ming Sheng *College of Engineering, Shandong Xiehe University, Jinan, China.
Suqin Wang *College of Engineering, Shandong Xiehe University, Jinan, China.
Hui ZhuCollege of Engineering, Shandong Xiehe University, Jinan, China.
Zhuang LiuKey Laboratory for Liquid-Solid Structural Evolution and Processing of Materials, Ministry of Education, Shandong University, Jinan, China.
Guangtao ZhouCollege of Engineering, Shandong Xiehe University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel perovskites pertain to newly discovered or less studied variants of the conventional perovskite structure, characterized by distinctive properties and potential for diverse applications such as ferroelectric, optoelectronic, and thermoelectric uses. In recent years, advancements in computational methods have markedly expedited the discovery and design of innovative perovskite materials, leading to numerous pertinent reports. However, there are few reviews that thoroughly elaborate the role of computational methods in studying novel perovskites, particularly for state-of-the-art perovskite categories. This review delves into the computational discovery of novel perovskite materials, with a particular focus on antiperovskites and chalcogenide perovskites. We begin with a discussion on the computational methods applied to evaluate the stability and electronic structure of materials. Next, we highlight how these methods expedite the discovery process, demonstrating how rational simulations contribute to researching novel perovskites with improved performance. Finally, we thoroughly discuss the remaining challenges and future outlooks in this research domain to encourage further investigation. We believe that this review will be highly beneficial both for newcomers to the field and for experienced researchers in computational science who are shifting their focus to novel perovskites.

Indexed as

antiperovskiteschalcogenide perovskitescomputational methodselectronic structureperovskitesstability

Identifiers

PMID39464385
PMCPMC11502337

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Registered trials

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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.