A Perovskite Material Screening and Performance Study Based on Asymmetric Convolutional Blocks.

Shumin Ji, Yujie Zhang, Yanyan Huang, Zhongwei Yu, Yong Zhou, Xiaogang Lin

Abstract read

In one paragraph

Article in Materials (Basel, Switzerland), 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

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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

6 authors.

Shumin JiSchool of Physics and Technology, Nantong University, Nantong 226001, China.

Yujie ZhangSchool of Physics and Technology, Nantong University, Nantong 226001, China.

Yanyan HuangSchool of Physics and Technology, Nantong University, Nantong 226001, China.ORCID 0000-0002-2541-4547

Zhongwei YuSchool of Physics and Technology, Nantong University, Nantong 226001, China.

Yong ZhouKey Laboratory of Optoelectronic Technology and System of Ministry of Education, College of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China.ORCID 0000-0002-2925-3912

Xiaogang LinKey Laboratory of Optoelectronic Technology and System of Ministry of Education, College of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China.ORCID 0000-0001-9255-0672

Funding

Natural Science Foundation of Chongging CSTB2022NSCQ-MSX0560Natural Science Foundation of Chongging CSTB2023NSCQ-MSX0231

6 · The paper itself

Abstract

This study introduces an innovative method for identifying high-efficiency perovskite materials using an asymmetric convolution block (ACB). Our approach involves preprocessing extensive data on perovskite oxide materials and developing a precise predictive model. This system is designed to accurately predict key properties such as band gap and stability, thereby eliminating the reliance on traditional feature importance filtering. It exhibited outstanding performance, achieving an accuracy of 96.8% and a recall of 0.998 in classification tasks, and a coefficient of determination (R

Indexed as

asymmetric convolutionperovskiteprediction modelsresidual networks

Identifiers

PMID39124405

DOI10.3390/ma17153741

PMCPMC11313385

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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.