Shuaihua Lu

1.8k citations

28 papers · 1.5k indexed · 1 hit paper · h-index 15

Renewable Energy, Sustainability and the Environment top 5%
- Electrocatalysts for Energy Conversion 5
- CO2 Reduction Techniques and Catalysts 4
Materials Chemistry top 5%
- Machine Learning in Materials Science 14
- 2D Materials and Applications 4
- Electronic and Structural Properties of Oxides 4
- X-ray Diffraction in Crystallography 4
Catalysis top 5%
Electrical and Electronic Engineering top 10%
- Perovskite Materials and Applications 6
Electrochemistry top 10%
Electronic, Optical and Magnetic Materials
- Magnetic Properties of Alloys 4

Co-authors: Jinlan Wang Qionghua Zhou Yilv Guo Qiang Li Yixin Ouyang Yilei Wu Chongyi Ling Yehui Zhang
Cited by: Renewable Energy, Sustainability and the Environment Materials Chemistry Catalysis
Journals: Journal of the American Chemical Society (1 paper)Advanced Materials (1 paper)Nature Communications (5 papers)
Partner nations: China Bangladesh Taiwan

In The Last Decade

Shuaihua Lu

27 papers receiving 1.4k citations

Hit Papers

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Peers

Countries citing papers authored by Shuaihua Lu

Since Specialization

Citations

This map shows the geographic impact of Shuaihua Lu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shuaihua Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuaihua Lu more than expected).

Fields of papers citing papers by Shuaihua Lu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shuaihua Lu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shuaihua Lu. The network helps show where Shuaihua Lu may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Shuaihua Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shuaihua Lu Line = papers co-authored together Shuaihua Lu links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Accurate prediction of synthesizability and precursors of 3D crystal structures via large language models Nature Communications ·Zhilong Song,Shuaihua Lu,Ming‐Gang Ju,Qionghua Zhou,Jinlan Wang	2025	3
2	Inverse design of promising electrocatalysts for CO2 reduction via generative models and bird swarm algorithm Nature Communications ·Zhilong Song,Linfeng Fan,Shuaihua Lu,Chongyi Ling,Qionghua Zhou,Jinlan Wang	2025	21
3	Active Learning for Accelerated Discovery of Two-Dimensional Magnetic Topological Materials Chemistry of Materials ·Zhipeng Cao,Shuaihua Lu,Shijun Yuan,Liang Ma,Qionghua Zhou,Jinlan Wang	2025	0
4	Universal machine learning aided synthesis approach of two-dimensional perovskites in a typical laboratory Nature Communications ·Yilei Wu,Changfeng Wang,Ming‐Gang Ju,Qiang‐Qiang Jia,Qionghua Zhou,Shuaihua Lu,Xinying Gao,Yi Zhang,Jinlan Wang	2024	48
5	From bulk effective mass to 2D carrier mobility accurate prediction via adversarial transfer learning Nature Communications ·Xinyu Chen,Shuaihua Lu,Qian Chen,Qionghua Zhou,Jinlan Wang	2024	22
6	Adaptive Design of Alloys for CO₂ Activation and Methanation via Reinforcement Learning Monte Carlo Tree Search Algorithm The Journal of Physical Chemistry Letters ·Zhilong Song,Qionghua Zhou,Shuaihua Lu,Sae Dieb,Chongyi Ling,Jinlan Wang	2023	9
7	How computations accelerate electrocatalyst discovery Chem ·Chongyi Ling,Yu Cui,Shuaihua Lu,Xiaowan Bai,Jinlan Wang	2022	47
8	Accurate energy prediction of large-scale defective two-dimensional materials via deep learning Applied Physics Letters ·Yuxing Ma,Shuaihua Lu,Yehui Zhang,Tingbo Zhang,Qionghua Zhou,Jinlan Wang	2022	5
9	Coexistence of Semiconducting Ferromagnetics and Piezoelectrics down 2D Limit from Non van der Waals Antiferromagnetic LiNbO₃-Type FeTiO₃ The Journal of Physical Chemistry Letters ·Yilv Guo,Yehui Zhang,Shuaihua Lu,Xiwen Zhang,Qionghua Zhou,Shijun Yuan,Jinlan Wang	2022	8
10	A Universal Descriptor for Complicated Interfacial Effects on Electrochemical Reduction Reactions Journal of the American Chemical Society ·Chunjin Ren,Shuaihua Lu,Yilei Wu,Yixin Ouyang,Yehui Zhang,Qiang Li,Chongyi Ling,Jinlan Wang	2022	117
11	Machine learning accelerated search for new double perovskite oxide photocatalysis Acta Physica Sinica ·Xin-Yang Wan,Yehui Zhang,Shuaihua Lu,Yilei Wu,Qionghua Zhou,Jinlan Wang	2022	6
12	Accelerated Discovery of Single‐Atom Catalysts for Nitrogen Fixation via Machine Learning Energy & environment materials ·Sheng Zhang,Shuaihua Lu,Peng Zhang,Jianxiong Tian,Li Shi,Chongyi Ling,Qionghua Zhou,Jinlan Wang	2021	64
13	Accelerated design of promising mixed lead-free double halide organic–inorganic perovskites for photovoltaics using machine learning Nanoscale ·Yilei Wu,Shuaihua Lu,Ming‐Gang Ju,Qionghua Zhou,Jinlan Wang	2021	35
14	Property-Oriented Material Design Based on a Data-Driven Machine Learning Technique The Journal of Physical Chemistry Letters ·Qionghua Zhou,Shuaihua Lu,Yilei Wu,Jinlan Wang	2020	70
15	Coupling a Crystal Graph Multilayer Descriptor to Active Learning for Rapid Discovery of 2D Ferromagnetic Semiconductors/Half‐Metals/Metals Advanced Materials ·Shuaihua Lu,Qionghua Zhou,Yilv Guo,Yehui Zhang,Yilei Wu,Jinlan Wang	2020	109
16	Perspective on theoretical methods and modeling relating to electro-catalysis processes Chemical Communications ·Qiang Li,Yixin Ouyang,Shuaihua Lu,Xiaowan Bai,Yehui Zhang,Li Shi,Chongyi Ling,Jinlan Wang	2020	75
17	Rapid Discovery of Ferroelectric Photovoltaic Perovskites and Material Descriptors via Machine Learning Small Methods ·Shuaihua Lu,Qionghua Zhou,Liang Ma,Yilv Guo,Jinlan Wang	2019	95
18	Magnetism and hybrid improper ferroelectricity in LaMO₃/YMO₃superlattices Physical Chemistry Chemical Physics ·Pengxia Zhou,Shuaihua Lu,Chuanfu Li,Chonggui Zhong,Zhiyun Zhao,Li-Hua Qu,Min Yi,Zhen‐Chao Dong,Na Zhang,Jun‐Ming Liu	2019	7
19	Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learningbreakdown → Nature Communications ·Shuaihua Lu,Qionghua Zhou,Yixin Ouyang,Yilv Guo,Qiang Li,Jinlan Wang	2018	577
20	Magnetic properties of Y2Fe17-M C compounds (M = Ga, Al and Si) Journal of Magnetism and Magnetic Materials ·W.C. Chang,Shuaihua Lu,S.K. Chen,Cheng Yu	1996	1

About Shuaihua Lu

Shuaihua Lu is a scholar working on Renewable Energy, Sustainability and the Environment, Materials Chemistry and Condensed Matter Physics, having authored 28 papers that have together received 1.5k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (14 papers), Perovskite Materials and Applications (6 papers), Electrocatalysts for Energy Conversion (5 papers), Magnetic Properties of Alloys (4 papers), 2D Materials and Applications (4 papers), CO2 Reduction Techniques and Catalysts (4 papers), Electronic and Structural Properties of Oxides (4 papers) and X-ray Diffraction in Crystallography (4 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (404 citations), Materials Chemistry (1.1k citations) and Catalysis (169 citations). Shuaihua Lu has collaborated with scholars based in China, Bangladesh and Taiwan. Frequent co-authors include Jinlan Wang, Qionghua Zhou, Yilv Guo, Qiang Li, Yixin Ouyang, Yilei Wu, Chongyi Ling, Yehui Zhang, Liang Ma and Xiaowan Bai. Their work appears in journals such as Journal of the American Chemical Society, Advanced Materials and Nature Communications.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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