Science China Technological Sciences
Published by Science China Press
ISSN : 1674-7321 eISSN : 1869-1900
Abbreviation : Sci. China Technol. Sci.
Aims & Scope
Science China Technological Sciences, an academic journal cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China, and published by Science China Press, is committed to publishing high-quality, original results in both basic and applied research.
Science China Technological Sciences is published in both print and electronic forms.
It is indexed by Science Citation Index.
Categories of articles: Reviews summarize representative results and achievements in a particular topic or an area, comment on the current state of research, and advise on the research directions.
The author’s own opinion and related discussion is requested.
Research papers report on important original results in all areas of technological sciences.
Brief reports present short reports in a timely manner of the latest important results.
View Aims & ScopeMetrics & Ranking
Impact Factor
| Year | Value |
|---|---|
| 2025 | 4.9 |
| 2024 | 4.40 |
Journal Rank
| Year | Value |
|---|---|
| 2024 | 6542 |
Journal Citation Indicator
| Year | Value |
|---|---|
| 2024 | 4159 |
SJR (SCImago Journal Rank)
| Year | Value |
|---|---|
| 2024 | 0.821 |
Quartile
| Year | Value |
|---|---|
| 2024 | Q1 |
h-index
| Year | Value |
|---|---|
| 2024 | 89 |
Impact Factor Trend
Abstracting & Indexing
Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.
Subjects & Keywords
Journal’s research areas, covering key disciplines and specialized sub-topics in Engineering and Materials Science, designed to support cutting-edge academic discovery.
Most Cited Articles
The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.
-
Pre-trained models for natural language processing: A survey
Citation: 997
Authors: XiPeng, TianXiang, YiGe, YunFan, Ning, XuanJing
-
Convective heat transfer and flow characteristics of Cu-water nanofluid
Citation: 306
Authors: Qiang, Yimin
-
Monocular depth estimation based on deep learning: An overview
Citation: 243
Authors: ChaoQiang, QiYu, ChongZhen, Yang, Feng
-
Preparation of polystyrene spheres in different particle sizes and assembly of the PS colloidal crystals
Citation: 233
Authors: JunFei, YiMin, Qiang
-
Sound absorption performance of natural fibers and their composites
Citation: 217
Authors: WeiDong, Yan
-
Recent studies on mechanical properties of recycled aggregate concrete in China—A review
Citation: 217
Authors: JianZhuang, WenGui, ChiSun
-
State-of-the-art of 3D printing technology of cementitious material—An emerging technique for construction
Citation: 201
Authors: GuoWei, Li, Yang
-
A novel memristive neural network with hidden attractors and its circuitry implementation
Citation: 198
Authors: Viet Thanh, Sajad, Sundarapandian, Christos, Xiong