Strategic Study of Chinese Academy of Engineering >
Strategy for Promoting the Basic Capabilities of Frontier New Materials Industry
Received date: 09 Aug 2021
Published date: 26 Apr 2022
In this article, we focus on the current status and problems regarding the basic capabilities of the frontier new materials industry in cutting-edge fields such as brain-like intelligence, artificial intelligence, deep space exploration, network security, and efficient energy conversion. Considering the phased development plans in 2025 and 2035, we propose the development goals and strategies for promoting the basic capabilities of China’s frontier new materials industry in terms of scientific and technological innovation, support, competitiveness, sustainable development, infrastructure construction, and industrial ecological environment. To meet the requirements of the new round of scientific and technological revolution and industrial transformation for frontier new materials, countermeasures and suggestions are proposed from the following aspects: material genetic engineering, double circulation, carbon peak and carbon neutrality, and testing and characterization of independent frontier new materials.
Xuefeng Liu , Changsheng Liu , Jianxin Xie . Strategy for Promoting the Basic Capabilities of Frontier New Materials Industry[J]. Strategic Study of Chinese Academy of Engineering, 2022 , 24(2) : 29 -37 . DOI: 10.15302/J-SSCAE-2022.02.006
[1] |
张学博, 阮梅花, 袁天蔚, 等. 神经科学和类脑人工智能发展: 新 进展、新趋势 [J]. 生命科学, 2020, 32(10): 993–1013. Zhang X B, Ruan M H, Yuan T W, et al. Neuroscience and braininspired artificial intelligence: New progress and trends [J]. Chinese Bulletin of Life Sciences, 2020, 32(10): 993–1013.
|
[2] |
Haefner N, Wincent J, Parida V, et al. Artificial intelligence and innovation management: A review, framework, and research agenda [J]. Technological Forecasting and Social Change, 2021, 162: 1–12.
|
[3] |
解维华, 韩国凯, 孟松鹤, 等. 返回舱/空间探测器热防护结构发 展现状与趋势 [J]. 航空学报, 2019, 40(8): 6–22. Xie W H, Han G K, Meng S H, et al. Development status and trend of thermal protection structure for return capsules and space probes [J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(8): 6–22.
|
[4] |
黄韬, 刘江, 汪硕, 等. 未来网络技术与发展趋势综述 [J]. 通信 学报, 2021, 42(1): 130–150. Huang T, Liu J, Wang S, et al. Survey of the future network technology and trend [J]. Journal on Communications, 2021, 42(1): 130–150.
|
[5] |
Sun C W, Alonso J A, Bian J J. Recent advances in perovskitetype oxides for energy conversion and storage applications [J]. Advanced Energy Materials, 2020, 11(2): 1–21.
|
[6] |
李昂, 刘雪峰, 俞波, 等. 金属增材制造技术的关键因素及发展 方向 [J]. 工程科学学报, 2019, 41(2): 159–173. Li A, Liu X F, Yu B, et al. Key factors and developmental directions with regard to metal additive manufacturing [J]. Chinese Journal of Engineering, 2019, 41(2): 159–173.
|
[7] |
李献军. 大规格纯钛铸锭成分均匀性控制技术 [J]. 金属学报, 2002, 38(z1): 318–319. Li X J. Technology controlling composition homogeneity for large diameter pure Ti-ingot [J]. Acta Metallurgica Sinica, 2002, 38 (z1): 318–319.
|
[8] |
宿彦京, 付华栋, 白洋, 等. 中国材料基因工程研究进展 [J]. 金 属学报, 2020, 56(10): 1313–1323. Su Y J, Fu H D, Bai Y, et al. Progress in materials genome engineering in China [J]. Acta Metallurgica Sinica, 2020, 56(10): 1313–1323.
|
[9] |
王冠杰, 李开旗, 彭力宇, 等. 高通量自动流程集成计算与数据管理智能平台及其在合金设计中的应用 [J]. 金属学报, 2022, 58(1): 75–88. Wang G J, Li K Q, Peng L Y, et al. Development and application of high-throughput automatic integrated calculation and data management intelligent platform in novel alloys [J]. Acta Metallurgica Sinica, 2022, 58(1): 75–88.
|
[10] |
冯金玲. 基于准直面光源的三维显示技术研究 [D]. 上海: 上海 交通大学(硕士学位论文), 2017. Feng J L. Three-dimensional display research based on the collimated light source [D]. Shanghai: Shanghai Jiao Tong University(Master’s thesis), 2017.
|
[11] |
庄存波, 刘检华, 张雷. 工业5.0的内涵、体系架构和使能技术 [J]. 机械工程学报, 2021, 57: 1–13. Zhuang C B, Liu J H, Zhang L. Connotation, architecture and enabling technology of Industrial 5.0 [J]. Journal of Mechanical Engineering, 2021, 57: 1–13.
|
[12] |
宋静思, 曲殿鹏, 陈晋, 等. 真空精密铸造炉的发展与展望 [J]. 真 空, 2018, 55(3): 55–60. Song J S, Qu D P, Chen J, et al. Development and prospect of vacuum precision casting furnace [J]. Vacuum, 2018, 55(3): 55–60.
|
[13] |
王琮. 多线切割机的现状及发展趋势 [J]. 电子工业专用设备, 2008 (11): 10–11. Wang C. Multi wire saw current situation and trend [J]. Equipment for Electronic Products Manufacturing, 2008 (11): 10–11.
|
[14] |
宋颍涛. 轧制设备现状分析与创新 [J]. 中国设备工程, 2019 (18): 2. Song Y T. Analysis and innovation of current rolling equipment [J]. China Plant Engineering, 2019 (18): 2.
|
[15] |
李建勋. 全自动串焊机之工艺分析与结构优化设计 [D]. 南京: 东南大学(硕士学位论文), 2017. Li J X. Progress analysis and structural optimization design of automatic series welding machine [D]. Nanjing: Southeast University(Master’s thesis), 2017.
|
[16] |
于琨山. 精密锻造设备研究现状及发展趋势 [J]. 世界有色金属, 2018 (10): 278–280. Yu K S. Research status and development trend of precision forging equipment [J]. World Nonferrous Metals, 2018 (10): 278– 280.
|
[17] |
朱徐立. 大型定向凝固设备非均匀温度场提纯多晶硅研究 [D]. 厦门: 厦门大学(博士学位论文), 2015. Zhu X L. Research on the non-uniform temperature field for purifying polysilicon in large directional solidification equipment [D]. Xianmen: Xiamen University(Doctoral dissertation), 2015.
|
[18] |
Van de Voorde M. Hydrogen production and energy transition [M]. Berlin: De Gruyter, 2021.
|
[19] |
Pei J, Deng L, Song S, et al. Towards artificial general intelligence with hybrid Tianjic chip architecture [J]. Nature, 2019 (572): 106–111.
|
[20] |
Deng X, Chao A, Feikes J, et al. Experimental demonstration of the mechanism of steady-state microbunching [J]. Nature, 2021 (590): 576–579.
|
[21] |
Olsen S, Zhang J W, Liang K F, et al. An artificial intelligence that increases simulated brain–computer interface performance [J]. Journal of Neural Engineering, 2021, 18(4): 046053.
|
[22] |
刘淦. 基于增材制造的高功率密度液压集成阀块优化设计 [D]. 杭州: 浙江大学(硕士学位论文), 2020. Liu G. Optimal design of high-power-density hydraulic manifolds utilizing additive manufacturing [D]. Hangzhou: Zhejiang University(Master’s thesis), 2020.
|
[23] |
李聪. 复杂工况材料力学性能原位测试装备设计与试验研究 [D]. 长春: 吉林大学(博士学位论文), 2020. Li C. Design and research of in-situ testing equipment for mechanical performance of materials under complex working conditions [D]. Changchun: Jilin University(Doctoral dissertation), 2020.
|
[24] |
代燕. 基于电化学参数分析的便携式恒电位仪系统设计及应用 [D]. 杭州: 杭州电子科技大学(硕士学位论文), 2020. Dai Y. Design and application of portable potentiostat system based on electrochemical parameter analysis [D]. Hangzhou: Hangzhou Dianzi University(Master’s thesis), 2020.
|
[25] |
汪洋堃. 低压交流电弧的动态特性与故障检测方法研究 [D]. 上 海: 上海交通大学(博士学位论文), 2020. Wang Y K. Research on dynamic characteristic and fault diagnostic method for low voltage alternating current [D]. Shanghai: Shanghai Jiao Tong University(Doctoral dissertation), 2020.
|
[26] |
冯霏, 吴访升, 陈鉴富, 等. 光伏阵列伏安特性测试系统设计 [J]. 计算机测量与控制, 2016, 24(10): 39–41. Feng F, Wu F S, Chen J F, et al. Measurement system of photovoltaic volt-ampere characteristic [J]. Computer Measurement & Control, 2016, 24(10): 39–41.
|
[27] |
何玮. 高量子效率可见–短波红外宽光谱InGaAs探测器研究 [D]. 上海: 中国科学院大学(博士学位论文), 2020. He W. Research on the high quantum efficiency broadband VisSWIR In Ga As photodetector [D]. Shanghai: University of Chinese Academy of Sciences(Doctoral dissertation), 2020.
|
[28] |
张学习, 郑忠, 高莹, 等. 金属基复合材料高通量制备及表征技 术研究进展 [J]. 金属学报, 2019, 55(1): 109–125. Zhang X X, Zheng Z, Gao Y, et al. Progress in high throughput fabrication and characterization of metal matrix composites [J]. Acta Metallurgica Sinica, 2019, 55(1): 109–125.
|
[29] |
钱梦翔. 太赫兹近场高通量材料物性测试系统的束流诊断系统 设计 [D]. 合肥: 中国科学技术大学(硕士学位论文), 2020. Qian M X. Design of beam diagnosis system for terahertz nearfield high-flux material property testing system [D]. Hefei: University of Science and Technology of China(Master’s thesis), 2020.
|
[30] |
于川茗, 李林, 蔡毅超. 扫描电镜在电池材料领域的应用 [J]. 电 子显微学报, 2021, 40(3): 339–347. Yu C M, Li L. Cai Y C. The application of scanning electron microscopy in the field of battery materials [J]. Journal of Chinese Electron Microscopy Society, 2021, 40(3): 339–347.
|
[31] |
苏晨. 基于LabVIEW的示波器自动测试系统的设计与实现 [D]. 北京: 北京交通大学 (硕士学位论文), 2018. Su C. Design and implementation of the automatic oscilloscope test system based on LabVIEW [D]. Beijing: Beijing Jiaotong University (Master’s thesis), 2018.
|
[32] |
Baran K, Róowicz A, Wachta H, et al. Thermal analysis of the factors influencing junction temperature of LED panel sources [J]. Energies, 2019, 12(20): 1–12.
|
[33] |
钟万勰, 陆仲绩. CAE: 事关国家竞争力和国家安全的战略技 术——关于发展我国CAE软件产业的思考 [J]. 中国科学院院 刊, 2007, 22(2): 115–119. Zhong W X, Lu Z J. CAE: Technology for National Competitive Power and National Security [J]. Bulletin of Chinese Academy of Sciences, 2007, 22(2): 115–119.
|
[34] |
Turkmen A, Yesil Y, Kayar M. Heuristic production line balancing problem solution with MATLAB software programming [J]. International Journal of Clothing Science and Technology, 2016, 28(6): 750–779.
|
[35] |
Markiewicz T. Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology [J]. Diagnostic pathology, 2011, 6(S1): 1–12.
|
[36] |
Modeste K N, Andrianaharison Y, Omer K, et al. Impact of climate change on demands for heating and cooling energy in hospitals: An in-depth case study of six islands located in the Indian Ocean region [J]. Sustainable Cities and Society, 2019, 44: 629–645.
|
[37] |
Belmahdi B, Bouardi A E. Solar potential assessment using PVsyst software in the Northern Zone of Morocco [J]. Procedia Manufacturing, 2020, 46: 738–745.
|
[38] |
Husain A A F, Phesal M H A, Ab Kadir M Z A, et al. Technoeconomic analysis of commercial size grid-connected rooftop solar PV systems in Malaysia under the NEM 3.0 scheme [J]. Applied Sciences, 2021, 11(21): 10118.
|
[39] |
陆雄建. 考虑电池寿命的增程式电动汽车参数匹配与能量管理 研究 [D]. 长沙: 湖南大学(硕士学位论文), 2018. Lu X J. Parameter matching and energy management of extended range electric vehicle considering battery life [D]. Changsha: Hunan University(Master’s thesis), 2018.
|
[40] |
罗树林. 基于高通量计算与机器学习的材料设计方法与软件的 开发与应用 [D]. 长春: 吉林大学(博士学位论文), 2021. Luo S L. The developments and applications of the highthroughput computational methods and toolkits combining with machine learning for materials design [D]. Changchun: Jilin University(Doctoral dissertation), 2021.
|
[41] |
Wimmer E, Christensen M, Eyert V, et al. Computational materials engineering: Recent applications of VASP in the medeA® software environment [J]. Journal of the Korean Ceramic Society, 2016, 53(3): 263–272.
|
[42] |
Altalhi A H, Luna J M, Vallejo M A, et al. Evaluation and comparison of open source software suites for data mining and knowledge discovery [J]. WIRES Data Mining and Knowledge Discovery, 2017, 7(3): 1–12.
|
[43] |
Gudy A, Sikora M, Wróbel. RuleKit: A comprehensive suite for rulebased learning [J]. Knowledge-Based Systems, 2020, 194: 1–12.
|
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