会议信息

ICEAMST 2026: International Conference on Emerging Applications in Material Science and Technology

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截稿日期:
2026-09-08
通知日期:
2026-10-10
会议日期:
2026-12-17
会议地点:
Bengaluru, Karnataka, India
届数:
浏览: 15922   关注: 0   参加: 0

会伴指数 (CP-I)

40.5 / 100
全站第 4,960 名 / 共 5,683 个会议 · 前 88%

材料、机械与制造 第 210 / 260

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
19
社区关注 (10%)
10
资料公开度 (15%)
55

用到的输入: 有据可查的届次：1 · 过去 24 个月打开过本页的研究者：3 人

公开资料里还缺: 历年录用率 (+4.5) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-21

征稿

ICEAMST 2026 (International Conference on Emerging Applications in Material Science and Technology) is an academic conference held in Bengaluru, Karnataka, India on 2026-12-17. The paper submission deadline is 2026-09-08. Acceptance notifications are sent on 2026-10-10.

ICEAMST 2026 welcomes high-quality research papers addressing significant innovations and applications in material science. The topics of interest include, but are not limited to, the following tracks: Track 1: Advanced Electronic Materials and Electronics 2D and 3D materials for next-generation electronics Layered materials for flexible and transparent electronic devices Stretchable and biodegradable electronics High-performance dielectric and piezoelectric applications Transistors and memory architectures Advanced signal and imaging technologies Bio-inspired electronic systems Edge computing and AI-integrated embedded devices Quantum materials for future electronics MEMS and NEMS innovations Advanced satellite and deep-space communication materials 5G and 6G-ready electronic circuits and architectures High-speed photonic and optoelectronic systems Terahertz and sub-terahertz communication materials Nanoelectronic sensor applications Track 2: Sustainable Materials and Communication Technologies Energy-harvesting materials for smart electronics Self-repairing and bio-degradable electronic components Circular economy and sustainable electronic waste management Next-gen VLSI and ULSI eco-friendly architectures High-efficiency RF and microwave materials Advanced remote sensing technologies AI-driven material design for green communications Smart grid innovations with sustainable materials Robotics and drone-based environmental monitoring Secure and reliable communication protocols Computational methods for sustainable material synthesis Terahertz communication materials AI-based misinformation detection in communication systems Track 3: Materials for Control, Automation, and Industry 4.0 Intelligent materials for automation and robotics AI-integrated sensor networks for industrial automation Machine learning-driven adaptive control systems Bio-compatible smart coatings for automation Quantum-enhanced process control Advanced AI-driven robotic applications in agriculture Sustainable power electronics for electric mobility High-efficiency autonomous vehicle materials Smart materials for human-machine collaboration Digital twin and cyber-physical systems in Industry 4.0 Track 4: Materials for Networking and Computing Advanced photonic computing materials AI-powered security materials for quantum networks Future-proof materials for high-speed networking Emerging substrates for 6G and beyond Bio-inspired materials for secure information transfer Edge computing hardware innovations AI-driven networking topologies and architectures AR/VR-assisted networking material advancements Secure hardware-based cryptographic materials Impacts of advanced networking materials Low-latency materials for high-performance computing Track 5: Applications of Material Science and Computing Technologies Materials for next-gen biomedical implants and sensors Hybrid material innovations for sustainable engineering Emerging trends in smart material synthesis AI-assisted material design and optimization LiDAR and hyperspectral imaging material applications High-speed computing materials for AI acceleration Novel bio-mimetic materials for medical applications AI-driven nano-material fabrication Augmented and virtual reality-based material applications Computational intelligence for material property prediction
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