New Technology– category –
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TSMC Completes 1.6nm A16 Process Development, Targets Q4 Mass Production for Next-Gen AI/HPC Chips
Design And Reuse Taiwan Overview TSMC has successfully completed development of its 1.6nm A16 process technology, with mass production scheduled for Q4. This cutting-edge process is foundational for next-generation high-performance compu... -
Shanghai Jiao Tong University Develops FOWLP for Seamless Opto-Electronic Integration, Halving Signal Loss in Data Centers
IMAPS 3D InCites Content Platform China Overview Researchers at Shanghai Jiao Tong University have pioneered a fan-out wafer-level packaging (FOWLP) technique to integrate electronic and photonic components, significantly reducing signal... -
High-Frequency MLCC Evolution Critical for 800G/1.6T Optical Modules: Enabling AI-Era High-Capacity Communications
Barron (Barron MLCC) International Overview The evolution of high-frequency multilayer ceramic capacitors (MLCCs) is proving critical for enabling next-generation 800G and 1.6T optical modules. These ultra-high-speed modules require ultr... -
Heterogeneously Integrated Thin-Film Lithium Niobate Coupled-Cavity Modulator Enables Tunable Frequency Beam Splitting on Silicon
arXiv International Overview Researchers have developed a heterogeneously integrated thin-film lithium niobate (TFLN) coupled-cavity modulator on silicon that achieves tunable bidirectional frequency mode conversion. This breakthrough al... -
ACS Paper: Modular ML Workflow Achieves High-Efficiency Hypothesis Generation for Lithium Solid Electrolytes, Predicting Ionic Conductivity
The Journal of Physical Chemistry C | ACS Publications USA Overview A research published in 'The Journal of Physical Chemistry C' (ACS Publications) presents a modular machine learning (ML) workflow for generating and prioritizing lithiu... -
Preprints.org Publishes Review on High-Entropy Alloy Design: ML Addresses Combinatorial Explosion in Discovery
Preprints.org Unknown Overview A review paper published on Preprints.org explores the convergence of physical metallurgy and data-driven methods in high-entropy alloy (HEA) design. The paper details how AI and machine learning (ML) addre... -
Mitsubishi Chemical Forges Hybrid AI-Quantum Path for Next-Gen EUV Photoresists
Mitsubishi Chemical Japan Overview Mitsubishi Chemical has unveiled a pioneering research initiative integrating generative AI, quantum computing, and GPU-accelerated platforms to revolutionize the design of next-generation EUV photoresi... -
Autonomous Laboratories Spark Paradigm Shift in Materials Science, Accelerating Development Through Evolving Algorithms and Hardware
Facebook Unknown Overview Autonomous Laboratories (SDLs) are fundamentally transforming materials science, enabling unprecedented acceleration in materials discovery through autonomous exploration. By integrating advanced AI—from machine... -
AI-Powered Platform from IIT Madras Forges World’s Largest Open Alloy Database, Turbocharging Sustainable Materials Discovery
Open Source For U India Overview Researchers at IIT Madras have developed an AI-driven, open-source platform that leverages large language models (LLMs) to extract and organize scientific data from over 10,000 papers. This initiative has... -
MIT Unveils CrysVCD Framework, Boosting AI-Designed Material Stability by 70% and Dramatically Reducing Computational Costs
MIT News USA Overview MIT researchers have developed 'CrysVCD' (crystal generator with valence-constrained design), a framework that significantly improves the stability rate of AI-generated materials. This approach ensures designs satis...
