Meeting The Design Requirements For Bi-Directional On-Board Charging (OBC)


As the automotive industry shifts from internal combustion engines (ICE), powered by fossil fuel, to electric drivetrains, consumers must adapt their approach to 'fueling' their vehicles. In fact, there is no longer any requirement to use dedicated fueling stations. Instead, plug-in hybrid and battery electric vehicles (xEV) can be charged either at home, at the office, or while shopping using ... » read more

AI’s Value In Chip Design Depends On Data Availability


Experts at the Table: Semiconductor Engineering sat down to discuss the advantages and challenges in using AI in designing chips, with Chuck Alpert, Cadence Fellow; Sathish Balasubramanian, head of product marketing and senior director for custom IC at Siemens EDA; Anand Thiruvengadam, senior director and head of AI product management at Synopsys; Sailesh Kumar, CEO of Baya Systems; Mehir ... » read more

Cross-Node Scaling Potential of SOT-MRAM for Last-Level Caches (imec)


A new technical paper titled "SOT-MRAM Bitcell Scaling with BEOL Read Selectors: A DTCO Study" was published by researchers at imec, Leuven, and 3001 Belgium. Abstract "This work explores the cross-node scaling potential of SOT-MRAM for last-level caches (LLCs) under heterogeneous system scaling paradigm. We perform extensive Design-Technology Co-Optimization (DTCO) exercises to evaluate th... » read more

Operational Cybersecurity and Supply Chain Risks Across the AI Lifecycle (Sandia National Labs)


A new technical paper titled "Surveying the Operational Cybersecurity and Supply Chain Threat Landscape when Developing and Deploying AI Systems" was published by researchers at Sandia National Labs. Abstract "The rise of AI has transformed the software and hardware landscape, enabling powerful capabilities through specialized infrastructures, large-scale data storage, and advanced hardware... » read more

Preparing For The Quantum Computing Age


Within a decade, quantum computers will be able to break virtually any encryption algorithm in use today. What used to be science fiction is on its way to becoming a commercial reality. Once that happens, quantum computers will be able to crack in minutes what was supposed to be unbreakable for more than a century using the most powerful computers available. Erik Wood, senior director of crypto... » read more

Research Bits: Sept. 2


Microwave neural network Researchers from Cornell University designed an on-chip microwave neural network that can perform real-time frequency domain computation for tasks like radio signal decoding, radar target tracking, and digital data processing. By using interconnected modes produced in tunable waveguides, the device can handle data streams in the tens of gigahertz while consuming less t... » read more

Chip Industry Technical Paper Roundup: Sept 2


New technical papers recently added to Semiconductor Engineering’s library: [table id=469 /] Find more semiconductor research papers here. » read more

2025 Critical Hardware Weaknesses (Hardware CWE Special Interest Group)


A new technical paper titled "2025 Most Important Hardware Weaknesses" was published by researchers at Hardware CWE Special Interest Group. Excerpt "The Most Important Hardware Weaknesses (MIHW) empowers organizations with the knowledge to proactively strengthen hardware security and reduce risks at the source. The 2025 CWE MIHW represents a refreshed and enhanced effort to identify and edu... » read more

Electrochemical Absorption of Hydrogen in Structured Palladium Thin-Film Electrodes (Univ. of Bristol)


A new technical paper titled "Exploring Electrochemical Methods for Precision Stress Control in Nanoscale Devices " was published by researchers at the University of Bristol. Abstract "Tuning the local film stress (and associated strain) provides a universal route toward exerting dynamic control on propagating fields in nanoscale geometries and engineering controlled interactions between th... » read more

LLM-Based Chiplet Design Generation Framework (Univ. of Minnesota)


A new technical paper titled "MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging" was published by researchers at the University of Minnesota - Twin Cities. Abstract "As program workloads (e.g., AI) increase in size and algorithmic complexity, the primary challenge lies in their high dimensionality, encompassing computing cores, array sizes, and memory hierarch... » read more

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