tag: CNRS

Chip Industry Technical Paper Roundup: Sept. 24
By Linda Christensen - 24 Sep, 2024 - Comments: 0

New technical papers recently added to Semiconductor Engineering’s library: [table id=358 /] More ReadingTechnical Paper Library home » read more

Better Security and Power Efficiency of Ascon HW Implementation with STT-MRAM (CEA, et al.)
By Technical Paper Link - 18 Sep, 2024 - Comments: 0

A new technical paper titled "Enhancing Security and Power Efficiency of Ascon Hardware Implementation with STT-MRAM" was published by researchers at CEA, Leti, Université Grenoble Alpes, CNRS, and Spintec. Abstract "With the outstanding growth of Internet of Things (IoT) devices, security and power efficiency of integrated circuits can no longer be overlooked. Current approved standards f... » read more

Steps to Fabricate Nanotips Overhanging From Chip Edge By a Few Micrometers (CNRS, CEA-Leti)
By Technical Paper Link - 10 Sep, 2024 - Comments: 0

A new technical paper titled "Suspended tip overhanging from chip edge for atomic force microscopy with an optomechanical resonator" was published by researchers at Lab. d'Analyse et d'Architecture des Systèmes du CNRS and CEA-LETI. Abstract Raising the mechanical frequency of atomic force microscopy (AFM) probes to increase the measurement bandwidth has been a long-standing expectation in... » read more

Chip Industry Technical Paper Roundup: Sept. 9
By Linda Christensen - 09 Sep, 2024 - Comments: 0

New technical papers recently added to Semiconductor Engineering’s library: [table id=354 /] More ReadingTechnical Paper Library home » read more

New Strategies For Enhancing Transport Properties of Conducting Polymers (Cambridge, et al.)
By Technical Paper Link - 06 Sep, 2024 - Comments: 0

A new technical paper titled "Non-equilibrium transport in polymer mixed ionic–electronic conductors at ultrahigh charge densities" was published by researchers at Cambridge University, Grenoble Alpes University, CNRS, Humboldt-Universität zu Berlin, et al. Abstract "Conducting polymers are mixed ionic–electronic conductors that are emerging candidates for neuromorphic computing, bioel... » read more

Research Bits: Jan. 23
By Jesse Allen - 23 Jan, 2024 - Comments: 0

Memristor-based Bayesian neural network Researchers from CEA-Leti, CEA-List, and CNRS built a complete memristor-based Bayesian neural network implementation for classifying types of arrhythmia recordings with precise aleatoric and epistemic uncertainty. While Bayesian neural networks are useful for at sensory processing applications based on a small amount of noisy input data because they ... » read more

Chip Industry Week In Review
By The SE Staff - 19 Jan, 2024 - Comments: 0

By Jesse Allen, Gregory Haley, and Liz Allan Synopsys will acquire Ansys for about $35 billion in cash and stock. The deal will boost Synopsys' multi-physics simulation capabilities, which are essential for complex 3D-IC designs, where thermal density can have significant repercussions. The acquisition is expected to be finalized in the first half of 2025. Worldwide semiconductor revenue ... » read more

Chip Industry Technical Paper Roundup: Jan 2
By Linda Christensen - 02 Jan, 2024 - Comments: 0

New technical papers added to Semiconductor Engineering’s library this week. [table id=180 /] More ReadingTechnical Paper Library home » read more

Nanoscale Reconfigurable Si Transistors (TU Wien, CNRS, UNC)
By Technical Paper Link - 20 Dec, 2023 - Comments: 0

A new technical paper titled "Nanoscale Reconfigurable Si Transistors: From Wires to Sheets and Unto Multi-Wire Channels" was published by researchers at TU Wien, CNRS, and University of North Carolina at Chapel Hill. Abstract: "In this work, bottom-up Al–Si–Al nanowire (NW) heterostructures are presented, which act as a prototype vehicle toward top-down fabricated nanosheet (NS) and ... » read more

Memory Devices-Based Bayesian Neural Networks For Edge AI
By Technical Paper Link - 20 Dec, 2023 - Comments: 0

A new technical paper titled "Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks" was published by researchers at Université Grenoble Alpes, CEA, LETI, and CNRS. Abstract: "Safety-critical sensory applications, like medical diagnosis, demand accurate decisions from limited, noisy data. Bayesian neural networks excel at such tasks, offering... » read more

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