Results 201 to 210 of about 82,344 (301)

Robust and Compatible Ferroelectric Memories with Polycrystalline TiO2 Channel for 3D Integration

Advanced Electronic Materials, EarlyView.
Robust and monolithic 3D compatible ferroelectric memories are realized using the polycrystalline TiO2 channel‐based FeFET. The review covers physical mechanisms of the TiO2 channel FeFET, quantitative benchmarking, and advanced planar/vertical architectures for monolithic 3D integration based on HfO2‐TiO2 gate stack, offering a roadmap for reliable ...
Xujin Song, Chenxi Yu, Shangze Li, Dijiang Sun, Jiajia Zhang, Haotong Zhu, Xiaomin Xiao, Xionghao Qin, Xiaoyan Liu, Xing Zhang, Jinfeng Kang   +10 more
wiley   +1 more source

A Compendium of Logic Gates Based on Reconfigurable Three‐Independent‐Gate Transistors Realized in FDSOI Hardware

Advanced Electronic Materials, EarlyView.
This work electrically characterizes sixteen logic gates built from three‐independent‐gate reconfigurable transistors fabricated on full‐scale 300 mm wafers using the industrial 22 nm fully depleted FDSOI process of GlobalFoundries. Static and time‐resolved measurements confirm correct operation, including a 1‐bit adder and reconfigurable AOI/OAI ...
Juan P. Martinez, Yuxuan He, Giulio Galderisi, Violetta Sessi, Niladri Bhattacharjee, Peter Baars, Kerstin Poenisch, Annekathrin Zeun, Konstantin Li, Fernando Koch, Binit Syamal, Thomas Mikolajick, Jens Trommer   +12 more
wiley   +1 more source

Social media distrust and turn to artificial intelligence among generation Z: a qualitative model linking digital minimalism and financial discipline with social policy recommendations. [PDF]

Front Artif Intell
Ökten B.
europepmc   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

A budget of paradoxes. [PDF]

Journal of the Staple Inn Actuarial Society, 1953
openaire   +2 more sources

Budget instructions [PDF]

Nature, 2009
openaire   +2 more sources

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Historical roots of hospital-centred operational governance in China: a path dependence analysis and its implications for global health system reform. [PDF]

BMJ Glob Health
Li JZ, Wang D, Li X, Zhu M, Tiong Y, Lao Y.   +5 more
europepmc   +1 more source

Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation

Advanced Electronic Materials, EarlyView.
A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang, Nellie Laleni, Sina Ranjbar, Andreas Tsiougkos, Nandakishor Yadav, Vasilis Pavlidis, Thomas Kämpfe   +6 more
wiley   +1 more source