Results 111 to 120 of about 3,122,051 (263)
Fast Kronecker Matrix-Matrix Multiplication on GPUs [PDF]
Kronecker Matrix-Matrix Multiplication (Kron-Matmul) is the multiplication of a matrix with the Kronecker Product of several smaller matrices. Kron-Matmul is a core operation for many scientific and machine learning computations.
Jangda, Abhinav, Yadav, Mohit
core +1 more source
Azobenzene photoswitches translate molecular‐scale E/Z photoisomerization into macroscopic material responses and device‐level photonic functions. This Review highlights how azobenzene research has evolved from molecular photochemistry to photoalignment, mass migration, photomechanics, and heat release, ultimately enabling holography, reconfigurable ...
Heeju Son +20 more
wiley +1 more source
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Matrix Multiplication on Quantum Computer [PDF]
This paper introduces an innovative and practical approach to universal quantum matrix multiplication. We designed optimized quantum adders and multipliers based on Quantum Fourier Transform (QFT), which significantly reduced the number of gates used ...
Liu, Ding, Yao, Jiaqi
core +1 more source
Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair +3 more
wiley +1 more source
Experimental implementation of matrix multiplication by DNA computing
In this chapter, a method to do binary multiplication with DNA molecules based on DNA computing is presented. The first proposal on matrix multiplication with DNA has been presented by John S. Oliver.
Tsuboi, Yusei +3 more
core
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Sheaf Cohomology of Rectangular-Matrix Chains to Develop Deep-Machine-Learning Multiple Sequencing
The sheaf cohomology techniques are newly used to include Morse simplicial complexes in a rectangular-matrix chain, whose singular values are compatible with those of a square matrix, which can be used for multiple sequencing. The equivalence with the simplices of the corresponding graph is proven, as well as that the filtration of the corresponding ...
openaire +1 more source
“Smelltronics”—From Gas to Smell Sensing
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono +7 more
wiley +1 more source
Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen +7 more
wiley +1 more source

