Results 171 to 180 of about 1,025,950 (315)

Device quantization policy in variation-aware in-memory computing design. [PDF]

Sci Rep, 2022
Chang CC, Li ST, Pan TL, Tsai CM, Wang IT, Chang TS, Hou TH.   +6 more
europepmc   +1 more source

Self‐Immolative Activatable Nanoassembly toward Immuno‐Photodynamic Therapy in TME

Advanced Functional Materials, EarlyView.
A quinone methide‐gated, self‐immolative, H2O2‐responsive nano‐photosensitizer (Pyz/PS) is developed for targeted immuno‐photodynamic therapy. Pyz/PS selectively activates within tumor microenvironments, restores photosensitizer activity, generates ROS, and depletes intracellular GSH, enhancing oxidative stress.
Jing Li, E Pang, Snehasish Debnath, Jia Hong, Aojun Qiu, Dongeun Kim, Goeun Kim, Minhuan Lan, Min‐Goo Lee, Qian‐Yong Cao, Jong Seung Kim   +10 more
wiley   +1 more source

Recent advances in ferroelectric materials, devices, and in-memory computing applications. [PDF]

Nano Converg
Hwang H, Youn S, Kim H.
europepmc   +1 more source

Synergistic Approach of Interfacial Layer Engineering and READ-Voltage Optimization in HfO₂-Based FeFETs for In-Memory-Computing Applications. [PDF]

ACS Appl Electron Mater, 2022
Raffel Y, De S, Lederer M, Olivo RR, Hoffmann R, Thunder S, Pirro L, Beyer S, Chohan T, Kämpfe T, Seidel K, Heitmann J.   +11 more
europepmc   +1 more source

Multicolor Optoelectronic Synapse Enabled by Photon‐Modulated Remote Doping in Solution‐Processed Van Der Waals Heterostructures

Advanced Functional Materials, EarlyView.
Multicolor optoelectronic synapses are realized by vertically integrating solution‐processed MoS2 thin‐film and SWCNT. The electronically disconnected but interactive MoS2 enables photon‐modulated remote doping, producing a bi‐directional photoresponse.
Jihyun Kim, Hyunbin Kim, Gang Jin Cheon, Dohyun Lee, In Soo Kim, Uiyeon Won, Jongseok Lee, Sang Min Won, Joohoon Kang   +8 more
wiley   +1 more source

High-throughput design of optoelectronic-ferroelectric heterostructure from materials to sensor-memory-computing devices. [PDF]

Natl Sci Rev
Zhong G, Yan J, Tang M, Deng H, Tan Y, Zhong X, Li C, Fan Z, Wang J, Li J.   +9 more
europepmc   +1 more source

An energy-efficient in-memory computing architecture for survival data analysis based on resistive switching memories. [PDF]

Front Neurosci, 2022
Baroni A, Glukhov A, Pérez E, Wenger C, Calore E, Schifano SF, Olivo P, Ielmini D, Zambelli C.   +8 more
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Complex Cryptographic and User‐Centric Physically Unclonable Functions Enabled by Strain‐Sensitive Nanocrystals via Selective Ligand Exchange

Advanced Functional Materials, EarlyView.
This study investigates electromechanical PUFs that improve on traditional electric PUFs. The electron transport materials are coated randomly through selective ligand exchange. It produces multiple keys and a key with motion dependent on percolation and strain, and approaches almost ideal inter‐ and intra‐hamming distances.
Seungshin Lim, Hanseok Seo, Taesung Park, Byung Ku Jung, Junhyeok Park, Young Kyun Choi, Dae Yang Oh, Soong Ju Oh   +7 more
wiley   +1 more source

In-Memory-Computing Realization with a Photodiode/Memristor Based Vision Sensor. [PDF]

Materials (Basel), 2021
Vasileiadis N, Ntinas V, Sirakoulis GC, Dimitrakis P.   +3 more
europepmc   +1 more source