Results 101 to 110 of about 970,819 (298)

Investigating the First-Order Flotation Kinetics Models for Iranian Gilsonite

open access: yesIranian Journal of Materials Science and Engineering, 2020
Kinetic models are the most important instruments for predicting and evaluating the performance of flotation circuits. To determine the kinetic order and rate of flotation of a gilsonite sample, flotation experiments were carried out in both rougher and ...
A. Bahrami   +2 more
doaj  

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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

Physics‐Based Compact Modeling of Advanced 3D Nanoscale Vertical NAND Flash Memory

open access: yesAdvanced Electronic Materials, EarlyView.
For advanced 3D NAND flash memory, a unified compact model for SPICE is proposed that spans from the intrinsic unit cell to the full string and captures the electrostatic coupling with adjacent inhibit strings. It can successfully predict read behavior, program/erase dynamics, and interactions between neighboring cells, reflecting array‐level behavior ...
Ilho Myeong, Seonho Shin, Ickhyun Song
wiley   +1 more source

Highly‐Uniform Passive Crossbar Arrays of Resistive Switching Random Access Memory (RRAM) for In‐Memory Computing Applications

open access: yesAdvanced Electronic Materials, EarlyView.
Passive resistive memory arrays promise efficient in‐memory computing but suffer from sneak paths and programming variability. Here, highly uniform 32 × 32 passive RRAM crossbars are programmed with multilevel precision below 3% error and 99.5% yield.
S. Ricci   +6 more
wiley   +1 more source

Natural Anionic Interfacial Reconstruction for Suppressing Pitting Corrosion Enables Durable Seawater Zinc‐Ion Batteries

open access: yesAdvanced Energy Materials, EarlyView.
In situ electrochemically induced molecular sieve‐alginate interface layer can suppress chloride‐induced pitting corrosion, hydrogen evolution, and dendrite growth, while regulating zinc ion transport and deposition, thereby protecting the zinc anode in seawater electrolyte.
Yunpeng Zhong   +7 more
wiley   +1 more source

Gas–liquid mass transfer enhancement in the presence of nanoparticles under slug flow in microreactors

open access: yesAIChE Journal, EarlyView.
Abstract Nanofluids containing nanoparticles represent a promising solvent or reaction system for gas–liquid operations. Herein, the effect of nanoparticle (Al2O3 and SiO2) addition on gas–liquid slug flow pattern and mass transfer enhancement was investigated during CO2 absorption into water in microreactors.
Jie Zong, Jun Yue
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

open access: yesAdvanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj   +2 more
wiley   +1 more source

Removal of Emulsified Paraffine from Water: Effect of Bubble Size and Particle Size on Kinetic of Flotation

open access: yesIraqi Journal of Chemical and Petroleum Engineering, 2007
This paper  studied  kinetics  of flotation   of  emulsified  paraffine  in  water  in  bubble  column  with  sodium .dodecylsulphate as a collector agent. The effects of oil drops and air bubble diameters on the flotation rate constant were studied. The
Ahmed A. Mohammed
doaj  

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

open access: yesAdvanced Intelligent Discovery, EarlyView.
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh   +3 more
wiley   +1 more source

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