Results 61 to 70 of about 114,012 (307)

Al–Cu Composite Casting of Laser‐Deoxidized Copper: Bonding, Interfacial Chemistry, and Thermal Conductivity

Advanced Engineering Materials, EarlyView.
This study investigates laser‐based oxide removal of Cu inserts in oxygen‐free conditions and examines long‐term oxidation kinetics and surface chemistry under different atmospheres via X‐ray photoelectron spectroscopy. Al–Cu compound casting with differently oxidized surfaces is performed, and intermetallic phase formation, morphology, and thermal ...
Timon Steinhoff, Finn‐Lennard Janthur, Sascha Zimmermann, Sarah Seffer, Jörg Hermsdorf, René Gustus, Ludger Overmeyer, Wolfgang Maus‐Friedrichs, Hans Jürgen Maier, Christian Klose   +9 more
wiley   +1 more source

Toward Low‐Consumable Anodes: Process Simulation and Prospective Life Cycle Assessment of NiFe2O4‐NiO‐Ni‐Cu vs. Prebaked Anodes for Aluminum Production with use of Molten Salt Electrolysis

Advanced Engineering Materials, EarlyView.
Low‐consumable nickel ferrite‐based anodes for the Hall–Héroult process are compared with conventional prebaked carbon anodes using thermodynamic simulation and prospective life cycle assessment under contrasting future electricity system pathways from 2025 to 2050.
Felipe Alejandro Garcia Paz, Ulziikhuu Otgonbayar, Alexander Adamczyk, Farhan Hossain, Daniel Vogt, Johan Berg Pettersen, Alexandros Charitos   +6 more
wiley   +1 more source

Coin impact on cross-crypto realized volatility and dynamic cryptocurrency volatility connectedness

Financial Innovation
This study evaluates the predictive accuracy of traditional time series (TS) models versus machine learning (ML) methods in forecasting realized volatility across major cryptocurrencies—Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), and Ripple (XRP ...
Burak Korkusuz, Mehmet Sahiner
doaj   +1 more source

Numerical Modeling of Tank Cars Carrying Hazardous Materials With and Without Composite Metal Foam

Advanced Engineering Materials, EarlyView.
Large‐scale puncture models consisting of hazardous materials (HAZMATs) tank car with protective steel–steel composite metal foam (S–S CMF) are solved numerically. Tank car plate with added 10.91–13.33 mm thick S–S CMF layer does not puncture. Protective S–S CMF absorbs impact energy, reduces plate deformation, and prevents shear bands formation ...
Aman Kaushik, Afsaneh Rabiei
wiley   +1 more source

Cryptocurrency price returns volatility modeling and forecasting with GARCH models [PDF]

RAUSP Management Journal
PurposeThe paper aims to identify suitable conditional variance models for the estimation and forecasting of cryptocurrency returns volatility.Design/methodology/approachThe methodology comprises the use of GARCH-family models estimated by maximum ...
Lukas Silva, Leandro Maciel
doaj   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +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

Reducing Open‐Circuit Voltage Losses in Wide‐Bandgap FAPbBr3 Perovskite Solar Cells for Continuous Unassisted Light‐Driven Water Splitting

Advanced Functional Materials, EarlyView.
The combination of formamidinium thiocyanate and 1,3‐propane diammonium iodide for bulk and top‐surface passivation, and a ternary fullerene blend to improve energy band alignment, suppresses energy losses in wide‐bandgap FAPbBr3 perovskite solar cells.
Laura Bellini, Daniël Grosfeld, Bruno Branco, Guus J. W. Aalbers, Lana M. Kessels, Willemijn H. M. Remmerswaal, Nicolas Daub, Kunal Datta, Martijn M. Wienk, René A. J. Janssen   +9 more
wiley   +1 more source

Advances in forecasting realized volatility: a review of methodologies

Financial Innovation
Over the past decade, volatility modeling has gained increasing importance in quantitative finance, significantly influencing risk management, investment strategies, and policymaking.
Radmir Mishelevich Leushuis, Nicolai Petkov   +1 more
doaj   +1 more source

The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock, and Bond Markets [PDF]

We study the forecasting of future realized volatility in the foreign exchange, stock, and bond markets from variables in the information set, including implied volatility backed out from option prices.
Bent Jesper Christensen, Morten Ørregaard Nielsen, Thomas Busch   +2 more
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