Results 131 to 140 of about 55,151 (279)

Thermal Conductivity Across the Nonpolar‐Polar Phase Transition in Incipient Ferroelectric KTaO3

Advanced Electronic Materials, EarlyView.
Phonon dispersion of the cubic nonpolar ground‐state and a ferroelectric tetragonal phase, stabilized by a compressive strain of 2%. ABSTRACT The manipulation of the lattice of polar materials via external electric fields is an effective way to dynamically control the heat flux, accessing different thermal conductivity, κ${\bm \kappa }$, states ...
Martí Raya‐Moreno, Nakib H. Protik, Riccardo Rurali   +2 more
wiley   +1 more source

Fault-tolerant interface between quantum memories and quantum processors

Nature Communications, 2017
In the quest for fault-tolerant quantum computation, being able to interface different topological codes such as surface and color codes would allow to get the best of each code. Here, the authors show how to interface arbitrary topological quantum error
Hendrik Poulsen Nautrup, Nicolai Friis, Hans J. Briegel   +2 more
doaj   +1 more source

Uncovering the Role of Intrinsic Magnetic Order in Oxygen Evolution Reaction Activity With Operando Spectroscopy

Advanced Energy Materials, EarlyView.
Operando magnetic spectroscopy provides insight into how intrinsic magnetic order modulates the oxygen evolution reaction on La0.67Sr${\rm La}_{0.67}{\rm Sr}$0.33MnO$_{0.33}{\rm MnO}$3$_3$ thin films. Temperature‐dependent operando FMR and ambient‐pressure XMCD suggest a correlation between activity and the emergence of ferromagnetic regions near and ...
Emma van der Minne, Silvia Mauri, Anatoliy A. Vereshchagin, Vadim Ratovskii, Ellen M. Kiens, Hemanita Sharma, Jan Behrends, Piero Torelli, Gertjan Koster, Christoph Baeumer   +9 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

SigmaFormer: Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction

AIChE Journal, EarlyView.
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim, Silabrata Pahari, Joseph Sang‐Il Kwon   +2 more
wiley   +1 more source

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen, Chiku Parida, Jonas Busk, Jin Hyun Chang, Arghya Bhowmik, Juan Maria Garcia Lastra   +5 more
wiley   +1 more source

Adaptive Syndrome Extraction

PRX Quantum
Device error rates on current quantum computers have improved enough to where demonstrations of error correction below break even are now possible. Still, the circuits required for quantum error correction introduce significant overhead and sometimes ...
Noah Berthusen, Shi Jie Samuel Tan, Eric Huang, Daniel Gottesman   +3 more
doaj   +1 more source

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

Advanced 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, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

Advanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen, Tushar Singh Thakur, Manuel Dillenz, Johan M. Carlsson, Celso R. C. Rêgo, Eibar Flores, Hamidreza Hajiyani, Felix Hanke, Juan María García Lastra, Wolfgang Wenzel, Nicola Marzari, Tejs Vegge, Giovanni Pizzi, Ivano E. Castelli   +13 more
wiley   +1 more source