Results 31 to 40 of about 15,459,849 (275)

Accelerated Discovery of Topological Spin Phase Diagrams in CrSBr Magnets Via High‐Throughput Optimization

Advanced Functional Materials, EarlyView.
Here, we develop a high‐throughput algorithm that accelerates the elucidation of phase diagrams of topological spin textures using limited computational resources at high numerical accuracy. Applying this framework to the van der Waals magnet CrSBr, we unveiled a hierarchy of previously unknown topological textures (domain‐wall bimerons, bimeron chains,
Andrew Lyall, Mohammad H. Badarneh, Cristian Bonato, Rebecca Cheung, Elton J. G. Santos   +4 more
wiley   +1 more source

Hybrid Ferroelectric Tunnel Junctions with Intrinsic Nonlinearity and Self‐Rectification via Interfacial Reconstruction

Advanced Functional Materials, EarlyView.
Rapid thermal annealing reconstructs the BCFO/Nb:STO interface into an atomically thin reconstructed interfacial layer, which reshapes the tunneling barrier and converts a high‐TER ferroelectric tunnel junction into an intrinsically nonlinear, self‐rectifying device.
Hojin Lee, Joonbong Lee, Jinho Byun, Sang‐Hyeok Yang, A young Cho, Sangwoo Lee, Dae Haa Ryu, Hyunbin Chung, Hee Seo Yun, Moon Seop Choi, Yesul Choi, Sungkyun Park, Min‐Hyung Jung, Dongwon Lee, Yoon‐Uk Heo, Hu Young Jeong, Hongseok Kim, Shinhyeong Lee, Yunseok Kim, Young‐Min Kim, Jaekwang Lee, Taekjib Choi   +21 more
wiley   +1 more source

A multi-resolution systematically improvable quantum embedding scheme for large-scale surface chemistry calculations

Nature Communications
Predictive simulation of surface chemistry is critical in fields from catalysis to electrochemistry and clean energy generation. Ab-initio quantum many-body methods should offer deep insights into these systems at the electronic level but are limited by ...
Zigeng Huang, Zhen Guo, Changsu Cao, Hung Q. Pham, Xuelan Wen, George H. Booth, Ji Chen, Dingshun Lv   +7 more
doaj   +1 more source

Building an ab initio solvated DNA model using Euclidean neural networks.

PLoS ONE
Accurately modeling large biomolecules such as DNA from first principles is fundamentally challenging due to the steep computational scaling of ab initio quantum chemistry methods. This limitation becomes even more prominent when modeling biomolecules in
Alex J Lee, Joshua A Rackers, Shivesh Pathak, William P Bricker   +3 more
doaj   +1 more source

Nitride MXenes Beyond Carbides: Bridging the Gap Between Computational Prediction and Experimental Realization

Advanced Functional Materials, EarlyView.
Nitride MXenes remain constrained by a persistent gap between computational prediction and experimental realization. This Review identifies the thermodynamic, kinetic, and chemical barriers limiting their synthesis, critically evaluates emerging fabrication routes, and proposes a multidimensional computational‐experimental framework to accelerate the ...
Naresh Varnakavi, Masoud Soroush
wiley   +1 more source

Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns

Frontiers in Chemistry, 2019
Computational Chemistry is currently a synergistic assembly between ab initio calculations, simulation, machine learning (ML) and optimization strategies for describing, solving and predicting chemical data and related phenomena.
Tânia F. G. G. Cova, Alberto A. C. C. Pais   +1 more
doaj   +1 more source

Calculation of absorption spectra of silver-thiolate complexes [PDF]

Компьютерные исследования и моделирование, 2019
Ligand protected metal nanoclusters (NCs) have gained much attention due to their unique physicochemical properties and potential applications in material science.
Andrey Andreevich Buglak, Vladimir Alexandrovich Pomogaev, A. I. Kononov   +2 more
doaj   +1 more source

Emergence of a Hexagonal Fe2S2 Single Layer Without a Bulk Counterpart via Phase Transformation

Advanced Functional Materials, EarlyView.
Upon annealing, single‐layer Mackinawite iron sulfide transforms into a previously unknown hexagonal Fe2S2${\rm Fe}_2{\rm S}_2$ phase with β$\beta$‐CuI structure. STM, LEED, and first‐principles calculations identify the structure and show that electronic correlations and magnetic order are important for its stability.
Affan Safeer, Wejdan Beida, Felix Oberbauer, Nicolae Atodiresei, Gustav Bihlmayer, Max Wolfertz, Chiara Schlichte, Wouter Jolie, Stefan Blügel, Jeison Fischer, Thomas Michely   +10 more
wiley   +1 more source

Evidence for Itinerant Ferromagnetic Flat Bands Producing Large Transverse Responses

Advanced Materials, EarlyView.
Itinerant ferromagnetic flat bands are demonstrated in GdCo5 with a high Curie temperature of 940K, a stacked honeycomb–kagome lattice, through angle‐resolved photoemission spectroscopy and magneto‐thermoelectric measurements. These topological flat bands generate large Berry curvaturte, producing gigantic anomalous Nernst effect with record‐high ...
Susumu Minami, Yangming Wang, Seigo Souma, Hiroto Nakamura, Akito Sakai, Takumi Osumi, Hang Su, Hikaru Watanabe, Shun'ichiro Kurosawa, Rikuto Oiwa, Daisuke Nishio‐Hamane, Kosuke Nakayama, Takuya Nomoto, Ryotaro Arita, Takafumi Sato, Satoru Nakatsuji   +15 more
wiley   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source