Search Results - "Stanev, Valentin"

Machine learning modeling of superconducting critical temperature by Stanev, Valentin, Oses, Corey, Kusne, A. Gilad, Rodriguez, Efrain, Paglione, Johnpierre, Curtarolo, Stefano, Takeuchi, Ichiro

“…Superconductivity has been the focus of enormous research effort since its discovery more than a century ago. Yet, some features of this unique phenomenon…”
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Machine-learning guided discovery of a new thermoelectric material by Iwasaki, Yuma, Takeuchi, Ichiro, Stanev, Valentin, Kusne, Aaron Gilad, Ishida, Masahiko, Kirihara, Akihiro, Ihara, Kazuki, Sawada, Ryohto, Terashima, Koichi, Someya, Hiroko, Uchida, Ken-ichi, Saitoh, Eiji, Yorozu, Shinichi

“…Thermoelectric technologies are becoming indispensable in the quest for a sustainable future. Recently, an emerging phenomenon, the spin-driven thermoelectric…”
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Quasiclassical Eilenberger theory of the topological proximity effect in a superconducting nanowire by Stanev, Valentin, Galitski, Victor

“…We use the quasiclassical Eilenberger theory to study the topological superconducting proximity effects between a segment of a nanowire with a p-wave order…”
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Artificial intelligence for search and discovery of quantum materials by Stanev, Valentin, Choudhary, Kamal, Kusne, Aaron Gilad, Paglione, Johnpierre, Takeuchi, Ichiro

“…Artificial intelligence and machine learning are becoming indispensable tools in many areas of physics, including astrophysics, particle physics, and climate…”
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Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals by Iliev, Filip L, Stanev, Valentin G, Vesselinov, Velimir V, Alexandrov, Boian S

“…Factor analysis is broadly used as a powerful unsupervised machine learning tool for reconstruction of hidden features in recorded mixtures of signals. In the…”
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Identification of release sources in advection–diffusion system by machine learning combined with Green’s function inverse method by Stanev, Valentin G, Iliev, Filip L, Hansen, Scott, Vesselinov, Velimir V, Alexandrov, Boian S

“…The identification of sources of advection–diffusion transport is based usually on solving complex ill-posed inverse models against the available…”
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Excitonic and nematic instabilities on the surface of topological Kondo insulators by Roy, Bitan, Hofmann, Johannes, Stanev, Valentin, Sau, Jay D., Galitski, Victor

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Machine learning modeling of the absorption properties of azobenzene molecules by Stanev, Valentin, Maehashi, Ryota, Ohta, Yoshimi, Takeuchi, Ichiro

“…We present a machine learning framework for modeling the absorption properties of azobenzene molecules – an important class of organic compounds with many…”
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Identification of advanced spin-driven thermoelectric materials via interpretable machine learning by Iwasaki, Yuma, Sawada, Ryohto, Stanev, Valentin, Ishida, Masahiko, Kirihara, Akihiro, Omori, Yasutomo, Someya, Hiroko, Takeuchi, Ichiro, Saitoh, Eiji, Yorozu, Shinichi

“…Machine learning is becoming a valuable tool for scientific discovery. Particularly attractive is the application of machine learning methods to the field of…”
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Finding the Number of Latent Topics with Semantic Non-negative Matrix Factorization by Vangara, Raviteja, Bhattarai, Manish, Skau, Erik, Chennupati, Gopinath, Djidjev, Hristo, Tierney, Thomas, Smith, James P., Stanev, Valentin G., Alexandrov, Boian S.

“…Topic modeling, or identifying the set of topics that occur in a collection of articles, is one of the primary objectives of text mining. Typically, a text…”
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Topological defect-phase soliton and the pairing symmetry of a two-band superconductor: role of the proximity effect by Vakaryuk, Victor, Stanev, Valentin, Lee, Wei-Cheng, Levchenko, Alex

“…We suggest a mechanism which promotes the existence of a phase soliton--a topological defect formed in the relative phase of superconducting gaps of a two-band…”
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Nonnegative tensor decomposition with custom clustering for microphase separation of block copolymers by Alexandrov, Boian S., Stanev, Valentin G., Vesselinov, Velimir V., Rasmussen, Kim Ø.

“…High‐dimensional datasets are becoming ubiquitous in many applications and therefore unsupervised tensor methods to interrogate them are needed. Here, we…”
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Robust accidental nodes and zeros and critical quasiparticle scaling in iron-based multiband superconductors by Stanev, Valentin, Alexandrov, Boian S., Nikolić, Predrag, Tešanović, Zlatko

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Model of collective modes in three-band superconductors with repulsive interband interactions by Stanev, Valentin

“…I consider a simple model of a three-band superconductor with repulsive interband interactions. The frustration, associated with the odd number of bands, leads…”
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Spin fluctuation dynamics and multiband superconductivity in iron pnictides by Stanev, Valentin, Kang, Jian, Tesanovic, Zlatko

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Predicting the superconducting critical temperature in transition metal carbides and nitrides using machine learning by Metni, Houssam, Takeuchi, Ichiro, Stanev, Valentin

“…Transition metal carbides and nitrides have unique mechanical and chemical characteristics. At low temperatures many of them also exhibit superconductivity,…”
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Predicting the superconducting critical temperature in transition metal carbides and nitrides using machine learning by Metni, Houssam, Takeuchi, Ichiro, Stanev, Valentin

“…Transition metal carbides and nitrides have unique mechanical and chemical characteristics. At low temperatures many of them also exhibit superconductivity,…”
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Exploring features in chromatographic profiles as a tool for monitoring column performance by Ravi, Nivetita, Malmquist, Gunnar, Stanev, Valentin, Ferreira, Gisela

“…•Accelerated resin degradation of a protein A chromatography column was studied.•Various data analysis methods were used on chromatogram…”
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Enhancement of superconductivity via periodic modulation in a three-dimensional model of cuprates by Raines, Zachary M., Stanev, Valentin, Galitski, Victor M.

“…Recent experiments in the cuprates have seen evidence of a transient superconducting state upon optical excitation polarized along the c axis [R. Mankowsky et…”
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Semantic Nonnegative Matrix Factorization with Automatic Model Determination for Topic Modeling by Vangara, Raviteja, Skau, Erik, Chennupati, Gopinath, Djidjev, Hristo, Tierney, Thomas, Smith, James P., Bhattarai, Manish, Stanev, Valentin G., Alexandrov, Boian S.

“…Non-negative Matrix Factorization (NMF) models the topics of a text corpus by decomposing the matrix of term frequency-inverse document frequency (TF-IDF)…”
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