The fast simulation of dynamical systems is a key challenge in many scientific and engineering applications, such as weather forecasting, disease control, and drug discovery. With the recent success of deep learning, there is increasing interest in using neural networks to solve differential equations in a data-driven manner. However, existing methods are either limited to specific types of differential equations or require large amounts of data for training. This restricts their practicality in many real-world applications, where data is often scarce or expensive to obtain. To address this, a novel multi-modal foundation model, named FMint (Foundation Model based on Initialization) is proposed, to bridge the gap between human-designed and data-driven models for the fast simulation of dynamical systems. Built on a decoder-only transformer architecture with in-context learning, FMint utilizes both numerical and textual data to learn a universal error correction scheme for dynamical systems, using prompted sequences of coarse solutions from traditional solvers. The model is pre-trained on a corpus of 400K ordinary differential equations (ODEs), and extensive experiments are performed on challenging ODEs that exhibit chaotic behavior and of high dimensionality. The results demonstrate the effectiveness of the proposed model in terms of both accuracy and efficiency compared to classical numerical solvers, highlighting FMint's potential as a general-purpose solver for dynamical systems. This approach achieves an accuracy improvement of 1 to 2 orders of magnitude over state-of-the-art dynamical system simulators, and delivers a 5X speedup compared to traditional numerical algorithms. The code for FMint is available at https://github.com/margotyjx/FMint.
{"title":"FMint: Bridging Human Designed and Data Pretrained Models for Differential Equation Foundation Model for Dynamical Simulation","authors":"Zezheng Song, Jiaxin Yuan, Haizhao Yang","doi":"10.1002/adts.202500062","DOIUrl":"https://doi.org/10.1002/adts.202500062","url":null,"abstract":"The fast simulation of dynamical systems is a key challenge in many scientific and engineering applications, such as weather forecasting, disease control, and drug discovery. With the recent success of deep learning, there is increasing interest in using neural networks to solve differential equations in a data-driven manner. However, existing methods are either limited to specific types of differential equations or require large amounts of data for training. This restricts their practicality in many real-world applications, where data is often scarce or expensive to obtain. To address this, a novel multi-modal foundation model, named <b>FMint</b> (<b>F</b>oundation <b>M</b>odel based on <b>In</b>i<b>t</b>ialization) is proposed, to bridge the gap between human-designed and data-driven models for the fast simulation of dynamical systems. Built on a decoder-only transformer architecture with in-context learning, FMint utilizes both numerical and textual data to learn a universal error correction scheme for dynamical systems, using prompted sequences of coarse solutions from traditional solvers. The model is pre-trained on a corpus of 400K ordinary differential equations (ODEs), and extensive experiments are performed on challenging ODEs that exhibit chaotic behavior and of high dimensionality. The results demonstrate the effectiveness of the proposed model in terms of both accuracy and efficiency compared to classical numerical solvers, highlighting FMint's potential as a general-purpose solver for dynamical systems. This approach achieves an accuracy improvement of 1 to 2 orders of magnitude over state-of-the-art dynamical system simulators, and delivers a 5X speedup compared to traditional numerical algorithms. The code for FMint is available at https://github.com/margotyjx/FMint.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"96 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143775869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hossein Tavakol, Sima shamsaddinimotlagh, Arash Kazemi, Min Shi
In this report, the reaction mechanism of triphenylphosphite addition to β-nitrostyrene is theoretically investigated. The M062X method, a subset of density functional theory (DFT), and the def2svp basis set are used to determine the appropriate mechanism. Three plausible mechanistic routes, labeled pathways A, B, and C, are proposed. In pathway A, triphenyl phosphite is added to the β-position of β-nitrostyrene. Pathway B involves the addition of the triphenyl phosphite molecule to the oxygen of the nitro group in β-nitrostyrene. In pathway C, triphenyl phosphite is added to the nitrogen of the β-nitrostyrene compound. Since the reaction requires the presence of two mmol of triphenyl phosphite to form the desired product, all three routes of the proposed mechanism are designed accordingly. In the gas phase, the overall energy barriers of paths A and B are 19.31 and 43.47 kcal mol−1, respectively, while no reliable transition state is obtained for path C. For path A in different solvents, the overall energy barriers are 20.75, 20.76, and 20.76 kcal mol−1, respectively in water, methanol, and dimethylformamide. Therefore, path A is a more favorable path, and there is not a meaningful difference between the results of the gas phase and different solvents.
{"title":"DFT Study of the Possible Mechanisms for Synthesizing α-Cyanophosphonates from β-Nitrostyrenes","authors":"Hossein Tavakol, Sima shamsaddinimotlagh, Arash Kazemi, Min Shi","doi":"10.1002/adts.202500379","DOIUrl":"https://doi.org/10.1002/adts.202500379","url":null,"abstract":"In this report, the reaction mechanism of triphenylphosphite addition to <i>β</i>-nitrostyrene is theoretically investigated. The M062X method, a subset of density functional theory (DFT), and the def2svp basis set are used to determine the appropriate mechanism. Three plausible mechanistic routes, labeled pathways <b>A</b>, <b>B</b>, and <b>C</b>, are proposed. In pathway <b>A</b>, triphenyl phosphite is added to the <i>β</i>-position of <i>β</i>-nitrostyrene. Pathway <b>B</b> involves the addition of the triphenyl phosphite molecule to the oxygen of the nitro group in <i>β</i>-nitrostyrene. In pathway <b>C</b>, triphenyl phosphite is added to the nitrogen of the <i>β</i>-nitrostyrene compound. Since the reaction requires the presence of two mmol of triphenyl phosphite to form the desired product, all three routes of the proposed mechanism are designed accordingly. In the gas phase, the overall energy barriers of paths <b>A</b> and <b>B</b> are 19.31 and 43.47 kcal mol<sup>−1</sup>, respectively, while no reliable transition state is obtained for path <b>C</b>. For path <b>A</b> in different solvents, the overall energy barriers are 20.75, 20.76, and 20.76 kcal mol<sup>−1</sup>, respectively in water, methanol, and dimethylformamide. Therefore, path <b>A</b> is a more favorable path, and there is not a meaningful difference between the results of the gas phase and different solvents.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"80 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143775868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sonia Chebouki, Ouarda Nemiri, Faycal Oumelaz, Djamel Boudjaadar, Akila Boumaza, Rabab Benredouane, Şule Uğur, A. K. Kushwaha, Gökay Uğur
Based on DFT computation, the physical properties of newlead-free double perovskites (DPs) X2CdZnCl6 (X = Na and K) is carried out within WIEN2K software. The measured formation energy (ΔEf) and tolerance factor indicate the cubic structure stabilities of investigated materials. The lattice parameters of the compounds Na2CdZnCl6 and K2CdZnCl6 are equal to 9.98 A° and 10.05 A°, respectively. The examination of the electronic structure through nKTB-mBJ demonstrates that lead free DPs X2CdZnCl6 (X = Na and K) exhibit semiconducting behavior with direct bandgap energy. The analysis of optical parameters reveal that the examined compounds have a stronger absorption property in UV region and make them well suited for photovoltaic devices and next-generation technologies. Additionally, using BoltzTrap code, the thermoelectric characteristics are thoroughly examined. The highest Seebeck coefficient values 218.32 and 254.29 µV K−1 for X = Na and K, respectively. According to calculations, the maximum ZT values of 0.7 for Na2CdZnCl6 and 0.73 for K2CdZnCl6 indicate their potential as promising materials for thermoelectric devices. The acquired figure of merit (ZT) values indictes that examined lead free DPs X2CdZnCl6 (X = Na and K) exhibit potential for implementation in thermoelectric devices.
{"title":"Computational Exploration of Innovative Lead-Free DPs X2CdZnCl6 (X = Na and K) DFT Analysis of Optoelectronic, Mechanical and Thermoelectric Performance","authors":"Sonia Chebouki, Ouarda Nemiri, Faycal Oumelaz, Djamel Boudjaadar, Akila Boumaza, Rabab Benredouane, Şule Uğur, A. K. Kushwaha, Gökay Uğur","doi":"10.1002/adts.202401540","DOIUrl":"https://doi.org/10.1002/adts.202401540","url":null,"abstract":"Based on DFT computation, the physical properties of newlead-free double perovskites (DPs) X<sub>2</sub>CdZnCl<sub>6</sub> (X = Na and K) is carried out within WIEN2K software. The measured formation energy (ΔE<sub>f</sub>) and tolerance factor indicate the cubic structure stabilities of investigated materials. The lattice parameters of the compounds Na<sub>2</sub>CdZnCl<sub>6</sub> and K<sub>2</sub>CdZnCl<sub>6</sub> are equal to 9.98 A° and 10.05 A°, respectively. The examination of the electronic structure through nKTB-mBJ demonstrates that lead free DPs X<sub>2</sub>CdZnCl<sub>6</sub> (X = Na and K) exhibit semiconducting behavior with direct bandgap energy. The analysis of optical parameters reveal that the examined compounds have a stronger absorption property in UV region and make them well suited for photovoltaic devices and next-generation technologies. Additionally, using BoltzTrap code, the thermoelectric characteristics are thoroughly examined. The highest Seebeck coefficient values 218.32 and 254.29 µV K<sup>−1</sup> for X = Na and K, respectively. According to calculations, the maximum ZT values of 0.7 for Na<sub>2</sub>CdZnCl<sub>6</sub> and 0.73 for K<sub>2</sub>CdZnCl<sub>6</sub> indicate their potential as promising materials for thermoelectric devices. The acquired figure of merit (ZT) values indictes that examined lead free DPs X<sub>2</sub>CdZnCl<sub>6</sub> (X = Na and K) exhibit potential for implementation in thermoelectric devices.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"9 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143758360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alkhumra virus, a zoonotic pathogen in the Flaviviridae family, causes severe hemorrhagic fever in humans, yet vaccines and drugs remain unavailable. The nonstructural protein 2B (NS2B)/nonstructural protein 3 (NS3) NS2B/NS3 protease, essential for virion maturation, represents a promising therapeutic target. Structural and dynamical changes induced by NS2B cofactor binding to the NS3 protein are examined using all-atom molecular dynamics simulations. NS2B binding reduces the flexibility of NS3, particularly in contact regions, without altering its secondary structure. Non-bonding van der Waals and electrostatic interactions are identified as the primary driving forces in cofactor binding. The protonation states of catalytic triad residues significantly affect the active pocket's geometry. A drug repurposing campaign utilizing ensemble docking and molecular dynamics simulations identified three DrugBank compounds as potential NS2B/NS3 protease inhibitors. The catalytic serine residue with a deprotonated hydroxyl group contributes most significantly to the free energy of binding. These findings provide a detailed understanding of the molecular interactions underlying ligand binding to NS2B/NS3, offering valuable insights for developing effective inhibitors.
{"title":"Insights into the Dynamics and Binding Mechanisms of the Alkhumra Virus NS2B/NS3 Protease: A Molecular Dynamics Study","authors":"Jurica Novak, Shivananda Kandagalla, Ramesh Sistla","doi":"10.1002/adts.202401406","DOIUrl":"https://doi.org/10.1002/adts.202401406","url":null,"abstract":"Alkhumra virus, a zoonotic pathogen in the Flaviviridae family, causes severe hemorrhagic fever in humans, yet vaccines and drugs remain unavailable. The nonstructural protein 2B (NS2B)/nonstructural protein 3 (NS3) NS2B/NS3 protease, essential for virion maturation, represents a promising therapeutic target. Structural and dynamical changes induced by NS2B cofactor binding to the NS3 protein are examined using all-atom molecular dynamics simulations. NS2B binding reduces the flexibility of NS3, particularly in contact regions, without altering its secondary structure. Non-bonding van der Waals and electrostatic interactions are identified as the primary driving forces in cofactor binding. The protonation states of catalytic triad residues significantly affect the active pocket's geometry. A drug repurposing campaign utilizing ensemble docking and molecular dynamics simulations identified three DrugBank compounds as potential NS2B/NS3 protease inhibitors. The catalytic serine residue with a deprotonated hydroxyl group contributes most significantly to the free energy of binding. These findings provide a detailed understanding of the molecular interactions underlying ligand binding to NS2B/NS3, offering valuable insights for developing effective inhibitors.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"58 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143736903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenjing Liu, Jinrong Xu, Shulei Gong, Wenrui Huang, Jiahui Hao, Jiangying Yu, Kai Huang, Ying Wang
As fundamental quantum mechanical descriptors of crystalline lattice vibrational properties, phonons play a critical role in determining numerous macroscopic physical characteristics spanning thermal transport behavior and thermodynamic response functions. The precise determination of complete phonon spectra and their corresponding interatomic force constants continues to present substantial computational challenges, particularly in architecturally complex material systems. In this study, using graphene as a prototypical system, theoretical derivation of the phonon dispersion relations is presented through rigorous lattice dynamics formalism. The first- through eighth-nearest-neighbor force constants in the dynamical matrix are systematically determined via a self-consistent iterative genetic algorithm optimization framework. These derived parameters are further systematically validated through density functional theory simulations. The optimized interatomic force constants demonstrate remarkable fidelity in reproducing both the acoustic and optical phonon branches across the entire Brillouin zone, thereby establishing a comprehensive theoretical foundation for predictive calculations of temperature-dependent thermodynamic properties. The developed genetic algorithm optimization methodology shows significant transferability to diverse material systems, enabling precise alignment with inelastic neutron scattering and Raman spectroscopy measurements. This advancement provides a generalized computational tool for investigating lattice dynamics in complex material systems.
{"title":"Genetic Algorithm to Obtain Accurate Force Constants in Graphene","authors":"Wenjing Liu, Jinrong Xu, Shulei Gong, Wenrui Huang, Jiahui Hao, Jiangying Yu, Kai Huang, Ying Wang","doi":"10.1002/adts.202500124","DOIUrl":"https://doi.org/10.1002/adts.202500124","url":null,"abstract":"As fundamental quantum mechanical descriptors of crystalline lattice vibrational properties, phonons play a critical role in determining numerous macroscopic physical characteristics spanning thermal transport behavior and thermodynamic response functions. The precise determination of complete phonon spectra and their corresponding interatomic force constants continues to present substantial computational challenges, particularly in architecturally complex material systems. In this study, using graphene as a prototypical system, theoretical derivation of the phonon dispersion relations is presented through rigorous lattice dynamics formalism. The first- through eighth-nearest-neighbor force constants in the dynamical matrix are systematically determined via a self-consistent iterative genetic algorithm optimization framework. These derived parameters are further systematically validated through density functional theory simulations. The optimized interatomic force constants demonstrate remarkable fidelity in reproducing both the acoustic and optical phonon branches across the entire Brillouin zone, thereby establishing a comprehensive theoretical foundation for predictive calculations of temperature-dependent thermodynamic properties. The developed genetic algorithm optimization methodology shows significant transferability to diverse material systems, enabling precise alignment with inelastic neutron scattering and Raman spectroscopy measurements. This advancement provides a generalized computational tool for investigating lattice dynamics in complex material systems.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"63 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143723475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Asadul Islam Shimul, M. A. Khan, Abu Rayhan, Avijit Ghosh
Recent research focuses on enhancing the sustainability of perovskite solar cells (PSCs) by substituting lead with non-toxic materials, identifying tin-based perovskites such as CH3NH3SnBr3 as a viable alternative. This study examines the efficacy of CH3NH3SnBr3 as the absorber layer in conjunction with V2O5 as the hole transport layer (HTL) and several electron transport layers (ETLs), including C60, IGZO, WS2, and ZnSe. The study employs SCAPS-1D simulations to optimize parameters including doping concentration, thickness, and defect density, aiming to improve photovoltaic efficiency. The optimal configuration (FTO/WS2/CH3NH3SnBr3/V2O5/Au) attained a power conversion efficiency (PCE) of 33.54%, surpassing alternative ETL combinations. The results of the SCAPS-1D simulation are analyzed in comparison to those of the wxAMPS simulation. The machine learning model is developed to predict solar cell performance, achieving an accuracy of 82%. The findings underscore the significance of choosing appropriate ETL to enhance PSC efficiency and sustainability.
{"title":"Machine Learning-Based Optimization and Performance Enhancement of CH3NH3SnBr3 Perovskite Solar Cells with Different Charge Transport Materials Using SCAPS-1D and wxAMPS","authors":"Asadul Islam Shimul, M. A. Khan, Abu Rayhan, Avijit Ghosh","doi":"10.1002/adts.202500182","DOIUrl":"https://doi.org/10.1002/adts.202500182","url":null,"abstract":"Recent research focuses on enhancing the sustainability of perovskite solar cells (PSCs) by substituting lead with non-toxic materials, identifying tin-based perovskites such as CH<sub>3</sub>NH<sub>3</sub>SnBr<sub>3</sub> as a viable alternative. This study examines the efficacy of CH<sub>3</sub>NH<sub>3</sub>SnBr<sub>3</sub> as the absorber layer in conjunction with V<sub>2</sub>O<sub>5</sub> as the hole transport layer (HTL) and several electron transport layers (ETLs), including C<sub>60</sub>, IGZO, WS<sub>2</sub>, and ZnSe. The study employs SCAPS-1D simulations to optimize parameters including doping concentration, thickness, and defect density, aiming to improve photovoltaic efficiency. The optimal configuration (FTO/WS<sub>2</sub>/CH<sub>3</sub>NH<sub>3</sub>SnBr<sub>3</sub>/V<sub>2</sub>O<sub>5</sub>/Au) attained a power conversion efficiency (PCE) of 33.54%, surpassing alternative ETL combinations. The results of the SCAPS-1D simulation are analyzed in comparison to those of the wxAMPS simulation. The machine learning model is developed to predict solar cell performance, achieving an accuracy of 82%. The findings underscore the significance of choosing appropriate ETL to enhance PSC efficiency and sustainability.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"21 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143695613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jianing Liu, Yingying Li, Junling Qiu, Xuefei Feng, Kaizhe Fan
Superconducting Josephson junctions, as integral components of quantum circuits, are vital for the production of high-quality, reproducible, and scalable quantum chips. The aluminum tunnel junctions is currently regarded as one of the most high-performing and well-established Josephson junctions for application in quantum devices. Nonetheless, the critical current of the junctions is highly sensitive to its thickness, which significantly influences both the tunneling effect and the electrical properties of the device. This study develops a numerical model of the 3D Al/<span data-altimg="/cms/asset/7add7f3e-ee64-4158-b4e9-b4b9ded75f62/adts202401315-math-0003.png"></span><mjx-container ctxtmenu_counter="10" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidden="true" location="graphic/adts202401315-math-0003.png"><mjx-semantics><mjx-mi data-semantic-annotation="clearspeak:simple" data-semantic-font="italic" data-semantic- data-semantic-role="greekletter" data-semantic-speech="alpha" data-semantic-type="identifier"><mjx-c></mjx-c></mjx-mi></mjx-semantics></mjx-math><mjx-assistive-mml display="inline" unselectable="on"><math altimg="urn:x-wiley:25130390:media:adts202401315:adts202401315-math-0003" display="inline" location="graphic/adts202401315-math-0003.png" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mi data-semantic-="" data-semantic-annotation="clearspeak:simple" data-semantic-font="italic" data-semantic-role="greekletter" data-semantic-speech="alpha" data-semantic-type="identifier">α</mi>$alpha$</annotation></semantics></math></mjx-assistive-mml></mjx-container>-<span data-altimg="/cms/asset/08d9e0d2-862b-415d-b413-4c41ae1b5a2f/adts202401315-math-0004.png"></span><mjx-container ctxtmenu_counter="11" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidden="true" location="graphic/adts202401315-math-0004.png"><mjx-semantics><mjx-mrow data-semantic-annotation="clearspeak:unit" data-semantic-children="2,5" data-semantic-content="6" data-semantic- data-semantic-role="implicit" data-semantic-speech="upper A l 2 normal upper O 3" data-semantic-type="infixop"><mjx-msub data-semantic-children="0,1" data-semantic- data-semantic-parent="7" data-semantic-role="unknown" data-semantic-type="subscript"><mjx-mi data-semantic-font="normal" data-semantic- data-semantic-parent="2" data-semantic-role="unknown" data-semantic-type="identifier"><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mi><mjx-script style="vertical-align: -0.15em;"><mjx-mn data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic- data-semantic-parent="2" data-semantic-role="integer" data-semantic-type="number" size="s"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msub><mjx-mo data-semantic-added="true" data-semantic- data-semantic-operator="infixop," data-semantic-parent="7" data
{"title":"A COMSOL-Based Study of the Electrical Transport Properties of Al/α-Al2O3/Al Josephson Junctions","authors":"Jianing Liu, Yingying Li, Junling Qiu, Xuefei Feng, Kaizhe Fan","doi":"10.1002/adts.202401315","DOIUrl":"https://doi.org/10.1002/adts.202401315","url":null,"abstract":"Superconducting Josephson junctions, as integral components of quantum circuits, are vital for the production of high-quality, reproducible, and scalable quantum chips. The aluminum tunnel junctions is currently regarded as one of the most high-performing and well-established Josephson junctions for application in quantum devices. Nonetheless, the critical current of the junctions is highly sensitive to its thickness, which significantly influences both the tunneling effect and the electrical properties of the device. This study develops a numerical model of the 3D Al/<span data-altimg=\"/cms/asset/7add7f3e-ee64-4158-b4e9-b4b9ded75f62/adts202401315-math-0003.png\"></span><mjx-container ctxtmenu_counter=\"10\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/adts202401315-math-0003.png\"><mjx-semantics><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"italic\" data-semantic- data-semantic-role=\"greekletter\" data-semantic-speech=\"alpha\" data-semantic-type=\"identifier\"><mjx-c></mjx-c></mjx-mi></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:25130390:media:adts202401315:adts202401315-math-0003\" display=\"inline\" location=\"graphic/adts202401315-math-0003.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mi data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"italic\" data-semantic-role=\"greekletter\" data-semantic-speech=\"alpha\" data-semantic-type=\"identifier\">α</mi>$alpha$</annotation></semantics></math></mjx-assistive-mml></mjx-container>-<span data-altimg=\"/cms/asset/08d9e0d2-862b-415d-b413-4c41ae1b5a2f/adts202401315-math-0004.png\"></span><mjx-container ctxtmenu_counter=\"11\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/adts202401315-math-0004.png\"><mjx-semantics><mjx-mrow data-semantic-annotation=\"clearspeak:unit\" data-semantic-children=\"2,5\" data-semantic-content=\"6\" data-semantic- data-semantic-role=\"implicit\" data-semantic-speech=\"upper A l 2 normal upper O 3\" data-semantic-type=\"infixop\"><mjx-msub data-semantic-children=\"0,1\" data-semantic- data-semantic-parent=\"7\" data-semantic-role=\"unknown\" data-semantic-type=\"subscript\"><mjx-mi data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"identifier\"><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mi><mjx-script style=\"vertical-align: -0.15em;\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\" size=\"s\"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msub><mjx-mo data-semantic-added=\"true\" data-semantic- data-semantic-operator=\"infixop,\" data-semantic-parent=\"7\" data","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"70 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, the calculation of average and orbital energies for the ground and excited configurations of five-electron quantum dots (QDs) is performed using the Quantum Genetic Algorithm (QGA) and Hartree-Fock Roothaan (HFR) methods. The average Coulomb and exchange energies of electron pairs, along with one-electron kinetic and Coulomb potential energies, are calculated as a function of the dot radius. A penetrable confinement potential is used as a model to investigate the effects of confinement on both average and orbital energies. Furthermore, this study examines how confinement influences electron probability densities inside and outside the quantum well for ground and excited state configurations. Additionally, the configuration-average binding energy is computed at two different values of the confinement potential. The main conclusion is that the average energy and binding energy go up when the confinement radius is reduced and eventually reach at a fixed value. Other energies rise steadily until reaching their maximum values, after which they decline rapidly as the dot radius continues to decrease. For configurations <span data-altimg="/cms/asset/5e24a8e6-5333-4576-b8f2-d6170b96ceea/adts202401375-math-0001.png"></span><mjx-container ctxtmenu_counter="159" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidden="true" location="graphic/adts202401375-math-0001.png"><mjx-semantics><mjx-mrow data-semantic-annotation="clearspeak:unit" data-semantic-children="0,3,4,7,8,9" data-semantic-content="10,11,12,13,14" data-semantic- data-semantic-role="implicit" data-semantic-speech="1 normal s squared 2 normal s squared n l" data-semantic-type="infixop"><mjx-mn data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic- data-semantic-parent="15" data-semantic-role="integer" data-semantic-type="number"><mjx-c></mjx-c></mjx-mn><mjx-mo data-semantic-added="true" data-semantic- data-semantic-operator="infixop," data-semantic-parent="15" data-semantic-role="multiplication" data-semantic-type="operator" style="margin-left: 0.056em; margin-right: 0.056em;"><mjx-c></mjx-c></mjx-mo><mjx-msup data-semantic-children="1,2" data-semantic- data-semantic-parent="15" data-semantic-role="latinletter" data-semantic-type="superscript"><mjx-mi data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic- data-semantic-parent="3" data-semantic-role="latinletter" data-semantic-type="identifier"><mjx-c></mjx-c></mjx-mi><mjx-script style="vertical-align: 0.363em;"><mjx-mn data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic- data-semantic-parent="3" data-semantic-role="integer" data-semantic-type="number" size="s"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msup><mjx-mo data-semantic-added="true" data-semantic- data-semantic-operator="infixop," data-semantic-parent="15" data-semantic-role="mu
{"title":"Analysis of Electronic Structure and Binding Energy in Five-Electron GaAs/AlxGa1-xAs Quantum Dots Under Penetrable Confinement Potential","authors":"Yusuf Yakar, Bekir Çakır, Ayhan Özmen","doi":"10.1002/adts.202401375","DOIUrl":"https://doi.org/10.1002/adts.202401375","url":null,"abstract":"In this study, the calculation of average and orbital energies for the ground and excited configurations of five-electron quantum dots (QDs) is performed using the Quantum Genetic Algorithm (QGA) and Hartree-Fock Roothaan (HFR) methods. The average Coulomb and exchange energies of electron pairs, along with one-electron kinetic and Coulomb potential energies, are calculated as a function of the dot radius. A penetrable confinement potential is used as a model to investigate the effects of confinement on both average and orbital energies. Furthermore, this study examines how confinement influences electron probability densities inside and outside the quantum well for ground and excited state configurations. Additionally, the configuration-average binding energy is computed at two different values of the confinement potential. The main conclusion is that the average energy and binding energy go up when the confinement radius is reduced and eventually reach at a fixed value. Other energies rise steadily until reaching their maximum values, after which they decline rapidly as the dot radius continues to decrease. For configurations <span data-altimg=\"/cms/asset/5e24a8e6-5333-4576-b8f2-d6170b96ceea/adts202401375-math-0001.png\"></span><mjx-container ctxtmenu_counter=\"159\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/adts202401375-math-0001.png\"><mjx-semantics><mjx-mrow data-semantic-annotation=\"clearspeak:unit\" data-semantic-children=\"0,3,4,7,8,9\" data-semantic-content=\"10,11,12,13,14\" data-semantic- data-semantic-role=\"implicit\" data-semantic-speech=\"1 normal s squared 2 normal s squared n l\" data-semantic-type=\"infixop\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"15\" data-semantic-role=\"integer\" data-semantic-type=\"number\"><mjx-c></mjx-c></mjx-mn><mjx-mo data-semantic-added=\"true\" data-semantic- data-semantic-operator=\"infixop,\" data-semantic-parent=\"15\" data-semantic-role=\"multiplication\" data-semantic-type=\"operator\" style=\"margin-left: 0.056em; margin-right: 0.056em;\"><mjx-c></mjx-c></mjx-mo><mjx-msup data-semantic-children=\"1,2\" data-semantic- data-semantic-parent=\"15\" data-semantic-role=\"latinletter\" data-semantic-type=\"superscript\"><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"3\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\"><mjx-c></mjx-c></mjx-mi><mjx-script style=\"vertical-align: 0.363em;\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"3\" data-semantic-role=\"integer\" data-semantic-type=\"number\" size=\"s\"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msup><mjx-mo data-semantic-added=\"true\" data-semantic- data-semantic-operator=\"infixop,\" data-semantic-parent=\"15\" data-semantic-role=\"mu","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"9 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：