Pub Date : 2026-01-15DOI: 10.1016/j.mtphys.2026.102022
Umair Haider, Gul Rahman, Imran Shakir, M.S. Al-Buriahi, Norah Alomayrah, Imen Kebaili
We implement a reliable and generalizable multistep workflow that leverages supervised machine learning algorithms to construct accurate, data-driven models for predicting the work function (WF) of 4000 MM’XT<span><span style=""></span><span data-mathml='<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true" /><mrow is="true"><mn is="true">2</mn></mrow></msub></math>' role="presentation" style="font-size: 90%; display: inline-block; position: relative;" tabindex="0"><svg aria-hidden="true" focusable="false" height="1.509ex" role="img" style="vertical-align: -0.582ex;" viewbox="0 -399.4 453.9 649.8" width="1.054ex" xmlns:xlink="http://www.w3.org/1999/xlink"><g fill="currentColor" stroke="currentColor" stroke-width="0" transform="matrix(1 0 0 -1 0 0)"><g is="true"><g is="true"></g><g is="true" transform="translate(0,-150)"><g is="true"><use transform="scale(0.707)" xlink:href="#MJMAIN-32"></use></g></g></g></g></svg><span role="presentation"><math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"></mrow><mrow is="true"><mn is="true">2</mn></mrow></msub></math></span></span><script type="math/mml"><math><msub is="true"><mrow is="true"></mrow><mrow is="true"><mn is="true">2</mn></mrow></msub></math></script></span>-type MXenes. Among the tested models, the <em>random forest regressor</em> demonstrates excellent performance, achieving a mean absolute error of 0.03 eV on the training set and 0.09 eV on the test set. Remarkably, through recursive feature elimination and hyperparameter tuning, the model attains even higher accuracy with only ten key descriptors, reducing the test MAE to 0.02 eV. The optimized model is employed to predict the properties of 150 unexplored MXenes for applications in catalysis (86 MXenes), electronics (38 MXenes), and energy storage (26 MXenes). The low–WF energy-storage candidates are dominated by nitride- and halide-terminated species, often incorporating early transition metals or rare-earth elements such as Y, Sc, and Hf. The intermediate-WF window contains compositions with balanced metallic and semiconducting features, such as <span><span style=""></span><span data-mathml='<math xmlns="http://www.w3.org/1998/Math/MathML"><msub is="true"><mrow is="true"><mi mathvariant="normal" is="true">TiZrNCl</mi></mrow><mrow is="true"><mn is="true">2</mn></mrow></msub></math>' role="presentation" style="font-size: 90%; display: inline-block; position: relative;" tabindex="0"><svg aria-hidden="true" focusable="false" height="2.432ex" role="img" style="vertical-align: -0.582ex;" viewbox="0 -796.9 4210.4 1047.3" width="9.779ex" xmlns:xlink="http://www.w3.org/1999/xlink"><g fill="currentColor" stroke="currentColor" stroke-width="0" transform="matrix(1 0 0 -1 0 0)"><g is="true"><g is="true"><g is="true"><use xlink:href="#MJMAIN-54"></use><use x="722" xlink:href="#
{"title":"Accelerated discovery of MM’XT2 MXenes for catalysis, electronics, and energy storage using supervised machine learning","authors":"Umair Haider, Gul Rahman, Imran Shakir, M.S. Al-Buriahi, Norah Alomayrah, Imen Kebaili","doi":"10.1016/j.mtphys.2026.102022","DOIUrl":"https://doi.org/10.1016/j.mtphys.2026.102022","url":null,"abstract":"We implement a reliable and generalizable multistep workflow that leverages supervised machine learning algorithms to construct accurate, data-driven models for predicting the work function (WF) of 4000 MM’XT<span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><msub is=\"true\"><mrow is=\"true\" /><mrow is=\"true\"><mn is=\"true\">2</mn></mrow></msub></math>' role=\"presentation\" style=\"font-size: 90%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"1.509ex\" role=\"img\" style=\"vertical-align: -0.582ex;\" viewbox=\"0 -399.4 453.9 649.8\" width=\"1.054ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><g is=\"true\"><g is=\"true\"></g><g is=\"true\" transform=\"translate(0,-150)\"><g is=\"true\"><use transform=\"scale(0.707)\" xlink:href=\"#MJMAIN-32\"></use></g></g></g></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><msub is=\"true\"><mrow is=\"true\"></mrow><mrow is=\"true\"><mn is=\"true\">2</mn></mrow></msub></math></span></span><script type=\"math/mml\"><math><msub is=\"true\"><mrow is=\"true\"></mrow><mrow is=\"true\"><mn is=\"true\">2</mn></mrow></msub></math></script></span>-type MXenes. Among the tested models, the <em>random forest regressor</em> demonstrates excellent performance, achieving a mean absolute error of 0.03 eV on the training set and 0.09 eV on the test set. Remarkably, through recursive feature elimination and hyperparameter tuning, the model attains even higher accuracy with only ten key descriptors, reducing the test MAE to 0.02 eV. The optimized model is employed to predict the properties of 150 unexplored MXenes for applications in catalysis (86 MXenes), electronics (38 MXenes), and energy storage (26 MXenes). The low–WF energy-storage candidates are dominated by nitride- and halide-terminated species, often incorporating early transition metals or rare-earth elements such as Y, Sc, and Hf. The intermediate-WF window contains compositions with balanced metallic and semiconducting features, such as <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><msub is=\"true\"><mrow is=\"true\"><mi mathvariant=\"normal\" is=\"true\">TiZrNCl</mi></mrow><mrow is=\"true\"><mn is=\"true\">2</mn></mrow></msub></math>' role=\"presentation\" style=\"font-size: 90%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"2.432ex\" role=\"img\" style=\"vertical-align: -0.582ex;\" viewbox=\"0 -796.9 4210.4 1047.3\" width=\"9.779ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><g is=\"true\"><g is=\"true\"><g is=\"true\"><use xlink:href=\"#MJMAIN-54\"></use><use x=\"722\" xlink:href=\"#","PeriodicalId":18253,"journal":{"name":"Materials Today Physics","volume":"178 1","pages":""},"PeriodicalIF":11.5,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145993423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-14DOI: 10.1016/j.mtphys.2026.102021
Yaran Shi , Ze Yang , Xiaohui Li , Zhouzhou Wang , Xue Dong , Wenzhu Cao , Chenchen Wei , Zhixuan Huang , Zijun Sun , Yan Jiang , Ying Yu
Sn-based aqueous acidic batteries (SnAABs) as a new type of non-toxicity, acid-resistant, and ease of recycling batteries, face the challenges of inhomogeneous Sn deposition and excessive hydrogen evolution reaction (HER) in acidic electrolytes, leading to its fast failure. Herein, current density has been identified as a key parameter for tuning Sn2+ nucleation and mass-transfer processes simultaneously on Sn anode. Both low current densities (LCD) and high current densities (HCD) resulted in poor plating/stripping stability due to inhomogeneous deposition and excessive HER. The optimal stability was achieved at moderate current densities (MCD), which balanced the nucleation and mass-transfer processes. As such, the Sn symmetrical cell exhibited stable cycling for 1000 h with a voltage polarization of 47 mV at the MCD, which remarkably surpassed the performances under the LCD (110 h) and the HCD (68 h). This work provides fundamental and practical insights for designing highly stable metal anodes.
{"title":"Balancing nucleation and mass-transfer processes through regulating current density for stable aqueous Sn anode batteries","authors":"Yaran Shi , Ze Yang , Xiaohui Li , Zhouzhou Wang , Xue Dong , Wenzhu Cao , Chenchen Wei , Zhixuan Huang , Zijun Sun , Yan Jiang , Ying Yu","doi":"10.1016/j.mtphys.2026.102021","DOIUrl":"10.1016/j.mtphys.2026.102021","url":null,"abstract":"<div><div>Sn-based aqueous acidic batteries (SnAABs) as a new type of non-toxicity, acid-resistant, and ease of recycling batteries, face the challenges of inhomogeneous Sn deposition and excessive hydrogen evolution reaction (HER) in acidic electrolytes, leading to its fast failure. Herein, current density has been identified as a key parameter for tuning Sn<sup>2+</sup> nucleation and mass-transfer processes simultaneously on Sn anode. Both low current densities (LCD) and high current densities (HCD) resulted in poor plating/stripping stability due to inhomogeneous deposition and excessive HER. The optimal stability was achieved at moderate current densities (MCD), which balanced the nucleation and mass-transfer processes. As such, the Sn symmetrical cell exhibited stable cycling for 1000 h with a voltage polarization of 47 mV at the MCD, which remarkably surpassed the performances under the LCD (110 h) and the HCD (68 h). This work provides fundamental and practical insights for designing highly stable metal anodes.</div></div>","PeriodicalId":18253,"journal":{"name":"Materials Today Physics","volume":"61 ","pages":"Article 102021"},"PeriodicalIF":9.7,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145962499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-13DOI: 10.1016/j.mtphys.2026.102019
Zhi-Yuan Qiu , Zheng-Tang Liu , Qi-Jun Liu
Exploring new types of high-temperature superconductors has always been a central topic in condensed matter physics and materials science. This study breaks through the traditional element substitution strategy and takes boron-carbon compound MB4C4 as the parent structure, innovatively proposing a new material design paradigm of "structural isomer engineering (SIE)". Through first-principles calculations, it systematically studies the structural isomers MC4B4 formed after the positions of B and C atoms are swapped. We conducted a high-throughput screening of 59 compounds and found that only SiC4B4 and BeC4B4 can maintain kinetic stability at normal pressure. SiC4B4 is an electron semiconductor similar to diamond, while BeC4B4 is predicted to be a new type of high-temperature superconductor with a superconducting transition temperature (TC) of up to 87.52 K. Particularly noteworthy is that its TC exhibits remarkable robustness compared to the original BeB4C4 (∼76–83 K). The analysis of the electronic structure reveals that the difference in physical properties is attributed to the degree of electron filling in the framework. The in-depth microscopic mechanism study indicates that the high-temperature superconductivity of BeC4B4 stems from an unprecedented "dynamic donor-skeleton framework coupling" mechanism. The strong electron-phonon coupling (EPC) ( = 1.76) is mainly contributed by the high-frequency collective vibration mode driven by the light Be2+ ions, which efficiently couples with the delocalized electrons of the electron-deficient B-C framework. Based on this, we constructed a two-dimensional design descriptor centered on "donor-skeleton coupling degree " and "electron filling degree (Ntot)", successfully explaining the superconducting trend of MB4C4 and its isomer systems, and providing a universal blueprint for systematically searching for new high-temperature superconductors driven by dynamic ionic coupling in three-dimensional rigid covalent frameworks.
{"title":"Structural isomer engineering to create novel high TC: Predicting the dynamic donor-skeleton coupling mechanism of superconducting BeC4B4","authors":"Zhi-Yuan Qiu , Zheng-Tang Liu , Qi-Jun Liu","doi":"10.1016/j.mtphys.2026.102019","DOIUrl":"10.1016/j.mtphys.2026.102019","url":null,"abstract":"<div><div>Exploring new types of high-temperature superconductors has always been a central topic in condensed matter physics and materials science. This study breaks through the traditional element substitution strategy and takes boron-carbon compound MB<sub>4</sub>C<sub>4</sub> as the parent structure, innovatively proposing a new material design paradigm of \"structural isomer engineering (SIE)\". Through first-principles calculations, it systematically studies the structural isomers MC<sub>4</sub>B<sub>4</sub> formed after the positions of B and C atoms are swapped. We conducted a high-throughput screening of 59 compounds and found that only SiC<sub>4</sub>B<sub>4</sub> and BeC<sub>4</sub>B<sub>4</sub> can maintain kinetic stability at normal pressure. SiC<sub>4</sub>B<sub>4</sub> is an electron semiconductor similar to diamond, while BeC<sub>4</sub>B<sub>4</sub> is predicted to be a new type of high-temperature superconductor with a superconducting transition temperature (<em>T</em><sub><em>C</em></sub>) of up to 87.52 K. Particularly noteworthy is that its <em>T</em><sub><em>C</em></sub> exhibits remarkable robustness compared to the original BeB<sub>4</sub>C<sub>4</sub> (∼76–83 K). The analysis of the electronic structure reveals that the difference in physical properties is attributed to the degree of electron filling in the framework. The in-depth microscopic mechanism study indicates that the high-temperature superconductivity of BeC<sub>4</sub>B<sub>4</sub> stems from an unprecedented \"dynamic donor-skeleton framework coupling\" mechanism. The strong electron-phonon coupling (EPC) (<span><math><mrow><mi>λ</mi></mrow></math></span> = 1.76) is mainly contributed by the high-frequency collective vibration mode driven by the light Be<sup>2+</sup> ions, which efficiently couples with the delocalized electrons of the electron-deficient B-C framework. Based on this, we constructed a two-dimensional design descriptor centered on \"donor-skeleton coupling degree <span><math><mrow><mo>(</mo><msub><mi>Γ</mi><mi>X</mi></msub><mo>)</mo></mrow></math></span>\" and \"electron filling degree (<em>N</em><sub><em>tot</em></sub>)\", successfully explaining the superconducting trend of MB<sub>4</sub>C<sub>4</sub> and its isomer systems, and providing a universal blueprint for systematically searching for new high-temperature superconductors driven by dynamic ionic coupling in three-dimensional rigid covalent frameworks.</div></div>","PeriodicalId":18253,"journal":{"name":"Materials Today Physics","volume":"61 ","pages":"Article 102019"},"PeriodicalIF":9.7,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-13DOI: 10.1016/j.mtphys.2025.102006
A. El Alouani, M. Al Khalfioui, A. Michon, S. Vézian, P. Boucaud, M.T. Dau
Regressive Machine learning (ML) has emerged as an alternative method for theoretically evaluating materials properties. Most of ML-based study of materials properties including dataset handling, feature spaces, transformers and estimators have been reported without questioning the ML foundation of these components and their interactions with the outcomes because of the availability of homogeneous datasets, standardized training conditions and technical implementation challenges. In this paper, a database of defect impurities in 2D materials was used to assess the impact of ML workflow’s components on the training-inference process. By investigating descriptor engineering (vectorized matrix properties) and model algorithms (statistical tree-based and artificial neural network - ANN models) on two sub-datasets derived from the database (interstitial-int and adsorbate-ads impurities), we report a comprehensive study of the ML-based prediction of the energy formation of the impurities in 2D materials. Quantitatively, for the statistical models, the training errors lower than 1.4 eV and 1.1 eV were found thanks to the descriptor engineering for the int and the ads datasets, respectively. Regarding the ANN models, these values are 2.1 eV and 1.3 eV. The prediction errors on the unseen data (test sets) were found lower than the ones obtained without descriptor engineering for all models. However, the overfitting effect remains visible but less pronounced for the ads dataset than for the int dataset. This finding reveals the impact of the dataset characteristics on the performance of the ML ecosystem involving data engineering and model algorithms. Beyond the search of best performances in regressive ML prediction of 2D materials properties, our work demonstrates a full-scale study of the ML process starting from the data engineering to model evaluation and selection, allowing to benchmark the criteria for further ML assessment in terms of training, models and prediction. Our results could be reference for further works in ML-led prediction physics of materials science.
{"title":"Defect formation energy of impurities in 2D materials: How does data engineering shape machine learning model selection?","authors":"A. El Alouani, M. Al Khalfioui, A. Michon, S. Vézian, P. Boucaud, M.T. Dau","doi":"10.1016/j.mtphys.2025.102006","DOIUrl":"10.1016/j.mtphys.2025.102006","url":null,"abstract":"<div><div>Regressive Machine learning (ML) has emerged as an alternative method for theoretically evaluating materials properties. Most of ML-based study of materials properties including dataset handling, feature spaces, transformers and estimators have been reported without questioning the ML foundation of these components and their interactions with the outcomes because of the availability of homogeneous datasets, standardized training conditions and technical implementation challenges. In this paper, a database of defect impurities in 2D materials was used to assess the impact of ML workflow’s components on the training-inference process. By investigating descriptor engineering (vectorized matrix properties) and model algorithms (statistical tree-based and artificial neural network - ANN models) on two sub-datasets derived from the database (interstitial-int and adsorbate-ads impurities), we report a comprehensive study of the ML-based prediction of the energy formation of the impurities in 2D materials. Quantitatively, for the statistical models, the training errors lower than 1.4 eV and 1.1 eV were found thanks to the descriptor engineering for the int and the ads datasets, respectively. Regarding the ANN models, these values are 2.1 eV and 1.3 eV. The prediction errors on the unseen data (test sets) were found lower than the ones obtained without descriptor engineering for all models. However, the overfitting effect remains visible but less pronounced for the ads dataset than for the int dataset. This finding reveals the impact of the dataset characteristics on the performance of the ML ecosystem involving data engineering and model algorithms. Beyond the search of best performances in regressive ML prediction of 2D materials properties, our work demonstrates a full-scale study of the ML process starting from the data engineering to model evaluation and selection, allowing to benchmark the criteria for further ML assessment in terms of training, models and prediction. Our results could be reference for further works in ML-led prediction physics of materials science.</div></div>","PeriodicalId":18253,"journal":{"name":"Materials Today Physics","volume":"61 ","pages":"Article 102006"},"PeriodicalIF":9.7,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The development of high-performance infrared emissive materials is crucial for advancing energy utilization and thermal management technologies. To this end, we designed a series of Nd-doped CeO2 materials with different dopant concentrations to precisely modulate oxygen vacancy concentration and impurity incorporation. The introduction of Nd not only facilitates the dynamic transition between Ce3+ and Ce4+ but also generates abundant oxygen vacancies and induces significant lattice distortion. These synergistic effects collectively narrow the electronic bandgap, facilitate carrier transitions, and reduce vibrational symmetry, thereby enhancing phonon-infrared interactions. As a result, Ce-Nd07 nanoparticles achieved a broadband emissivity of 0.923 (2.5-15 μm), which further increased to 0.935 when the material was fabricated into Ce-Nd07@PDMS composite coating. Furthermore, simulated radiative cooling tests reveal a temperature drop of 8.3 °C with a cooling efficiency of 12.3%, confirming the exceptional radiative heat-dissipation capability. Additionally, the composite coating exhibits excellent UV resistance and hydrophobicity. These findings highlight a dual electronic-lattice engineering strategy for the development of next-generation radiative cooling materials.
{"title":"Enhanced Broadband Infrared Radiative Cooling of CeO2/PDMS Coating via Partial Substitution of Ce with Nd","authors":"Yu Duan, Mingrui Liu, Xianfeng Ye, Yu Liang, Danqi He, Zhijie Wei, Wanting Zhu, Yu Zhang, Wenyu Zhao, Qingjie Zhang","doi":"10.1016/j.mtphys.2026.102017","DOIUrl":"https://doi.org/10.1016/j.mtphys.2026.102017","url":null,"abstract":"The development of high-performance infrared emissive materials is crucial for advancing energy utilization and thermal management technologies. To this end, we designed a series of Nd-doped CeO<ce:inf loc=\"post\">2</ce:inf> materials with different dopant concentrations to precisely modulate oxygen vacancy concentration and impurity incorporation. The introduction of Nd not only facilitates the dynamic transition between Ce<ce:sup loc=\"post\">3+</ce:sup> and Ce<ce:sup loc=\"post\">4+</ce:sup> but also generates abundant oxygen vacancies and induces significant lattice distortion. These synergistic effects collectively narrow the electronic bandgap, facilitate carrier transitions, and reduce vibrational symmetry, thereby enhancing phonon-infrared interactions. As a result, Ce-Nd07 nanoparticles achieved a broadband emissivity of 0.923 (2.5-15 μm), which further increased to 0.935 when the material was fabricated into Ce-Nd07@PDMS composite coating. Furthermore, simulated radiative cooling tests reveal a temperature drop of 8.3 °C with a cooling efficiency of 12.3%, confirming the exceptional radiative heat-dissipation capability. Additionally, the composite coating exhibits excellent UV resistance and hydrophobicity. These findings highlight a dual electronic-lattice engineering strategy for the development of next-generation radiative cooling materials.","PeriodicalId":18253,"journal":{"name":"Materials Today Physics","volume":"51 1","pages":""},"PeriodicalIF":11.5,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.mtphys.2026.102016
Yijie Chen , Chunwei Zhang , Tong Wang , Guojun Li , Jiahui Lou , Qun Cao , Cheng Shao , Hongkun Li , Weidong Zheng
The group VI transition metal dichalcogenides (MoX2 and WX2, X = chalcogen) have attracted considerable interest for next-generation electronic devices owing to their unique physical properties. Although thermal transport across MoX2 interfaces has been extensively investigated over the past decade, research on WX2 interfaces remains limited, and large discrepancies in previous reports obscure the underlying mechanisms. In this work, we experimentally unveil the governing factors and the underlying mechanisms of phonon transport across WX2 interfaces through measuring interfacial thermal conductance (G) of metal/WS2(or WSe2)/Al2O3 over the temperature (T) of 80–600 K using time-domain thermoreflectance (TDTR). We find that even for WS2 grown by chemical vapor deposition, G of metal/WS2/Al2O3 spreads in a wide range of 6.4–13.4 MW m−2 K−1 under room temperature. Through a detailed analysis of picosecond acoustic signals and a comparison of samples prepared under differing conditions, we experimentally demonstrate that the interfacial bonding strength, rather than the mismatch in phonon density of states, plays a decisive role in tuning G of WX2 interfaces. Moreover, we observe that G of Al/WSe2/Al2O3 exceeds the phonon radiation limit and increases substantially with T even beyond the Debye temperature. This suggests that inelastic phonon scattering should contribute significantly to the G of WSe2 interfaces. Our work fills the gap in experimental data on thermal conductance for WX2 interfaces and offers valuable insights into the underlying thermal transport physics in such systems.
{"title":"Unveiling the governing factors of phonon transport across monolayer WS2 and WSe2 interfaces","authors":"Yijie Chen , Chunwei Zhang , Tong Wang , Guojun Li , Jiahui Lou , Qun Cao , Cheng Shao , Hongkun Li , Weidong Zheng","doi":"10.1016/j.mtphys.2026.102016","DOIUrl":"10.1016/j.mtphys.2026.102016","url":null,"abstract":"<div><div>The group VI transition metal dichalcogenides (MoX<sub>2</sub> and WX<sub>2</sub>, X = chalcogen) have attracted considerable interest for next-generation electronic devices owing to their unique physical properties. Although thermal transport across MoX<sub>2</sub> interfaces has been extensively investigated over the past decade, research on WX<sub>2</sub> interfaces remains limited, and large discrepancies in previous reports obscure the underlying mechanisms. In this work, we experimentally unveil the governing factors and the underlying mechanisms of phonon transport across WX<sub>2</sub> interfaces through measuring interfacial thermal conductance (<em>G</em>) of metal/WS<sub>2</sub>(or WSe<sub>2</sub>)/Al<sub>2</sub>O<sub>3</sub> over the temperature (<em>T</em>) of 80–600 K using time-domain thermoreflectance (TDTR). We find that even for WS<sub>2</sub> grown by chemical vapor deposition, <em>G</em> of metal/WS<sub>2</sub>/Al<sub>2</sub>O<sub>3</sub> spreads in a wide range of 6.4–13.4 MW m<sup>−2</sup> K<sup>−1</sup> under room temperature. Through a detailed analysis of picosecond acoustic signals and a comparison of samples prepared under differing conditions, we experimentally demonstrate that the interfacial bonding strength, rather than the mismatch in phonon density of states, plays a decisive role in tuning <em>G</em> of WX<sub>2</sub> interfaces. Moreover, we observe that <em>G</em> of Al/WSe<sub>2</sub>/Al<sub>2</sub>O<sub>3</sub> exceeds the phonon radiation limit and increases substantially with <em>T</em> even beyond the Debye temperature. This suggests that inelastic phonon scattering should contribute significantly to the <em>G</em> of WSe<sub>2</sub> interfaces. Our work fills the gap in experimental data on thermal conductance for WX<sub>2</sub> interfaces and offers valuable insights into the underlying thermal transport physics in such systems.</div></div>","PeriodicalId":18253,"journal":{"name":"Materials Today Physics","volume":"61 ","pages":"Article 102016"},"PeriodicalIF":9.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.mtphys.2026.102015
Zhen Wang , Yazhu Xu , Gaofeng Zhao , Zhenzhen Feng , David J. Singh
Thermal conductivity is a key materials parameter that is important in combination with other properties for important applications including electronics, thermal barriers and a variety of energy technologies. There are established trends that are useful in finding materials with desirable thermal conductivity. For example, stable stiff lattices typically yield high thermal conductivity, while materials near instabilities have low thermal conductivity. Rattling is widely applied approach for lowering thermal conductivity and is understood as the incorporation of loosely bound ions in a semiconducting framework. It is manifested in low frequency flat optical phonon branches that cross the acoustic branches. We investigate LaRhTe using global optimization crystal structure determination, anharmonic lattice dynamics, and first principles based characterization of bonding. There are two low energy phases, a hexagonal metallic phase and a cubic semiconducting phase. This cubic phase is predicted to be a low thermal conductivity (1.61 W m−1K−1 at 300 K) semiconductor. We elucidate the origins of its low thermal conductivity finding that strong anharmonic phonon scattering, induced by weak bonding of Rh within the cage-like LaTe network, is important. The Rh atoms contribute to low-frequency phonons, while the La-Te system dominates the high-frequency optical phonon branches. This is unexpected based on the chemical characteristics of Rh chalcogenides and the known thermoelectric behavior of La-Te binary phases. It arises due to the structural constraints in the cubic half-Heusler phase leading to a generalized rattling behavior involving Rh. These results show that the rattling concept is more general than usually assumed and can be operative even without the characteristic rattler induced flat optical branches anticrossing the acoustic branches that are often discussed in the context of low thermal conductivity thermoelectrics.
导热系数是一个关键的材料参数，它与电子、热障和各种能源技术等重要应用的其他性能结合在一起很重要。在寻找具有理想导热性的材料时，有一些既定的趋势是有用的。例如，稳定的刚性晶格通常产生高导热系数，而接近不稳定的材料具有低导热系数。嘎嘎是广泛应用于降低热导率的方法，被理解为在半导体框架中结合松散结合的离子。它表现为低频平面光学声子分支与声学分支交叉。我们使用全局优化晶体结构确定、非调和晶格动力学和基于第一性原理的键合表征来研究LaRhTe。有两种低能相，六方金属相和立方半导体相。该立方相预测为低导热系数（在300 K时为1.61 W m−1K−1）的半导体。我们阐明了其低热导率的起源，发现由笼状LaTe网络中Rh的弱键引起的强非谐波声子散射是重要的。Rh原子对低频声子有贡献，而La-Te系统主导高频光学声子分支。基于Rh硫族化合物的化学特性和已知的La-Te二元相的热电行为，这是出乎意料的。它的产生是由于立方半赫斯勒相的结构约束导致涉及Rh的广义咔嗒行为。这些结果表明，嘎嘎声的概念比通常假设的更普遍，即使没有响尾声诱发的平坦光学分支的特征也可以运作，而声学分支通常在低热导率的热电环境中讨论。
{"title":"Generalized rattling and thermal conductivity: Cubic LaRhTe","authors":"Zhen Wang , Yazhu Xu , Gaofeng Zhao , Zhenzhen Feng , David J. Singh","doi":"10.1016/j.mtphys.2026.102015","DOIUrl":"10.1016/j.mtphys.2026.102015","url":null,"abstract":"<div><div>Thermal conductivity is a key materials parameter that is important in combination with other properties for important applications including electronics, thermal barriers and a variety of energy technologies. There are established trends that are useful in finding materials with desirable thermal conductivity. For example, stable stiff lattices typically yield high thermal conductivity, while materials near instabilities have low thermal conductivity. Rattling is widely applied approach for lowering thermal conductivity and is understood as the incorporation of loosely bound ions in a semiconducting framework. It is manifested in low frequency flat optical phonon branches that cross the acoustic branches. We investigate LaRhTe using global optimization crystal structure determination, anharmonic lattice dynamics, and first principles based characterization of bonding. There are two low energy phases, a hexagonal metallic phase and a cubic semiconducting phase. This cubic phase is predicted to be a low thermal conductivity (1.61 W m<sup>−1</sup>K<sup>−1</sup> at 300 K) semiconductor. We elucidate the origins of its low thermal conductivity finding that strong anharmonic phonon scattering, induced by weak bonding of Rh within the cage-like LaTe network, is important. The Rh atoms contribute to low-frequency phonons, while the La-Te system dominates the high-frequency optical phonon branches. This is unexpected based on the chemical characteristics of Rh chalcogenides and the known thermoelectric behavior of La-Te binary phases. It arises due to the structural constraints in the cubic half-Heusler phase leading to a generalized rattling behavior involving Rh. These results show that the rattling concept is more general than usually assumed and can be operative even without the characteristic rattler induced flat optical branches anticrossing the acoustic branches that are often discussed in the context of low thermal conductivity thermoelectrics.</div></div>","PeriodicalId":18253,"journal":{"name":"Materials Today Physics","volume":"61 ","pages":"Article 102015"},"PeriodicalIF":9.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-07DOI: 10.1016/j.mtphys.2026.102010
Kaisen Liu , Songhao Wu , Shulin Hu , Dongyang Han , Li Chen , Gaofeng Deng , Shen Hu , Li Ji , Ping Cui , Jichun Ye , Wenrui Zhang
Ultrawide bandgap (UWBG) gallium oxide (Ga2O3) featuring several polymorphs holds great potential for high-power electronics and solar-blind optoelectronics. Designing electronic devices based on hybrid Ga2O3 polymorph structures appears highly attractive, but it meets persistent obstacles from epitaxy challenges and dopant activation problems. This study reports a 3 kV-class lateral Schottky barrier diode (SBD) based on a unique heteroepitaxial α/β-Ga2O3 heterostructure composed of conductive β-Ga2O3 domains embedded in an insulating α-Ga2O3 matrix. The α/β-Ga2O3 heterostructure is constructed from a strain-relaxed α-to-β Ga2O3 phase transition that strongly depends on the substrate orientation and film thickness. The formation of the β-Ga2O3 phase presents a minor impact on the crystallinity of the α-Ga2O3 matrix and exhibits more readily dopant activation during the sputtering growth. The lateral SBD based on this hybrid α/β-Ga2O3 heterostructure combines the benefits of efficient carrier transport in β-Ga2O3 and the superior breakdown field in α-Ga2O3, thus enabling a decent rectifying behavior and a 3 kV breakdown voltage two times larger than the single-phase β-Ga2O3 diode. This study provides critical insights into the phase-design strategy for developing advanced UWBG electronic devices.
{"title":"Designing a hybrid α/β-Ga2O3 polymorph heterostructure from strain-relaxed phase transition for high-voltage power diodes","authors":"Kaisen Liu , Songhao Wu , Shulin Hu , Dongyang Han , Li Chen , Gaofeng Deng , Shen Hu , Li Ji , Ping Cui , Jichun Ye , Wenrui Zhang","doi":"10.1016/j.mtphys.2026.102010","DOIUrl":"10.1016/j.mtphys.2026.102010","url":null,"abstract":"<div><div>Ultrawide bandgap (UWBG) gallium oxide (Ga<sub>2</sub>O<sub>3</sub>) featuring several polymorphs holds great potential for high-power electronics and solar-blind optoelectronics. Designing electronic devices based on hybrid Ga<sub>2</sub>O<sub>3</sub> polymorph structures appears highly attractive, but it meets persistent obstacles from epitaxy challenges and dopant activation problems. This study reports a 3 kV-class lateral Schottky barrier diode (SBD) based on a unique heteroepitaxial <em>α</em>/<em>β</em>-Ga<sub>2</sub>O<sub>3</sub> heterostructure composed of conductive <em>β</em>-Ga<sub>2</sub>O<sub>3</sub> domains embedded in an insulating <em>α</em>-Ga<sub>2</sub>O<sub>3</sub> matrix. The <em>α</em>/<em>β</em>-Ga<sub>2</sub>O<sub>3</sub> heterostructure is constructed from a strain-relaxed <em>α</em>-to-<em>β</em> Ga<sub>2</sub>O<sub>3</sub> phase transition that strongly depends on the substrate orientation and film thickness. The formation of the <em>β</em>-Ga<sub>2</sub>O<sub>3</sub> phase presents a minor impact on the crystallinity of the <em>α</em>-Ga<sub>2</sub>O<sub>3</sub> matrix and exhibits more readily dopant activation during the sputtering growth. The lateral SBD based on this hybrid <em>α</em>/<em>β</em>-Ga<sub>2</sub>O<sub>3</sub> heterostructure combines the benefits of efficient carrier transport in <em>β</em>-Ga<sub>2</sub>O<sub>3</sub> and the superior breakdown field in <em>α</em>-Ga<sub>2</sub>O<sub>3</sub>, thus enabling a decent rectifying behavior and a 3 kV breakdown voltage two times larger than the single-phase <em>β</em>-Ga<sub>2</sub>O<sub>3</sub> diode. This study provides critical insights into the phase-design strategy for developing advanced UWBG electronic devices.</div></div>","PeriodicalId":18253,"journal":{"name":"Materials Today Physics","volume":"61 ","pages":"Article 102010"},"PeriodicalIF":9.7,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145937483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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