Luke P. J. Gilligan, Matteo Cobelli, Hasan M. Sayeed, Taylor D. Sparks, Stefano Sanvito
Vector embeddings derived from large language models (LLMs) show promise in capturing latent information from the literature. Interestingly, these can be integrated into material embeddings, potentially useful for data-driven predictions of materials properties. We investigate the extent to which LLM-derived vectors capture the desired information and their potential to provide insights into material properties without additional training. Our findings indicate that, although LLMs can be used to generate representations reflecting certain property information, extracting the embeddings requires identifying the optimal contextual clues and appropriate comparators. Despite this restriction, it appears that LLMs still have the potential to be useful in generating meaningful materials-science representations.
{"title":"Sampling Latent Material-Property Information From LLM-Derived Embedding Representations","authors":"Luke P. J. Gilligan, Matteo Cobelli, Hasan M. Sayeed, Taylor D. Sparks, Stefano Sanvito","doi":"arxiv-2409.11971","DOIUrl":"https://doi.org/arxiv-2409.11971","url":null,"abstract":"Vector embeddings derived from large language models (LLMs) show promise in\u0000capturing latent information from the literature. Interestingly, these can be\u0000integrated into material embeddings, potentially useful for data-driven\u0000predictions of materials properties. We investigate the extent to which\u0000LLM-derived vectors capture the desired information and their potential to\u0000provide insights into material properties without additional training. Our\u0000findings indicate that, although LLMs can be used to generate representations\u0000reflecting certain property information, extracting the embeddings requires\u0000identifying the optimal contextual clues and appropriate comparators. Despite\u0000this restriction, it appears that LLMs still have the potential to be useful in\u0000generating meaningful materials-science representations.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In material physics, characterization techniques are foremost crucial for obtaining the materials data regarding the physical properties as well as structural, electronics, magnetic, optic, dielectric, and spectroscopic characteristics. However, for many materials, ensuring availability and safe accessibility is not always easy and fully warranted. Moreover, the use of modeling and simulation techniques need a lot of theoretical knowledge, in addition of being associated to costly computation time and a great complexity deal. Thus, analyzing materials with different techniques for multiple samples simultaneously, still be very challenging for engineers and researchers. It is worth noting that although of being very risky, X-ray diffraction is the well known and widely used characterization technique which gathers data from structural properties of crystalline 1d, 2d or 3d materials. We propose in this paper, a Smart GRU for Gated Recurrent Unit model to forcast structural characteristics or properties of thin films of tin oxide SnO$_2$(110). Indeed, thin films samples are elaborated and managed experimentally and the collected data dictionary is then used to generate an AI -- Artificial Intelligence -- GRU model for the thin films of tin oxide SnO$_2$(110) structural property characterization.
{"title":"Smart Data-Driven GRU Predictor for SnO$_2$ Thin films Characteristics","authors":"Faiza Bouamra, Mohamed Sayah, Labib Sadek Terrissa, Noureddine Zerhouni","doi":"arxiv-2409.11782","DOIUrl":"https://doi.org/arxiv-2409.11782","url":null,"abstract":"In material physics, characterization techniques are foremost crucial for\u0000obtaining the materials data regarding the physical properties as well as\u0000structural, electronics, magnetic, optic, dielectric, and spectroscopic\u0000characteristics. However, for many materials, ensuring availability and safe\u0000accessibility is not always easy and fully warranted. Moreover, the use of\u0000modeling and simulation techniques need a lot of theoretical knowledge, in\u0000addition of being associated to costly computation time and a great complexity\u0000deal. Thus, analyzing materials with different techniques for multiple samples\u0000simultaneously, still be very challenging for engineers and researchers. It is\u0000worth noting that although of being very risky, X-ray diffraction is the well\u0000known and widely used characterization technique which gathers data from\u0000structural properties of crystalline 1d, 2d or 3d materials. We propose in this\u0000paper, a Smart GRU for Gated Recurrent Unit model to forcast structural\u0000characteristics or properties of thin films of tin oxide SnO$_2$(110). Indeed,\u0000thin films samples are elaborated and managed experimentally and the collected\u0000data dictionary is then used to generate an AI -- Artificial Intelligence --\u0000GRU model for the thin films of tin oxide SnO$_2$(110) structural property\u0000characterization.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kisung Kang, Thomas A. R. Purcell, Christian Carbogno, Matthias Scheffler
Molecular dynamics (MD) employing machine-learned interatomic potentials (MLIPs) serve as an efficient, urgently needed complement to ab initio molecular dynamics (aiMD). By training these potentials on data generated from ab initio methods, their averaged predictions can exhibit comparable performance to ab initio methods at a fraction of the cost. However, insufficient training sets might lead to an improper description of the dynamics in strongly anharmonic materials, because critical effects might be overlooked in relevant cases, or only incorrectly captured, or hallucinated by the MLIP when they are not actually present. In this work, we show that an active learning scheme that combines MD with MLIPs (MLIP-MD) and uncertainty estimates can avoid such problematic predictions. In short, efficient MLIP-MD is used to explore configuration space quickly, whereby an acquisition function based on uncertainty estimates and on energetic viability is employed to maximize the value of the newly generated data and to focus on the most unfamiliar but reasonably accessible regions of phase space. To verify our methodology, we screen over 112 materials and identify 10 examples experiencing the aforementioned problems. Using CuI and AgGaSe$_2$ as archetypes for these problematic materials, we discuss the physical implications for strongly anharmonic effects and demonstrate how the developed active learning scheme can address these issues.
{"title":"Accelerating the Training and Improving the Reliability of Machine-Learned Interatomic Potentials for Strongly Anharmonic Materials through Active Learning","authors":"Kisung Kang, Thomas A. R. Purcell, Christian Carbogno, Matthias Scheffler","doi":"arxiv-2409.11808","DOIUrl":"https://doi.org/arxiv-2409.11808","url":null,"abstract":"Molecular dynamics (MD) employing machine-learned interatomic potentials\u0000(MLIPs) serve as an efficient, urgently needed complement to ab initio\u0000molecular dynamics (aiMD). By training these potentials on data generated from\u0000ab initio methods, their averaged predictions can exhibit comparable\u0000performance to ab initio methods at a fraction of the cost. However,\u0000insufficient training sets might lead to an improper description of the\u0000dynamics in strongly anharmonic materials, because critical effects might be\u0000overlooked in relevant cases, or only incorrectly captured, or hallucinated by\u0000the MLIP when they are not actually present. In this work, we show that an\u0000active learning scheme that combines MD with MLIPs (MLIP-MD) and uncertainty\u0000estimates can avoid such problematic predictions. In short, efficient MLIP-MD\u0000is used to explore configuration space quickly, whereby an acquisition function\u0000based on uncertainty estimates and on energetic viability is employed to\u0000maximize the value of the newly generated data and to focus on the most\u0000unfamiliar but reasonably accessible regions of phase space. To verify our\u0000methodology, we screen over 112 materials and identify 10 examples experiencing\u0000the aforementioned problems. Using CuI and AgGaSe$_2$ as archetypes for these\u0000problematic materials, we discuss the physical implications for strongly\u0000anharmonic effects and demonstrate how the developed active learning scheme can\u0000address these issues.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna Hartl, Ján Minár, Procopios Constantinou, Vladimir Roddatis, Fatima Alarab, Arnold M. Müller, Christof Vockenhuber, Thorsten Schmitt, Daniele Pergolesi, Thomas Lippert Vladimir N. Strocov, Nick A. Shepelin
The conversion of solar energy into chemical energy, stored in the form of hydrogen, bears enormous potential as a sustainable fuel for powering emerging technologies. Photoactive oxynitrides are promising materials for splitting water into molecular oxygen and hydrogen. However, one of the issues limiting widespread commercial use of oxynitrides is the degradation during operation. While recent studies have shown the loss of nitrogen, its relation to the reduced efficiency has not been directly and systematically addressed with experiments. In this study, we demonstrate the impact of the anionic stoichiometry of BaTaO$_x$N$_y$ on its electronic structure and functional properties. Through experimental ion scattering, electron microscopy, and photoelectron spectroscopy investigations, we determine the anionic composition ranging from the bulk towards the surface of BaTaO$_x$N$_y$ thin films. This further serves as input for band structure computations modeling the substitutional disorder of the anion sites. Combining our experimental and computational approaches, we reveal the depth-dependent elemental composition of oxynitride films, resulting in downward band bending and the loss of semiconducting character towards the surface. Extending beyond idealized systems, we demonstrate the relation between the electronic properties of real oxynitride photoanodes and their performance, providing guidelines for engineering highly efficient photoelectrodes and photocatalysts for clean hydrogen production.
{"title":"Anionic disorder and its impact on the surface electronic structure of oxynitride photoactive semiconductors","authors":"Anna Hartl, Ján Minár, Procopios Constantinou, Vladimir Roddatis, Fatima Alarab, Arnold M. Müller, Christof Vockenhuber, Thorsten Schmitt, Daniele Pergolesi, Thomas Lippert Vladimir N. Strocov, Nick A. Shepelin","doi":"arxiv-2409.11825","DOIUrl":"https://doi.org/arxiv-2409.11825","url":null,"abstract":"The conversion of solar energy into chemical energy, stored in the form of\u0000hydrogen, bears enormous potential as a sustainable fuel for powering emerging\u0000technologies. Photoactive oxynitrides are promising materials for splitting\u0000water into molecular oxygen and hydrogen. However, one of the issues limiting\u0000widespread commercial use of oxynitrides is the degradation during operation.\u0000While recent studies have shown the loss of nitrogen, its relation to the\u0000reduced efficiency has not been directly and systematically addressed with\u0000experiments. In this study, we demonstrate the impact of the anionic\u0000stoichiometry of BaTaO$_x$N$_y$ on its electronic structure and functional\u0000properties. Through experimental ion scattering, electron microscopy, and\u0000photoelectron spectroscopy investigations, we determine the anionic composition\u0000ranging from the bulk towards the surface of BaTaO$_x$N$_y$ thin films. This\u0000further serves as input for band structure computations modeling the\u0000substitutional disorder of the anion sites. Combining our experimental and\u0000computational approaches, we reveal the depth-dependent elemental composition\u0000of oxynitride films, resulting in downward band bending and the loss of\u0000semiconducting character towards the surface. Extending beyond idealized\u0000systems, we demonstrate the relation between the electronic properties of real\u0000oxynitride photoanodes and their performance, providing guidelines for\u0000engineering highly efficient photoelectrodes and photocatalysts for clean\u0000hydrogen production.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paul Corbae, Aaron N. Engel, Jason T. Dong, Wilson J. Yánez-Parreño, Donghui Lu, Makoto Hashimoto, Alexei Fedorov, Christopher J. Palmstrøm
Bismuth antimony alloys (Bi$_x$Sb$_{1-x}$) provide a tuneable materials platform to study topological transport and spin-polarized surface states resulting from the nontrivial bulk electronic structure. In the two-dimensional limit, it is a suitable system to study the quantum spin Hall effect. In this work we grow epitaxial, single orientation thin films of Bi$_x$Sb$_{1-x}$ on an InSb(111)B substrate down to two bilayers where hybridization effects should gap out the topological surface states. Supported by a tight-binding model, spin- and angle-resolved photoemission spectroscopy data shows pockets at the Fermi level from the topological surface states disappear as the bulk gap increases from confinement. Evidence for a gap opening in the topological surface states is shown in the ultrathin limit. Finally, we observe spin-polarization approaching unity from the topological surface states in 10 bilayer films. The growth and characterization of ultrathin Bi$_x$Sb$_{1-x}$ alloys suggest ultrathin films of this material system can be used to study two-dimensional topological physics as well as applications such as topological devices, low power electronics, and spintronics.
{"title":"Hybridization gap approaching the two-dimensional limit of topological insulator Bi$_x$Sb$_{1-x}$","authors":"Paul Corbae, Aaron N. Engel, Jason T. Dong, Wilson J. Yánez-Parreño, Donghui Lu, Makoto Hashimoto, Alexei Fedorov, Christopher J. Palmstrøm","doi":"arxiv-2409.11705","DOIUrl":"https://doi.org/arxiv-2409.11705","url":null,"abstract":"Bismuth antimony alloys (Bi$_x$Sb$_{1-x}$) provide a tuneable materials\u0000platform to study topological transport and spin-polarized surface states\u0000resulting from the nontrivial bulk electronic structure. In the two-dimensional\u0000limit, it is a suitable system to study the quantum spin Hall effect. In this\u0000work we grow epitaxial, single orientation thin films of Bi$_x$Sb$_{1-x}$ on an\u0000InSb(111)B substrate down to two bilayers where hybridization effects should\u0000gap out the topological surface states. Supported by a tight-binding model,\u0000spin- and angle-resolved photoemission spectroscopy data shows pockets at the\u0000Fermi level from the topological surface states disappear as the bulk gap\u0000increases from confinement. Evidence for a gap opening in the topological\u0000surface states is shown in the ultrathin limit. Finally, we observe\u0000spin-polarization approaching unity from the topological surface states in 10\u0000bilayer films. The growth and characterization of ultrathin Bi$_x$Sb$_{1-x}$\u0000alloys suggest ultrathin films of this material system can be used to study\u0000two-dimensional topological physics as well as applications such as topological\u0000devices, low power electronics, and spintronics.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qingqi Zeng, Zhiwei Du, Xiaolei Han, Binbin Wang, Guangheng Wu, Enke Liu
During the phase transitions, diverse states evolve with multiplex phenomena arising from the critical competition. In this study, a displacive martensitic transformation with a lattice shear distortion was unexpectedly observed at the reconstructive phase boundary that usually connects multiple phases without crystallographic relation, in a Ni-Co-Mn-V all-d-metal alloy system. Experiments and theoretical calculations suggest that the parent phase becomes increasingly unstable when approaching the phase boundary. The lattice-distorted transformation with moderate first-order nature survives due to the critical phase competition from the structural frustration, in which the comparable energy and the diminished formation preference of different phases emerge. In this critical state, the phase selection including the martensitic phase transformation can be tuned by external fields such as rapid cooling, annealing and magnetic field. Our research reveals a novel manner to destabilize the parent phase, through which one could attain new functional materials based on the phase transitions.
{"title":"Observation of atomically displacive transformation out of the boundary-reconstructive phase competition","authors":"Qingqi Zeng, Zhiwei Du, Xiaolei Han, Binbin Wang, Guangheng Wu, Enke Liu","doi":"arxiv-2409.10945","DOIUrl":"https://doi.org/arxiv-2409.10945","url":null,"abstract":"During the phase transitions, diverse states evolve with multiplex phenomena\u0000arising from the critical competition. In this study, a displacive martensitic\u0000transformation with a lattice shear distortion was unexpectedly observed at the\u0000reconstructive phase boundary that usually connects multiple phases without\u0000crystallographic relation, in a Ni-Co-Mn-V all-d-metal alloy system.\u0000Experiments and theoretical calculations suggest that the parent phase becomes\u0000increasingly unstable when approaching the phase boundary. The\u0000lattice-distorted transformation with moderate first-order nature survives due\u0000to the critical phase competition from the structural frustration, in which the\u0000comparable energy and the diminished formation preference of different phases\u0000emerge. In this critical state, the phase selection including the martensitic\u0000phase transformation can be tuned by external fields such as rapid cooling,\u0000annealing and magnetic field. Our research reveals a novel manner to\u0000destabilize the parent phase, through which one could attain new functional\u0000materials based on the phase transitions.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Co$_3$O$_4$ spinel is an important material in oxidation catalysis. Its properties under catalytic conditions, i.e., at finite temperatures, can be studied by molecular dynamics simulations, which critically depend on an accurate description of the atomic interactions. Due to the high complexity of Co$_3$O$_4$, which is related to the presence of multiple oxidation states of the cobalt ions, to date textit{ab initio} methods have been essentially the only way to reliably capture the underlying potential energy surface, while more efficient atomistic potentials are very challenging to construct. Consequently, the accessible length and time scales of computer simulations of systems containing Co$_3$O$_4$ are still severely limited. Rapid advances in the development of modern machine learning potentials (MLPs) trained on electronic structure data now make it possible to bridge this gap. In this work, we employ a high-dimensional neural network potential (HDNNP) to construct a MLP for bulk Co$_3$O$_4$ spinel based on density functional theory calculations. After a careful validation of the potential, we compute various structural, vibrational, and dynamical properties of the Co$_3$O$_4$ spinel with a particular focus on its temperature-dependent behavior, including the thermal expansion coefficient.
{"title":"A High-Dimensional Neural Network Potential for Co$_3$O$_4$","authors":"Amir Omranpour, Jörg Behler","doi":"arxiv-2409.11037","DOIUrl":"https://doi.org/arxiv-2409.11037","url":null,"abstract":"The Co$_3$O$_4$ spinel is an important material in oxidation catalysis. Its\u0000properties under catalytic conditions, i.e., at finite temperatures, can be\u0000studied by molecular dynamics simulations, which critically depend on an\u0000accurate description of the atomic interactions. Due to the high complexity of\u0000Co$_3$O$_4$, which is related to the presence of multiple oxidation states of\u0000the cobalt ions, to date textit{ab initio} methods have been essentially the\u0000only way to reliably capture the underlying potential energy surface, while\u0000more efficient atomistic potentials are very challenging to construct.\u0000Consequently, the accessible length and time scales of computer simulations of\u0000systems containing Co$_3$O$_4$ are still severely limited. Rapid advances in\u0000the development of modern machine learning potentials (MLPs) trained on\u0000electronic structure data now make it possible to bridge this gap. In this\u0000work, we employ a high-dimensional neural network potential (HDNNP) to\u0000construct a MLP for bulk Co$_3$O$_4$ spinel based on density functional theory\u0000calculations. After a careful validation of the potential, we compute various\u0000structural, vibrational, and dynamical properties of the Co$_3$O$_4$ spinel\u0000with a particular focus on its temperature-dependent behavior, including the\u0000thermal expansion coefficient.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fluorite-type $mathrm{HfO_2}$-based ferroelectric (FE) oxides have rekindled interest in FE memories due to their compatibility with silicon processing and potential for high-density integration. The polarization characteristics of FE devices are governed by the dynamics of metastable domain structure evolution. Insightful design of FE devices for encoding and storage necessitates a comprehensive understanding of the internal structural evolution. Here, we demonstrate the evolution of domain structures through a transient polar orthorhombic (O)-$Pmn2_1$-like configuration via $in$-$situ$ biasing on $mathrm{TiN/Hf_{0.5}Zr_{0.5}O_2/TiN}$ capacitors within spherical aberration-corrected transmission electron microscope, combined with theoretical calculations. Furthermore, it is directly evidenced that the non-FE O-$Pbca$ transforms into the FE O-$Pca2_1$ phase under electric field, with the polar axis of the FE-phase aligning towards the bias direction through ferroelastic transformation, thereby enhancing FE polarization. As cycling progresses further, however, the polar axis collapses, leading to FE degradation. These novel insights into the intricate structural evolution path under electrical field cycling facilitate optimization and design strategies for $mathrm{HfO_2}$-based FE memory devices.
基于萤石型 $mathrm{HfO_2}$ 的铁电（FE）氧化物重新点燃了人们对 FE 存储器的兴趣，因为它们与硅加工兼容并具有高密度集成的潜力。FE 器件的极化特性受制于可迁移畴结构的动态演化。在这里，我们通过在球面偏差校正透射电子显微镜下对$mathrm{TiN/Hf_{0.5}Zr_{0.5}O_2/TiN}$电容器进行$in$$-$situ$偏压，并结合理论计算，展示了通过瞬态极性正交（O）-$Pmn2_1$类构型实现的畴结构演化。此外，研究还直接证明，在电场作用下，非 FEO-$Pbca$ 转变为 FE O-$Pca2_1$ 相，通过铁弹性转变，FE 相的极轴朝向偏压方向，从而增强了 FE 极化。然而，随着循环的进一步进行，极轴塌陷，导致 FE 退化。这些关于电场循环下复杂结构演变路径的新见解有助于基于 $mathrm{HfO_2}$ 的 FE 存储器件的优化和设计策略。
{"title":"Structure evolution path of ferroelectric hafnium zirconium oxide nanocrystals under in-situ biasing","authors":"Yunzhe Zheng, Heng Yu, Tianjiao Xin, Kan-Hao Xue, Yilin Xu, Zhaomeng Gao, Cheng Liu, Qiwendong Zhao, Yonghui Zheng, Xiangshui Miao, Yan Cheng","doi":"arxiv-2409.11217","DOIUrl":"https://doi.org/arxiv-2409.11217","url":null,"abstract":"Fluorite-type $mathrm{HfO_2}$-based ferroelectric (FE) oxides have rekindled\u0000interest in FE memories due to their compatibility with silicon processing and\u0000potential for high-density integration. The polarization characteristics of FE\u0000devices are governed by the dynamics of metastable domain structure evolution.\u0000Insightful design of FE devices for encoding and storage necessitates a\u0000comprehensive understanding of the internal structural evolution. Here, we\u0000demonstrate the evolution of domain structures through a transient polar\u0000orthorhombic (O)-$Pmn2_1$-like configuration via $in$-$situ$ biasing on\u0000$mathrm{TiN/Hf_{0.5}Zr_{0.5}O_2/TiN}$ capacitors within spherical\u0000aberration-corrected transmission electron microscope, combined with\u0000theoretical calculations. Furthermore, it is directly evidenced that the non-FE\u0000O-$Pbca$ transforms into the FE O-$Pca2_1$ phase under electric field, with the\u0000polar axis of the FE-phase aligning towards the bias direction through\u0000ferroelastic transformation, thereby enhancing FE polarization. As cycling\u0000progresses further, however, the polar axis collapses, leading to FE\u0000degradation. These novel insights into the intricate structural evolution path\u0000under electrical field cycling facilitate optimization and design strategies\u0000for $mathrm{HfO_2}$-based FE memory devices.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Phase transition is a fundamental phenomenon in condensed matter physics, in which states of matter transform to each other with various critical behaviors under different conditions. The magnetic martensitic transformation features significant multi-caloric effects that benefit the solid-state cooling or heat pumping. Meanwhile, the electronic topological transition (ETT) driven by pressure has been rarely reported in martensitic systems. Here, the modulation effects of hydrostatic pressure on phase transitions in a magnetic martensitic alloy are reported. Owing to the huge volume expansion during the transition, the martensitic transition temperature is driven from 339 to 273 K by pressure within 1 GPa, resulting in highly tunable giant baro- and magneto-caloric effects (BCE and MCE) in a wide working temperature range. Interestingly, an ETT was further induced by pressure in the martensite phase, with a sudden drop of the measured saturation magnetization around 0.6 GPa. First-principles calculations reveal a sharp change in the density of states (DOS) due to the orbit shift around the Fermi level at the same pressure and reproduce the experimental observation of magnetization. Besides, the ETT is accompanied by remarkable changes in the lattice parameters and the unit-cell orthorhombicity. The study provides insight into pressure-modulated exotic phase-transition phenomena in magnetic martensitic systems.
{"title":"Observation of hydrostatic-pressure-modulated giant caloric effect and electronic topological transition","authors":"Jinying Yang, Xingchen Liu, Yibo Wang, Shen Zhang, Yang Liu, Xuebin Dong, Yiting Feng, Qiusa Ren, Ping He, Meng Lyu, Binbin Wang, Shouguo Wang, Guangheng Wu, Xixiang Zhang, Enke Liu","doi":"arxiv-2409.10936","DOIUrl":"https://doi.org/arxiv-2409.10936","url":null,"abstract":"Phase transition is a fundamental phenomenon in condensed matter physics, in\u0000which states of matter transform to each other with various critical behaviors\u0000under different conditions. The magnetic martensitic transformation features\u0000significant multi-caloric effects that benefit the solid-state cooling or heat\u0000pumping. Meanwhile, the electronic topological transition (ETT) driven by\u0000pressure has been rarely reported in martensitic systems. Here, the modulation\u0000effects of hydrostatic pressure on phase transitions in a magnetic martensitic\u0000alloy are reported. Owing to the huge volume expansion during the transition,\u0000the martensitic transition temperature is driven from 339 to 273 K by pressure\u0000within 1 GPa, resulting in highly tunable giant baro- and magneto-caloric\u0000effects (BCE and MCE) in a wide working temperature range. Interestingly, an\u0000ETT was further induced by pressure in the martensite phase, with a sudden drop\u0000of the measured saturation magnetization around 0.6 GPa. First-principles\u0000calculations reveal a sharp change in the density of states (DOS) due to the\u0000orbit shift around the Fermi level at the same pressure and reproduce the\u0000experimental observation of magnetization. Besides, the ETT is accompanied by\u0000remarkable changes in the lattice parameters and the unit-cell orthorhombicity.\u0000The study provides insight into pressure-modulated exotic phase-transition\u0000phenomena in magnetic martensitic systems.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present results of atomic-level simulations of damage formation along the paths of swift heavy ions (SHI) decelerated in the electronic stopping regime in amorphous polyethylene. The applied model combines the Monte-Carlo code TREKIS-3, which describes excitation of the electronic and atomic systems around the ion trajectory, with molecular dynamics simulations of the response of the atomic system to the excitation. The simulation results were used to reconstruct the damage configuration, shape and size of the damaged region. We demonstrated that the positions of the maximum energy loss and maximum damage on the ion trajectory do not coincide, being separated by more than 10 micrometers. The difference between the thresholds of damage production by ions with energies realizing the opposite shoulders of the Bragg curve of the electronic stopping was found. We also analyzed the spatial distribution of chemically active fragments of polyethylene chains formed around the ion trajectory as a function of SHI energy.
我们介绍了在非晶态聚乙烯中电子停止机制下减速的迅猛重离子（SHI）沿路径形成损伤的原子级模拟结果。应用的模型结合了 Monte-Carlo 代码 TREKIS-3（该代码描述了围绕离子轨迹的电子和原子系统的激发）和原子系统对激发响应的分子动力学模拟。仿真结果被用于重建损伤构型、损伤区域的形状和大小。结果表明，离子轨迹上的最大能量损失和最大损伤位置并不重合，相距超过 10 厘米。我们发现，能量达到电子停止的布拉格曲线相反肩部的离子所产生的破坏阈值之间存在差异。我们还分析了离子轨迹周围形成的聚乙烯链化学活性碎片的空间分布与 SHI 能量的函数关系。
{"title":"Swift heavy ions in polyethylene: simulation of damage formation along the path","authors":"P. Babaev, R. Voronkov, A. E. Volkov","doi":"arxiv-2409.10935","DOIUrl":"https://doi.org/arxiv-2409.10935","url":null,"abstract":"We present results of atomic-level simulations of damage formation along the\u0000paths of swift heavy ions (SHI) decelerated in the electronic stopping regime\u0000in amorphous polyethylene. The applied model combines the Monte-Carlo code\u0000TREKIS-3, which describes excitation of the electronic and atomic systems\u0000around the ion trajectory, with molecular dynamics simulations of the response\u0000of the atomic system to the excitation. The simulation results were used to\u0000reconstruct the damage configuration, shape and size of the damaged region. We\u0000demonstrated that the positions of the maximum energy loss and maximum damage\u0000on the ion trajectory do not coincide, being separated by more than 10\u0000micrometers. The difference between the thresholds of damage production by ions\u0000with energies realizing the opposite shoulders of the Bragg curve of the\u0000electronic stopping was found. We also analyzed the spatial distribution of\u0000chemically active fragments of polyethylene chains formed around the ion\u0000trajectory as a function of SHI energy.","PeriodicalId":501234,"journal":{"name":"arXiv - PHYS - Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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