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Ferroelectricity at the extreme thickness limit in the archetypal antiferroelectric PbZrO3
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-25 DOI: 10.1038/s41524-025-01520-w
Nikhilesh Maity, Milan Haddad, Nazanin Bassiri-Gharb, Amit Kumar, Lewys Jones, Sergey Lisenkov, Inna Ponomareva

Size-driven transition of aNote, that the phasesn antiferroelectric into a polar ferroelectric or ferrielectric state is a strongly debated issue from both experimental and theoretical perspectives. While critical thickness limits for such transitions have been explored, a bottom-up approach in the ultrathin limit considering few atomic layers could provide insight into the mechanism of stabilization of the polar phases over the antipolar phase seen in bulk PbZrO3. Here, we use first-principles density functional theory to predict the stability of polar phases in Pt/PbZrO3/Pt nanocapacitors. In a few atomic layer thick slabs of PbZrO3 sandwiched between Pt electrodes, we find that the polar phase originating from the well established R3c phase of bulk PbZrO3 is energetically favorable over the antipolar phase originating from the Pbam phase of bulk PbZrO3. The famous triple-well potential of antiferroelectric PbZrO3 is modified in the nanocapacitor limit in such a way as to swap the positions of the global and local minima, stabilizing the polar phase relative to the antipolar one. The size effect is decomposed into the contributions from dimensionality reduction, surface charge screening, and interfacial relaxation, which reveals that it is the creation of well-compensated interfaces that stabilizes the polar phases over the antipolar ones in nanoscale PbZrO3.

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引用次数: 0
Efficient GPU-computing simulation platform JAX-CPFEM for differentiable crystal plasticity finite element method
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-22 DOI: 10.1038/s41524-025-01528-2
Fanglei Hu, Stephen Niezgoda, Tianju Xue, Jian Cao

We present the formulation and applications of JAX-CPFEM, an open-source, GPU-accelerated, and differentiable 3-D crystal plasticity finite element method (CPFEM) software package. Leveraging the modern computing architecture JAX, JAX-CPFEM features high performance through array programming and GPU acceleration, achieving a 39× speedup in a polycrystal case with ~52,000 degrees of freedom compared to MOOSE with MPI (8 cores). Furthermore, JAX-CPFEM utilizes the automatic differentiation technique, enabling users to handle complex, non-linear constitutive materials laws without manually deriving the case-specific Jacobian matrix. Beyond solving forward problems, JAX-CPFEM demonstrates its potential in an inverse design pipeline, where initial crystallographic orientations of polycrystal copper are optimized to achieve targeted mechanical properties under deformations. The end-to-end differentiability of JAX-CPFEM allows automatic sensitivity calculations and high-dimensional inverse design using gradient-based optimization. The concept of differentiable JAX-CPFEM provides an affordable, flexible, and multi-purpose tool, advancing efficient and accessible computational tools for inverse design in smart manufacturing.

我们介绍了开源、GPU 加速和可微分三维晶体塑性有限元法(CPFEM)软件包 JAX-CPFEM 的制定和应用。利用现代计算架构 JAX,JAX-CPFEM 通过阵列编程和 GPU 加速实现了高性能,与使用 MPI 的 MOOSE(8 核)相比,在具有 ~52,000 自由度的多晶体案例中实现了 39 倍的速度提升。此外,JAX-CPFEM 还采用了自动微分技术,使用户能够处理复杂的非线性材料构成规律,而无需手动推导特定情况下的雅各布矩阵。除了解决正向问题外,JAX-CPFEM 还展示了其在逆向设计管道中的潜力,在逆向设计管道中,多晶体铜的初始晶体学取向得到了优化,从而在变形条件下实现了目标机械性能。JAX-CPFEM 的端到端可微分性允许使用梯度优化进行自动灵敏度计算和高维逆向设计。可微分 JAX-CPFEM 的概念提供了一种经济、灵活、多用途的工具,为智能制造中的逆向设计提供了高效、易用的计算工具。
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引用次数: 0
First principles calculations of carrier dynamics of screw dislocation
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-21 DOI: 10.1038/s41524-025-01533-5
Qiang Gao, Zhengneng Zheng, Moshang Fan, Lin-Wang Wang

Nonradiative carrier recombination (NCR) in semiconductor is a fundamental process determining the efficiencies of many semiconductor devices. There is a longstanding debate on which line defect is an efficient NCR center, especially in third generation semiconductor. Here we developed a systematic method to calculate the electronic structure and NCR dynamics of screw dislocation. We studied the full-core screw dislocation of GaN with atomic structure taken from TEM images, and found that there are inside band gap dislocation states. Under n-type GaN condition, these band gap states will become occupied, making the core negatively charged, and inducing a potential well, which will attract minority hole carriers. Large-scale NAMD simulation shows that the holes can easily jump across a small band gap in the dislocation state band structure and hence will be annihilated with the electron nonradiatively, which agrees with the experimental observation of the photoluminescence dark spot on each dislocation.

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引用次数: 0
A physics-enforced neural network to predict polymer melt viscosity
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-20 DOI: 10.1038/s41524-025-01532-6
Ayush Jain, Rishi Gurnani, Arunkumar Rajan, H.Jerry Qi, Rampi Ramprasad

Achieving superior polymeric components through additive manufacturing (AM) relies on precise control of rheology. One rheological property particularly relevant to AM is melt viscosity (η). η is influenced by polymer chemistry, molecular weight (Mw), polydispersity, shear rate (({dot{gamma}})), and temperature (T). The relationship of η with Mw, ({dot{gamma }}), and T is captured by parameterized equations. Several physical experiments are required to fit the parameters, so predicting η of new polymer materials in unexplored physical domains is laborious. Here, we develop a Physics-Enforced Neural Network (PENN) model that predicts the empirical parameters and encodes the parametrized equations to calculate η as a function of polymer chemistry, Mw, polydispersity, ({dot{gamma }}), and T. We benchmark our PENN against physics-unaware Artificial Neural Network (ANN) and Gaussian Process Regression (GPR) models. We demonstrate that the PENN offers superior values of η when extrapolating to unseen values of Mw, ({dot{gamma }}), and T for sparsely seen polymers.

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引用次数: 0
The interplay between the martensitic transformation rate and the rate of plastic relaxation during martensitic transformation in low-carbon steel, a phase-field study
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-20 DOI: 10.1038/s41524-024-01499-w
Hesham Salama, Oleg Shchyglo, Ingo Steinbach
The complex interplay between the rapid martensitic transformation and the plastic relaxation during martensitic transformation in low-carbon steel is investigated using a combined phase-field and phenomenological crystal plasticity approach. The large transformation-induced deformations and local lattice rotations are rigorously described within the finite strain framework. The study reveals that plastic relaxation plays a crucial role in accommodating the transformation-induced deformations of martensite in the parent austenite phase. By systematically varying the plastic slip rate, imposed cooling rate, and carbon content, the simulations provide insights into the interdependence between these factors, contributing to a better understanding of the martensitic transformation process and the resulting microstructures. The phenomenological crystal plasticity model effectively relates the plastic relaxation rate to the rate of martensitic transformation with a significant time scale difference between the two processes. The findings contribute to a deeper understanding of the interplay between the rapid martensitic transformation and the requirement for plastic deformation.
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引用次数: 0
Accelerating crystal structure search through active learning with neural networks for rapid relaxations
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-20 DOI: 10.1038/s41524-025-01523-7
Stefaan S. P. Hessmann, Kristof T. Schütt, Niklas W. A. Gebauer, Michael Gastegger, Tamio Oguchi, Tomoki Yamashita

Global optimization of crystal compositions is a significant yet computationally intensive method to identify stable structures within chemical space. The specific physical properties linked to a three-dimensional atomic arrangement make this an essential task in the development of new materials. We present a method that efficiently uses active learning of neural network force fields for structure relaxation, minimizing the required number of steps in the process. This is achieved by neural network force fields equipped with uncertainty estimation, which iteratively guide a pool of randomly generated candidates toward their respective local minima. Using this approach, we are able to effectively identify the most promising candidates for further evaluation using density functional theory (DFT). Our method not only reliably reduces computational costs by up to two orders of magnitude across the benchmark systems Si16, Na8Cl8, Ga8As8 and Al4O6 but also excels in finding the most stable minimum for the unseen, more complex systems Si46 and Al16O24. Moreover, we demonstrate at the example of Si16 that our method can find multiple relevant local minima while only adding minor computational effort.

{"title":"Accelerating crystal structure search through active learning with neural networks for rapid relaxations","authors":"Stefaan S. P. Hessmann, Kristof T. Schütt, Niklas W. A. Gebauer, Michael Gastegger, Tamio Oguchi, Tomoki Yamashita","doi":"10.1038/s41524-025-01523-7","DOIUrl":"https://doi.org/10.1038/s41524-025-01523-7","url":null,"abstract":"<p>Global optimization of crystal compositions is a significant yet computationally intensive method to identify stable structures within chemical space. The specific physical properties linked to a three-dimensional atomic arrangement make this an essential task in the development of new materials. We present a method that efficiently uses active learning of neural network force fields for structure relaxation, minimizing the required number of steps in the process. This is achieved by neural network force fields equipped with uncertainty estimation, which iteratively guide a pool of randomly generated candidates toward their respective local minima. Using this approach, we are able to effectively identify the most promising candidates for further evaluation using density functional theory (DFT). Our method not only reliably reduces computational costs by up to two orders of magnitude across the benchmark systems Si<sub>16</sub>, Na<sub>8</sub>Cl<sub>8</sub>, Ga<sub>8</sub>As<sub>8</sub> and Al<sub>4</sub>O<sub>6</sub> but also excels in finding the most stable minimum for the unseen, more complex systems Si<sub>46</sub> and Al<sub>16</sub>O<sub>24</sub>. Moreover, we demonstrate at the example of Si<sub>16</sub> that our method can find multiple relevant local minima while only adding minor computational effort.</p>","PeriodicalId":19342,"journal":{"name":"npj Computational Materials","volume":"25 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automatic identification of slip pathways in ductile inorganic materials by combining the active learning strategy and NEB method
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-19 DOI: 10.1038/s41524-025-01531-7
Jun Luo, Tao Fan, Jiawei Zhang, Pengfei Qiu, Xun Shi, Lidong Chen

Ductile inorganic semiconductors have recently received considerable attention due to their metal-like mechanical properties and potential applications in flexible electronics. However, the accurate determination of slip pathways, crucial for understanding the deformation mechanism, still poses a great challenge owing to the complex crystal structures of these materials. In this study, we propose an automated workflow based on the interlayer slip potential energy surface to identify slip pathways in complex inorganic systems. Our computational approach consists of two key stages: first, an active learning strategy is utilized to efficiently and accurately model the interlayer slip potential energy surfaces; second, the climbing image nudged elastic band method is employed to identify minimum energy pathways, followed by comparative analysis to determine the final slip pathway. We discuss the validity of our selected feature vectors and models across various material systems and confirm that our approach demonstrates robust effectiveness in several case studies with both simple and complicated slip pathways. Our automated workflow opens a new avenue for the automatic identification of the slip pathways in inorganic materials, which holds promise for accelerating the high-throughput screening of ductile inorganic materials.

韧性无机半导体因其类似金属的机械特性和在柔性电子器件中的潜在应用,最近受到了广泛关注。然而,由于这些材料的晶体结构十分复杂,准确确定滑移路径对理解其变形机制至关重要,但这仍然是一个巨大的挑战。在本研究中,我们提出了一种基于层间滑移势能面的自动工作流程,用于识别复杂无机体系中的滑移途径。我们的计算方法包括两个关键阶段:首先,利用主动学习策略高效、准确地建立层间滑移势能面模型;其次,采用爬升图像推移弹力带方法识别最小能量路径,然后通过比较分析确定最终滑移路径。我们讨论了所选特征向量和模型在各种材料系统中的有效性,并证实了我们的方法在多个案例研究中,无论是简单还是复杂的滑移路径,都表现出了强大的有效性。我们的自动化工作流程为自动识别无机材料的滑移途径开辟了一条新途径,有望加速高通量筛选韧性无机材料。
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引用次数: 0
Soliquidy: a descriptor for atomic geometrical confusion
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-19 DOI: 10.1038/s41524-025-01529-1
Hagen Eckert, Sebastian A. Kube, Simon Divilov, Asa Guest, Adam C. Zettel, David Hicks, Sean D. Griesemer, Nico Hotz, Xiomara Campilongo, Siya Zhu, Axel van de Walle, Jan Schroers, Stefano Curtarolo

Tailoring material properties often requires understanding the solidification process. Herein, we introduce the geometric descriptor Soliquidy, which numerically captures the Euclidean transport cost between the translationally disordered versus ordered states of a materials. As a testbed, we apply Soliquidy to the classification of glass-forming metal alloys. By extending and combining an experimental library of metallic thin films (glass/no-glass) with the aflow.org computational database (geometrical and energetic information of mixtures) we found that the combination of Soliquity and formation enthalpies generates an effective classifier for glass formation. Such a classifier is then used to tackle a public dataset of metallic glasses showing that the glass-agnostic assumptions of Soliquity can be useful for understanding kinetically-controlled phase transitions.

{"title":"Soliquidy: a descriptor for atomic geometrical confusion","authors":"Hagen Eckert, Sebastian A. Kube, Simon Divilov, Asa Guest, Adam C. Zettel, David Hicks, Sean D. Griesemer, Nico Hotz, Xiomara Campilongo, Siya Zhu, Axel van de Walle, Jan Schroers, Stefano Curtarolo","doi":"10.1038/s41524-025-01529-1","DOIUrl":"https://doi.org/10.1038/s41524-025-01529-1","url":null,"abstract":"<p>Tailoring material properties often requires understanding the solidification process. Herein, we introduce the geometric descriptor Soliquidy, which numerically captures the Euclidean transport cost between the translationally disordered versus ordered states of a materials. As a testbed, we apply Soliquidy to the classification of glass-forming metal alloys. By extending and combining an experimental library of metallic thin films (glass/no-glass) with the <span>aflow.org</span> computational database (geometrical and energetic information of mixtures) we found that the combination of Soliquity and formation enthalpies generates an effective classifier for glass formation. Such a classifier is then used to tackle a public dataset of metallic glasses showing that the glass-agnostic assumptions of Soliquity can be useful for understanding kinetically-controlled phase transitions.</p>","PeriodicalId":19342,"journal":{"name":"npj Computational Materials","volume":"14 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Elucidation of molecular-level charge transport in an organic amorphous system
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-18 DOI: 10.1038/s41524-025-01526-4
Hiroki Sato, Syun Kanda, Hironori Kaji

Charge transport in organic amorphous systems has been considered to occur by intermolecular hopping. However, it has been difficult to reveal even the intra- and intermolecular structures because of their amorphous nature. Therefore, the details of charge transport at the molecular level have not been clarified. Here, we investigate a detailed molecular-level insight into the charge transport in an amorphous film by the analysis of multiscale simulation. The charge mobility is normally described by a constant value but is found to be widely distributed with two orders of magnitude even in the 100 nm neat film. From the detailed analysis at the molecular level, it becomes clear that there are three types of charge traps; in addition to (1) the well-known traps due to the site energy difference, we found (2) traps caused by the distribution of molecular packings in the aggregate, and (3) those by charge hopping against the electric field. These traps are the origins of the widely distributed mobilities and the understanding of these traps is important to improve mobility.

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引用次数: 0
Quadruple-well ferroelectricity and moderate switching barrier in defective wurtzite α-Al2S3: a first-principles study
IF 9.7 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Pub Date : 2025-02-17 DOI: 10.1038/s41524-025-01519-3
Yuto Shimomura, Saneyuki Ohno, Katsuro Hayashi, Hirofumi Akamatsu

Wurtzite-type ferroelectrics are highly promising for next-generation microelectronic devices due to their ferroelectric properties and integration with exiting semiconductors. However, their high coercive fields, which are close to breakdown electric fields, need to be lowered. To deal with this issue and secure device reliability, much effort has been devoted to exploring novel wurtzite compounds with lower polarization switching barriers and implementing doping strategies. Here, we report first-principles calculations on polarization switching in cation-vacancy ordered wurtzite α-Al2S3, unveiling its uniaxial quadruple-well ferroelectricity and moderate switching barrier, 51 meV/cation, which is much lower than that of conventional wurtzite ferroelectrics. There are three important features relevant to the Al vacancies leading to the uncommon quadruple-well ferroelectricity and the moderate switching barrier: mitigation of cation-cation repulsion, structural flexibility that alleviates an in-plane lattice expansion, and formation of σ-like bonding states consisting of Al 3pz and S 3pz orbitals. Biaxial compressive strain and Ga doping lower the switching barriers by up to 40%. This study encourages experimental investigation of the ferroelectric properties for defective wurtzite α-Al2S3 as a new promising material with unconventional and intriguing ferroelectricity and suggests a potential strategy for reducing switching barriers in wurtzite ferroelectrics: introducing cation vacancies.

{"title":"Quadruple-well ferroelectricity and moderate switching barrier in defective wurtzite α-Al2S3: a first-principles study","authors":"Yuto Shimomura, Saneyuki Ohno, Katsuro Hayashi, Hirofumi Akamatsu","doi":"10.1038/s41524-025-01519-3","DOIUrl":"https://doi.org/10.1038/s41524-025-01519-3","url":null,"abstract":"<p>Wurtzite-type ferroelectrics are highly promising for next-generation microelectronic devices due to their ferroelectric properties and integration with exiting semiconductors. However, their high coercive fields, which are close to breakdown electric fields, need to be lowered. To deal with this issue and secure device reliability, much effort has been devoted to exploring novel wurtzite compounds with lower polarization switching barriers and implementing doping strategies. Here, we report first-principles calculations on polarization switching in cation-vacancy ordered wurtzite α-Al<sub>2</sub>S<sub>3</sub>, unveiling its uniaxial quadruple-well ferroelectricity and moderate switching barrier, 51 meV/cation, which is much lower than that of conventional wurtzite ferroelectrics. There are three important features relevant to the Al vacancies leading to the uncommon quadruple-well ferroelectricity and the moderate switching barrier: mitigation of cation-cation repulsion, structural flexibility that alleviates an in-plane lattice expansion, and formation of σ-like bonding states consisting of Al 3p<sub><i>z</i></sub> and S 3p<sub><i>z</i></sub> orbitals. Biaxial compressive strain and Ga doping lower the switching barriers by up to 40%. This study encourages experimental investigation of the ferroelectric properties for defective wurtzite α-Al<sub>2</sub>S<sub>3</sub> as a new promising material with unconventional and intriguing ferroelectricity and suggests a potential strategy for reducing switching barriers in wurtzite ferroelectrics: <i>introducing cation vacancies</i>.</p>","PeriodicalId":19342,"journal":{"name":"npj Computational Materials","volume":"52 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143435307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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npj Computational Materials
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