npj Computational Materials最新文献

Ferroelectricity at the extreme thickness limit in the archetypal antiferroelectric PbZrO3

IF 9.7 1区材料科学

npj Computational Materials 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

{"title":"Ferroelectricity at the extreme thickness limit in the archetypal antiferroelectric PbZrO3","authors":"Nikhilesh Maity, Milan Haddad, Nazanin Bassiri-Gharb, Amit Kumar, Lewys Jones, Sergey Lisenkov, Inna Ponomareva","doi":"10.1038/s41524-025-01520-w","DOIUrl":"https://doi.org/10.1038/s41524-025-01520-w","url":null,"abstract":"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.","PeriodicalId":19342,"journal":{"name":"npj Computational Materials","volume":"89 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143486274","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

Efficient GPU-computing simulation platform JAX-CPFEM for differentiable crystal plasticity finite element method

IF 9.7 1区材料科学

npj Computational Materials Pub Date : 2025-02-22 DOI: 10.1038/s41524-025-01528-2

Fanglei Hu, Stephen Niezgoda, Tianju Xue, Jian Cao

{"title":"Efficient GPU-computing simulation platform JAX-CPFEM for differentiable crystal plasticity finite element method","authors":"Fanglei Hu, Stephen Niezgoda, Tianju Xue, Jian Cao","doi":"10.1038/s41524-025-01528-2","DOIUrl":"https://doi.org/10.1038/s41524-025-01528-2","url":null,"abstract":"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.","PeriodicalId":19342,"journal":{"name":"npj Computational Materials","volume":"50 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470614","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

First principles calculations of carrier dynamics of screw dislocation

IF 9.7 1区材料科学

npj Computational Materials Pub Date : 2025-02-21 DOI: 10.1038/s41524-025-01533-5

Qiang Gao, Zhengneng Zheng, Moshang Fan, Lin-Wang Wang

引用次数: 0

A physics-enforced neural network to predict polymer melt viscosity

IF 9.7 1区材料科学

npj Computational Materials Pub Date : 2025-02-20 DOI: 10.1038/s41524-025-01532-6

Ayush Jain, Rishi Gurnani, Arunkumar Rajan, H.Jerry Qi, Rampi Ramprasad

{"title":"A physics-enforced neural network to predict polymer melt viscosity","authors":"Ayush Jain, Rishi Gurnani, Arunkumar Rajan, H.Jerry Qi, Rampi Ramprasad","doi":"10.1038/s41524-025-01532-6","DOIUrl":"https://doi.org/10.1038/s41524-025-01532-6","url":null,"abstract":"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.","PeriodicalId":19342,"journal":{"name":"npj Computational Materials","volume":"52 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451908","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

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

npj Computational Materials Pub Date : 2025-02-20 DOI: 10.1038/s41524-024-01499-w

Hesham Salama, Oleg Shchyglo, Ingo Steinbach

{"title":"The interplay between the martensitic transformation rate and the rate of plastic relaxation during martensitic transformation in low-carbon steel, a phase-field study","authors":"Hesham Salama, Oleg Shchyglo, Ingo Steinbach","doi":"10.1038/s41524-024-01499-w","DOIUrl":"https://doi.org/10.1038/s41524-024-01499-w","url":null,"abstract":"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.","PeriodicalId":19342,"journal":{"name":"npj Computational Materials","volume":"2 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462442","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

Accelerating crystal structure search through active learning with neural networks for rapid relaxations

IF 9.7 1区材料科学

npj Computational Materials 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

{"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":"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.","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

npj Computational Materials Pub Date : 2025-02-19 DOI: 10.1038/s41524-025-01531-7

Jun Luo, Tao Fan, Jiawei Zhang, Pengfei Qiu, Xun Shi, Lidong Chen

{"title":"Automatic identification of slip pathways in ductile inorganic materials by combining the active learning strategy and NEB method","authors":"Jun Luo, Tao Fan, Jiawei Zhang, Pengfei Qiu, Xun Shi, Lidong Chen","doi":"10.1038/s41524-025-01531-7","DOIUrl":"https://doi.org/10.1038/s41524-025-01531-7","url":null,"abstract":"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.","PeriodicalId":19342,"journal":{"name":"npj Computational Materials","volume":"1 1","pages":""},"PeriodicalIF":9.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451909","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

Soliquidy: a descriptor for atomic geometrical confusion

IF 9.7 1区材料科学

npj Computational Materials 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

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

npj Computational Materials Pub Date : 2025-02-18 DOI: 10.1038/s41524-025-01526-4

Hiroki Sato, Syun Kanda, Hironori Kaji

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

npj Computational Materials Pub Date : 2025-02-17 DOI: 10.1038/s41524-025-01519-3

Yuto Shimomura, Saneyuki Ohno, Katsuro Hayashi, Hirofumi Akamatsu

{"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":"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.","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