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| 1 | Segregation-assisted spinodal and transient spinodal phase separation at grain boundaries显示文摘Segregation to grain boundaries affects their cohesion,corrosion,and embrittlement and plays a critical role in heterogeneous nucleation.In order to quantitatively study segregation and low-dimensional phase separation at grain boundaries,here,we apply a density-based phase-field model.The current model describes the grain-boundary thermodynamic properties based on available bulk thermodynamic data,while the grain-boundary-density profile is obtained using atomistic simulations.To benchmark the performance of the model,Mn grain-boundary segregation in the Fe–Mn system is studied.3D simulation results are compared against atom probe tomography measurements conducted for three alloy compositions.We show that a continuous increase in the alloy composition results in a discontinuous jump in the segregation isotherm.The jump corresponds to a spinodal phase separation at grain boundary.For alloy compositions above the jump,we reveal an interfacial transient spinodal phase separation.The transient spinodal phenomenon opens opportunities for knowledge-based microstructure design through the chemical manipulation of grain boundaries.The proposed density-based model provides a powerful tool to study thermodynamics and kinetics of segregation and phase changes at grain boundaries. | Reza Darvishi Kamachali Alisson Kwiatkowski da Silva Eunan McEniry Dirk Ponge Baptiste Gault Jörg Neugebauer Dierk Raabe | 2020 | npj Computational Materials2020，，1： | 2 |
| 2 | TEXTURE AND CRYSTALLINITY EVOLUTION IN ISOTACTIC POLYPROPYLENE INDUCED BY ROLLING AND THEIR INFLUENCE ON MECHANICAL PROPERTIES显示文摘The orientation and crystallinity evolution of isotactic polypropylene (iPP) induced by rolling were studied using wide angle X-ray scattering with an area detector. The tensile mechanical properties of rolled isotactic polypropylene sheets were also measured in this work. The texture component method was used to analyze the rolling texture. The rolling texture consists mainly of (010)[001], (130)[001] and [001]//RD fiber components in the sample with a rolling true strain of 1.5. The results reveal that crystallinity drastically decreases during rolling. It is suggested that amorphization is a deformation mechanism which takes place as an alternative to crystallographic intralamellar slip depending on the orientation of the lamellae. Both the orientation and crystallinity affect the tensile mechanical properties of rolled polypropylene. Crystallinity influences the elastic modulus on both directions and yield strength on transverse direction at the first stage of deformation. Orientation is the main reason for the changes of mechanical properties, especially at the latter part of deformation. The changes of both tensile strength and elongation percentage on rolling direction are larger than those on transverse direction, which results from the orientation. At last, the anisotropic mechanical properties occur on the rolling and transverse direction: high tensile strength with low elongation percentage on rolling direction and low tensile strength with high elongation percentage on transverse direction. | Dierk Raabe 贾涓 | 2006 | Chinese Journal of Polymer Science2006，24，4： | 2 |
| 3 | Teaching solid mechanics to artificial intelligence—a fast solver for heterogeneous materials显示文摘We propose a deep neural network(DNN)as a fast surrogate model for local stress calculations in inhomogeneous non-linear materials.We show that the DNN predicts the local stresses with 3.8%mean absolute percentage error(MAPE)for the case of heterogeneous elastic media and a mechanical contrast of up to factor of 1.5 among neighboring domains,while performing 103 times faster than spectral solvers.The DNN model proves suited for reproducing the stress distribution in geometries different from those used for training.In the case of elasto-plastic materials with up to 4 times mechanical contrast in yield stress among adjacent regions,the trained model simulates the micromechanics with a MAPE of 6.4%in one single forward evaluation of the network,without any iteration.The results reveal an efficient approach to solve non-linear mechanical problems,with an acceleration up to a factor of 8300 for elastic-plastic materials compared to typical solvers. | Jaber Rezaei Mianroodi Nima H.Siboni Dierk Raabe | 2021 | npj Computational Materials2021，，1： | 2 |
| 4 | Orientation gradients and geometrically necessary dislocations in ultrafine grained dual-phase steels studied by 2D and 3D EBSD显示文摘 | Marion Calcagnotto Dirk Ponge Eralp Demir Dierk Raabe | 2010 | Materials Science & Engineering A2010，，10： | 1 |
| 5 | Atomic scale effects of alloying, partitioning, solute drag and austempering on the mechanical properties of high-carbon bainitic–austenitic TRIP steels显示文摘 | Jae-Bok Seol Dierk Raabe Puck-Pa Choi Yung-Rok Im Chan-Gyung Park | 2012 | Acta Materialia2012，，17： | 1 |
| 6 | Rolling and recrystallization textures of Bcc steel显示文摘 | Martin Holscher Dierk Raabe Kurt Lucke | 1991 | Steel Research1991，62，12： | 1 |
| 7 | Deformation and fracture mechanisms in fine- and ultrafine-grained ferrite/martensite dual-phase steels and the effect of aging显示文摘 | Marion Calcagnotto Yoshitaka Adachi Dirk Ponge Dierk Raabe | 2010 | Acta Materialia2010，，2： | 1 |
| 8 | On the room temperature deformation mechanisms of a Mg–Y–Zn alloy with long-period-stacking-ordered structures显示文摘 | Jin-Kyung Kim Stefanie Sandl?bes Dierk Raabe | 2015 | Acta Materialia2015，，： | 1 |
| 9 | Tensile deformation characteristics of bulk ultrafine-grained austenitic stainless steel produced by thermal cycling显示文摘 | Ravi Kumara B Raabe Dierk | 2012 | Scripta Mater2012，66，： | 1 |
| 10 | Overview on Basic Types of Hot Rolling Textures of Steels显示文摘 | Dierk Raabe | 2003 | Steel Research2003，74，5： | 1 |
| 11 | Carbon partitioning during quenching and partitioning heat treatment accompanied by carbide precipitation显示文摘 | Yuki Toji Goro Miyamotob Dierk Raabe | 2015 | Acta Materialia2015，86，1： | 1 |
| 12 | Interaction between recrystal- lization and phase transformation during intercritical annealing in a cold-rolled dual-phase steel:A cellular automaton model 显示文摘 | Zheng Chengwu Dierk Raabe | 2013 | Acta Materialia2013，61，14： | 1 |
| 13 | Lattice Boltzmann modeling of dendritic growth in a forced melt convection显示文摘 | Dongke Sun Mingfang Zhu Shiyan Pan Dierk Raabe | 2008 | Acta Materialia2008，，6： | 1 |
| 14 | Hierarchical modeling of the elastic properties of bone at submicron scales: The role of extrafibrillar mineralization 显示文摘 | Svetoslav Nikolov Dierk Raabe | 2008 | Biophys J2008，94，11： | 1 |
| 15 | 轧制和退火过程中等规聚丙烯的力学性能显示文摘借助拉伸试验对轧制和退火后的等规聚丙烯进行了轧向及横向上力学性能的研究。结果发现,结晶度和大分子链的取向是影响材料力学性能的主要原因,力学性能的变化主要发生在轧制过程中。轧制后,大分子链沿轧向排列,出现各向异性:轧向上拥有高的拉伸强度和低的延伸率。结晶度的变化主要是影响材料的弹性模量和横向上的屈服强度。退火后,大分子链的取向发生较小的变化。非晶部分的再晶化与无序化共同影响材料的性能,在伸拉强度没有减少的基础上增大了材料轧向上的延伸率。 | 贾涓 毛卫民 Dierk Raabe | 2008 | 高分子材料科学与工程2008，24，2： | 1 |
| 16 | Retention of the Goss orientation between micobands during cold rolling of an Fe-3% Si single crystal 显示文摘 | Dorothee Dorner Stefan Zaefferer Dierk Raabe | 2007 | Acta Materialia2007，55，： | 1 |
| 17 | Interaction between recrystallization and phase transformation during intercritical annealing in a cold-rolled dual-phase steel: A cellular automaton model显示文摘 | Chengwu Zheng Dierk Raabe | 2013 | Acta Materialia2013，，14： | 1 |
| 18 | Prediction of post-dynamic austenite-to-ferrite transformation and reverse transformation in a low-carbon steel by cellular automaton modeling显示文摘 | Chengwu Zheng Dierk Raabe Dianzhong Li | 2012 | Acta Materialia2012，，12： | 1 |
| 19 | Lossless multi-scale constitutive elastic relations with artificial intelligence显示文摘A seamless and lossless transition of the constitutive description of the elastic response of materials between atomic and continuum scales has been so far elusive.Here we show how this problem can be overcome by using artificial intelligence(AI).A convolutional neural network(CNN)model is trained,by taking the structure image of a nanoporous material as input and the corresponding elasticity tensor,calculated from molecular statics(MS),as output.Trained with the atomistic data,the CNN model captures the size-and pore-dependency of the material’s elastic properties which,on the physics side,derive from its intrinsic stiffness as well as from surface relaxation and non-local effects.To demonstrate the accuracy and the efficiency of the trained CNN model,a finite element method(FEM)-based result of an elastically deformed nanoporous beam equipped with the CNN as constitutive law is compared with that obtained by a full atomistic simulation.The trained CNN model predicts the elasticity tensor in the test dataset with a root-mean-square error of 2.4 GPa(3.0%of the bulk modulus)when compared to atomistic calculations.On the other hand,the CNN model is about 230 times faster than the MS calculation and does not require changing simulation methods between different scales.The efficiency of the CNN evaluation together with the preservation of important atomistic effects makes the trained model an effective atomistically informed constitutive model for macroscopic simulations of nanoporous materials,optimization of nanostructures,and the solution of inverse problems. | Jaber Rezaei Mianroodi Shahed Rezaei Nima H.Siboni Bai-Xiang Xu Dierk Raabe | 2022 | npj Computational Materials2022，，1： | 1 |
| 20 | Retention of the goss orientation between microbands during cold rolling of an Fe3% single crystal显示文摘 | Dorothee Dorner Stefan Zaefferer Dierk Raabe | 2006 | Aeta Materialia2006，55，： | 1 |
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