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A review:applications of the phase field method in predicting microstructure and property evolution of irradiated nuclear materials

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npj Computational Materials 2017年第1期3卷 333-349页

作者： Yulan Li Shenyang Hu Xin Sun marius stan Pacific Northwest National Laboratory 902 Battelle BoulevardRichlandWA 99352USA Argonne National Laboratory 9700 South Cass AvenueLemontIL 60439USA

Complex microstructure changes occur in nuclear fuel and structural materials due to the extreme environments of intense irradiation and high temperature.This paper evaluates the role of the phase field method in predicting the microstructure evolution of irradiated nuclear materials and the impact on their mechanical,thermal,and magnetic properties.The paper starts with an overview of the important physical mechanisms of defect evolution and the significant gaps in simulating microstructure evolution in irradiated nuclear materials.Then,the phase field method is introduced as a powerful and predictive tool and its applications to microstructure and property evolution in irradiated nuclear materials are reviewed.The review shows that(1)Phase field models can correctly describe important phenomena such as spatial-dependent generation,migration,and recombination of defects,radiation-induced dissolution,the Soret effect,strong interfacial energy anisotropy,and elastic interaction;(2)The phase field method can qualitatively and quantitatively simulate two-dimensional and three-dimensional microstructure evolution,including radiation-induced segregation,second phase nucleation,void migration,void and gas bubble superlattice formation,interstitial loop evolution,hydrate formation,and grain growth,and(3)The Phase field method correctly predicts the relationships between microstructures and properties.The final section is dedicated to a discussion of the strengths and limitations of the phase field method,as applied to irradiation effects in nuclear materials.

关键词： properties irradiated phase

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Machine-learned interatomic potentials by active learning:amorphous and liquid hafnium dioxide

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npj Computational Materials 2020年第1期6卷 803-810页

作者： Ganesh Sivaraman Anand Narayanan Krishnamoorthy Matthias Baur Christian Holm marius stan Gábor Csányi Chris Benmore Álvaro Vázquez-Mayagoitia Leadership Computing Facility Argonne National LaboratoryArgonneIL 60439USA Institute for Computational Physics Universität StuttgartAllmandring 3Stuttgart 70569Germany Helmholtz-Institute Münster:Ionics in Energy Storage(IEK-12) Forschungszentrum Jülich GmbHCorrensstrasse 46Münster 48149Germany Applied Materials Division Argonne National LaboratoryArgonneIL 60439USA Department of Engineering University of CambridgeTrumpington StreetCambridge CB21PZUK X-ray Science Division Argonne National LaboratoryArgonneIL 60439USA Computational Science Division Argonne National LaboratoryArgonneIL 60439USA

We propose an active learning scheme for automatically sampling a minimum number of uncorrelated configurations for fitting the Gaussian Approximation Potential(GAP).Our active learning scheme consists of an unsupervised machine learning(ML)scheme coupled with a Bayesian optimization technique that evaluates the GAP model.We apply this scheme to a Hafnium dioxide(HfO2)dataset generated from a“melt-quench”ab initio molecular dynamics(AIMD)protocol.Our results show that the active learning scheme,with no prior knowledge of the dataset,is able to extract a configuration that reaches the required energy fit tolerance.Further,molecular dynamics(MD)simulations performed using this active learned GAP model on 6144 atom systems of amorphous and liquid state elucidate the structural properties of HfO2 with near ab initio precision and quench rates(i.e.,1.0 K/ps)not accessible via AIMD.The melt and amorphous X-ray structural factors generated from our simulation are in good agreement with experiment.In addition,the calculated diffusion constants are in good agreement with previous ab initio studies.

关键词： amorphous dioxide scheme

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Highly luminescent europium and terbium complexes based on succinimide and N-hydroxysuccinimide

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Journal of Rare Earths 2012年第5期30卷 401-407页

作者： Corneliu Sergiu stan Ioan Rosca Daniel Sutiman marius Sebastian Secula Faculty of Chemical Engineering and Environmental Protection Gheorghe Asachi Technical University of Iasi73 D.Mangeron700050IasiRomania

The preparation of two highly luminescent europium（Ill） and terbium（Ill） complexes with succinimide （SI） and N-hydroxysuccinimide （NHSI） were reported, which were further investigated through elemental chemical analysis, thermal analysis, FT-IR, powder X-ray diffraction, SEM and fluorescence spectroscopy. Data collected through these analysis revealed the formation of the Eu（III） and Th（III） complexes with the above mentioned ligands at a metal to ligand （M：L） molar ratio of 1：3. Interesting conclusions regarding the effi- cient sensitization through the coordination site of the lanthanide luminescent centers were retained from the photoluminescent spectra inves- tigation. Strong luminescence emission was observed in case of Eu（III）-SI and Tb（III）-NHSI complexes while the corresponding Eu（III）-NHSI and Tb（III）-SI complexes exhibited no photo luminescent properties. Newly obtained luminescent lanthanide complexes may be of particular interest for various applications in optoelectronics.

关键词： lanthanide complex succinimide N-hydroxysuccinimide luminescence rare earths

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山水之间的北国仙境闯入克兰河畔的童话世界

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城市地理 2024年第1期 28-37页

作者：涵曦 stan(图) 小黎(图) 涵曦(图) 吕吉敏(图) 跟滕老师去旅行(图) 图虫

在阿勒泰的广袤天地间,穿城而过的克兰河与两岸耸立的将军山、骆驼峰,见证了她的前世今生,各民族的迁徙、融合与发展,铸就了如今的“中国雪都”阿勒泰。

关键词：克兰河骆驼峰童话世界前世今生阿勒泰仙境融合与发展

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景观作为缝合都市与建筑的动态模型——斯坦·艾伦访谈

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建筑师 2024年第1期 93-100页

作者：孙志健斯坦·艾伦哥伦比亚大学普林斯顿大学纽约stan Allen Architects事务所

访谈由斯坦·艾伦对景观都市主义理论的研究引入到对景观在建筑与城市学之间关系的探讨,由此展开他近年关注的基础设施都市主义、地景建筑和场域建筑的理念,使景观成为衔接建筑与城市学的动态模型,同时结合当代城市复杂性和景观都市主... 详细信息

访谈由斯坦·艾伦对景观都市主义理论的研究引入到对景观在建筑与城市学之间关系的探讨,由此展开他近年关注的基础设施都市主义、地景建筑和场域建筑的理念,使景观成为衔接建筑与城市学的动态模型,同时结合当代城市复杂性和景观都市主义折射出的问题,提出将城市基础设施作为宏观框架而建筑实体在这片场域中自然生长的设计理念。

关键词：景观基础设施场域城市性实体

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Recognition of rock anisotropy using integrated seismic approach-A case in Strzegom and Podlesna,Poland

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第7期15卷 1759-1767页

作者： Iwona stan-Kłeczek Artur Marciniak University of Silesia Faculty of Natural SciencesSosnowiecPoland Institute of Geophysics of Polish Academy of Sciences WarsawPoland

This paper presents the integration of seismic refraction and multichannel analysis of surface wave(MASW)measurements to investigate the anisotropy of P-and S-wave velocities.Additionally,synthetic forward modelling is presented as a tool for supporting seismic anisotropy studies.The geophysical measurements of cracks allowed to recognise the fracturing of a granite rock mass in a Paleozoic granite quarry(Strzegom,Poland)and a dolomite rock mass in a Triassic dolomite quarry(Podlesna,Poland).Application of the forward modelling supports the interpretation of seismic methods,simplifying data processing and verifying the final results based on data from difficult seismic conditions.As a result of direct measurements,two crack systems were determined in granite rock mass:NNE-SSW and NNW-SSE,and two in dolomite rock mass:NNE-SSW and NW-SE.Furthermore,the numerical results show the relationship between the highest values of P-and S-wave velocities and separated crack systems which allowed an unequivocal interpretation of the direction of stress,resulting in the deformations.The obtained information is promising to be helpful in mining exploration for optimising excavation works.

关键词： Fracturing Anisotropy Seismic refraction Multichannel analysis of surface wave(MASW) Forward modelling

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A New Fuzzy Adaptive Algorithm to Classify Imbalanced Data

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Computers, Materials & Continua 2022年第1期70卷 73-89页

作者： Harshita Patel Dharmendra Singh Rajput Ovidiu Petru stan Liviu Cristian Miclea School of Information Technology&Engineering Vellore Institute of TechnologyVellore632014India Technical University of Cluj Napoca Faculty of Automation and Computer ScienceCluj Napoca400114Romania

Classification of imbalanced data is a well explored issue in the data mining and machine learning community where one class representation is overwhelmed by other classes.The Imbalanced distribution of data is a natural occurrence in real world datasets,so needed to be dealt with carefully to get important insights.In case of imbalance in data sets,traditional classifiers have to sacrifice their performances,therefore lead to misclassifications.This paper suggests a weighted nearest neighbor approach in a fuzzy manner to deal with this issue.We have adapted the‘existing algorithm modification solution’to learn from imbalanced datasets that classify data without manipulating the natural distribution of data unlike the other popular data balancing methods.The K nearest neighbor is a non-parametric classification method that is mostly used in machine learning problems.Fuzzy classification with the nearest neighbor clears the belonging of an instance to classes and optimal weights with improved nearest neighbor concept helping to correctly classify imbalanced data.The proposed hybrid approach takes care of imbalance nature of data and reduces the inaccuracies appear in applications of original and traditional classifiers.Results show that it performs well over the existing fuzzy nearest neighbor and weighted neighbor strategies for imbalanced learning.

关键词： Machine learning fuzzy classification nearest neighbor adaptive approach optimal weights

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Reproducibility of deposition and industrial applications of stable superhard nanocomposites

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中国有色金属学会会刊：英文版 2004年第Z1期14卷 19-24页

作者： stan Veprek Department for Chemistry Technical University Munich Lichtenbergstr. 4 D-85747 Garching b. Munich Germany

After a brief introduction regarding the different approaches to superhard coatings we shall concentrate on the problem of the reproducibility of the deposition of superhard and thermally very stable nanocomposites according to the design principle published by Veprek and Reiprich in 1995. It will be shown that either the choice of inappropriate deposition conditions, in contradiction to our design principle, or impurities in the coatings are the reason for the lack of reproducibility of our earlier results by many other workers. We shall also briefly summarize the recent industrial applications.

关键词： superhard nanocomposite reproducibility of deposition industrial application

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Express analysis for prioritization:Best-Worst Scaling alteration to System 1

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Journal of Management Analytics 2020年第1期7卷 12-27页

作者： stan Lipovetsky Minneapolis MinnesotaUSA

The work considers modification of the Best–Worst Scaling(BWS)to the so-called System 1(S1)approach.S1 was described by D.Kahneman as a spontaneous and automatic reaction by an unconsciousway in which human decision-makers choose among multiple alternatives.Application of S1 can be seen as a simplified BWS for data eliciting and express analysis of prioritization between many compared items.In S1,a respondent picks the items with which she feels“happy”,and those can be one,several,all,or none items in a task.Estimation of utilities is performed by multinomial-logit modeling with different optimization criteria which produce parameters of the models and choice probabilities of the items.Numerical examples by marketing research data are encouraging and demonstrating that spontaneous choice decisions can make S1 approach very fast,efficient,and convenient for express analysis of items prioritization,especially for big data.

关键词： System 1 BWS max diff MNLutility choice probability prioritization

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The influence of metabolic imbalances and oxidative stress on the outcome of critically ill polytrauma patients: a review

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Burns & Trauma 2017年第1期5卷 17-23页

作者： Alexandru Florin Rogobete Dorel Sandesc marius Papurica Emil Robert Stoicescu Sonia Elena Popovici Lavinia Melania Bratu Corina Vernic Adriana Mariana Sas Adrian Tudor stan Ovidiu Horea Bedreag Faculty of Medicine Victor Babes University of Medicine and PharmacyStr.Eftimie Murgu Nr.2Timisoara300041TimisRomania Clinic of Anaesthesia and Intensive Care Emergency County Hospital“PiusBrinzeu”Bd.Liviu Rebreanu Nr.156Timisoara300736TimisRomania

The critically ill polytrauma patient presents with a series of associated pathophysiologies secondary to the traumatic injuries. The most important include systemic inflammatory response syndrome (SIRS), sepsis, oxidative stress (OS), metabolic disorders, and finally multiple organ dysfunction syndrome (MODS) and death. The poor outcome of these patients is related to the association of the aforementioned pathologies. The nutrition of the critically ill polytrauma patient is a distinct challenge because of the rapid changes in terms of energetic needs associated with hypermetabolism, sepsis, SIRS, and OS. Moreover, it has been proven that inadequate nutrition can prolong the time spent on a mechanical ventilator and the length of stay in an intensive care unit (ICU). A series of mathematical equations can predict the energy expenditure (EE), but they have disadvantages, such as the fact that they cannot predict the EE accurately in the case of patients with hypermetabolism. Indirect calorimetry (IC) is another method used for evaluating and monitoring the energy status of critically ill patients. In this update paper, we present a series of pathophysiological aspects associated with the metabolic disaster affecting the critically ill polytrauma patient. Furthermore, we present different non-invasive monitoring methods that could help the intensive care physician in the adequate management of this type of patient.

关键词： Critically ill Energy expenditure Indirect calorimetry Metabolic disaster Oxidative stress Overfeeding Underfeeding Polytrauma

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