Although phase separation is a ubiquitous phenomenon, the interactions between multiple components make it difficult to accurately model and predict. In recent years, machine learning has been widely used in physics s...Although phase separation is a ubiquitous phenomenon, the interactions between multiple components make it difficult to accurately model and predict. In recent years, machine learning has been widely used in physics simulations. Here,we present a physical information-enhanced graph neural network(PIENet) to simulate and predict the evolution of phase separation. The accuracy of our model in predicting particle positions is improved by 40.3% and 51.77% compared with CNN and SVM respectively. Moreover, we design an order parameter based on local density to measure the evolution of phase separation and analyze the systematic changes with different repulsion coefficients and different Schmidt numbers.The results demonstrate that our model can achieve long-term accurate predictions of order parameters without requiring complex handcrafted features. These results prove that graph neural networks can become new tools and methods for predicting the structure and properties of complex physical systems.展开更多
A high-power CW Yb:YAG slab laser amplifier with no adaptive optics correction has been experimentally established.At room temperature,the amplifier emits a power of 22 kW with an average beam quality(β)of less than ...A high-power CW Yb:YAG slab laser amplifier with no adaptive optics correction has been experimentally established.At room temperature,the amplifier emits a power of 22 kW with an average beam quality(β)of less than 3 in 0.5 min.To our knowledge,this is the brightest slab laser without closed-loop adaptive optics demonstrated to date.In addition,an extracted power of 17 kW with an optical extraction efficiency of 33%,corresponding to a residual optical path difference of less than 0.5μm,is achieved with the single Yb:YAG slab gain module.The slab gain module has the potential to be scalable to higher powers while maintaining good beam quality.This makes a high-power solid-state laser system simpler and more robust.展开更多
随着数据科学和材料科学的进步,人们如今可构建出较为准确的人工智能模型,用于材料性质预测.本文中,我们以170,714个无机晶体化合物的高通量第一性原理计算数据集为基础,训练得到了可精确预测无机化合物形成能的机器学习模型.相比于同...随着数据科学和材料科学的进步,人们如今可构建出较为准确的人工智能模型,用于材料性质预测.本文中,我们以170,714个无机晶体化合物的高通量第一性原理计算数据集为基础,训练得到了可精确预测无机化合物形成能的机器学习模型.相比于同类工作,本项研究以超大数据集为出发点,构建出无机晶体形成能的高精度泛化模型,可外推至广阔相空间,其中的Dense Net神经网络模型精度可以达到R^(2)=0.982和平均绝对误差(MAE)=0.072 eV atom^(-1).上述模型精度的提升源自一系列新型特征描述符,这些描述符可有效提取出原子与领域原子间的电负性和局域结构等信息,从而精确捕捉到原子间的相互作用.本文为新材料搜索提供了一种高效、低成本的结合能预测手段.展开更多
Objective:The morphology analysis of whole-mount mouse embryos was observed using an improved paraffin section technique.Methods:Mouse embryos of varying embryonic ages were collected and whole-mount embryo paraffin s...Objective:The morphology analysis of whole-mount mouse embryos was observed using an improved paraffin section technique.Methods:Mouse embryos of varying embryonic ages were collected and whole-mount embryo paraffin sections were prepared using PFA-intravenously injected fixation,prolonged dehydration,and paraffin embedding.Hematoxylin and eosin(H&E)staining and immunohistochemical staining were employed to evaluate the quality of sections,with different tissues being observed labeled by CD34.Results:Following a series of tissue processing and staining procedures,the structure of the whole-mount mouse embryo was well-preserved,and the staining was clear and easily distinguishable.Embryos of different embryonic ages were treated differently,yet the quality of tissue processing remained highly consistent.Conclusion:Tissue processing and staining have been significantly improved,allowing for the easy acquisition of whole-mount mouse embryos of different ages through simplified methods of tissue fixation and dehydration duration.The staining results are clear and stable,providing technical support for the study of mouse embryo development.展开更多
Magnetic topological states of matter provide a fertile playground for emerging topological physics and phenomena.The current main focus is on materials whose magnetism stems from 3d magnetic transition elements,e.g.,...Magnetic topological states of matter provide a fertile playground for emerging topological physics and phenomena.The current main focus is on materials whose magnetism stems from 3d magnetic transition elements,e.g.,MnBi_(2)Te_(4),Fe_(3)Sn_(2),and Co_(3)Sn_(2)S_(2).In contrast,topological materials with the magnetism from rare earth elements remain largely unexplored.Here we report rare earth antiferromagnet GdAuAl_(4)Ge_(2)as a candidate magnetic topological metal.Angle resolved photoemission spectroscopy(ARPES)and first-principles calculations have revealed multiple bulk bands crossing the Fermi level and pairs of low energy surface states.According to the parity and Wannier charge center analyses,these bulk bands possess nontrivial Z2 topology,establishing a strong topological insulator state in the nonmagnetic phase.Furthermore,the surface band pairs exhibit strong termination dependence which provides insight into their origin.Our results suggest GdAuAl_(4)Ge_(2)as a rare earth platform to explore the interplay between band topology,magnetism and f electron correlation,calling for further study targeting on its magnetic structure,magnetic topology state,transport behavior,and microscopic properties.展开更多
In this paper, we introduce high-order finite volume methods for the multi-term time fractional sub-diffusion equation. The time fractional derivatives are described in Caputo’s sense. By using some operators, we obt...In this paper, we introduce high-order finite volume methods for the multi-term time fractional sub-diffusion equation. The time fractional derivatives are described in Caputo’s sense. By using some operators, we obtain the compact finite volume scheme have high order accuracy. We use a compact operator to deal with spatial direction;then we can get the compact finite volume scheme. It is proved that the finite volume scheme is unconditionally stable and convergent in L<sub>∞</sub>-norm. The convergence order is O(τ<sup>2-α</sup> + h<sup>4</sup>). Finally, two numerical examples are given to confirm the theoretical results. Some tables listed also can explain the stability and convergence of the scheme.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.11702289)the Key Core Technology and Generic Technology Research and Development Project of Shanxi Province,China(Grant No.2020XXX013)。
文摘Although phase separation is a ubiquitous phenomenon, the interactions between multiple components make it difficult to accurately model and predict. In recent years, machine learning has been widely used in physics simulations. Here,we present a physical information-enhanced graph neural network(PIENet) to simulate and predict the evolution of phase separation. The accuracy of our model in predicting particle positions is improved by 40.3% and 51.77% compared with CNN and SVM respectively. Moreover, we design an order parameter based on local density to measure the evolution of phase separation and analyze the systematic changes with different repulsion coefficients and different Schmidt numbers.The results demonstrate that our model can achieve long-term accurate predictions of order parameters without requiring complex handcrafted features. These results prove that graph neural networks can become new tools and methods for predicting the structure and properties of complex physical systems.
基金supported by the Joint Fund of the National Natural Science Foundation of China and the China Academy of Engineering Physics(No.U1830132)the National Natural Science Foundation of China(No.62105313)。
文摘A high-power CW Yb:YAG slab laser amplifier with no adaptive optics correction has been experimentally established.At room temperature,the amplifier emits a power of 22 kW with an average beam quality(β)of less than 3 in 0.5 min.To our knowledge,this is the brightest slab laser without closed-loop adaptive optics demonstrated to date.In addition,an extracted power of 17 kW with an optical extraction efficiency of 33%,corresponding to a residual optical path difference of less than 0.5μm,is achieved with the single Yb:YAG slab gain module.The slab gain module has the potential to be scalable to higher powers while maintaining good beam quality.This makes a high-power solid-state laser system simpler and more robust.
基金the financial support from the Chinese Academy of Sciences(CAS-WX2021PY-0102,ZDBS-LY-SLH007,and XDB33020000)。
文摘随着数据科学和材料科学的进步,人们如今可构建出较为准确的人工智能模型,用于材料性质预测.本文中,我们以170,714个无机晶体化合物的高通量第一性原理计算数据集为基础,训练得到了可精确预测无机化合物形成能的机器学习模型.相比于同类工作,本项研究以超大数据集为出发点,构建出无机晶体形成能的高精度泛化模型,可外推至广阔相空间,其中的Dense Net神经网络模型精度可以达到R^(2)=0.982和平均绝对误差(MAE)=0.072 eV atom^(-1).上述模型精度的提升源自一系列新型特征描述符,这些描述符可有效提取出原子与领域原子间的电负性和局域结构等信息,从而精确捕捉到原子间的相互作用.本文为新材料搜索提供了一种高效、低成本的结合能预测手段.
基金the funding of Department of Education of Guangdong Province,China(Grant No.2020KTSCX036Grant No.2023A1515010544)Health Commission of Guangdong Province(A2023342).
文摘Objective:The morphology analysis of whole-mount mouse embryos was observed using an improved paraffin section technique.Methods:Mouse embryos of varying embryonic ages were collected and whole-mount embryo paraffin sections were prepared using PFA-intravenously injected fixation,prolonged dehydration,and paraffin embedding.Hematoxylin and eosin(H&E)staining and immunohistochemical staining were employed to evaluate the quality of sections,with different tissues being observed labeled by CD34.Results:Following a series of tissue processing and staining procedures,the structure of the whole-mount mouse embryo was well-preserved,and the staining was clear and easily distinguishable.Embryos of different embryonic ages were treated differently,yet the quality of tissue processing remained highly consistent.Conclusion:Tissue processing and staining have been significantly improved,allowing for the easy acquisition of whole-mount mouse embryos of different ages through simplified methods of tissue fixation and dehydration duration.The staining results are clear and stable,providing technical support for the study of mouse embryo development.
基金Project supported by the National Key Research and Development Program of China (Grant No. 2022YFA1403700)the National Natural Science Foundation of China (Grant No. 12074163)+2 种基金the Basic and Applied Basic Research Foundation of Guangdong Province, China (Grants Nos. 2022B1515020046, 2022B1515130005, and 2021B1515130007)the Innovative and Entrepreneurial Research Team Program of Guangdong Province, China (Grant Nos. 2019ZT08C044)Shenzhen Science and Technology Program (Grant No. KQTD20190929173815000)
文摘Magnetic topological states of matter provide a fertile playground for emerging topological physics and phenomena.The current main focus is on materials whose magnetism stems from 3d magnetic transition elements,e.g.,MnBi_(2)Te_(4),Fe_(3)Sn_(2),and Co_(3)Sn_(2)S_(2).In contrast,topological materials with the magnetism from rare earth elements remain largely unexplored.Here we report rare earth antiferromagnet GdAuAl_(4)Ge_(2)as a candidate magnetic topological metal.Angle resolved photoemission spectroscopy(ARPES)and first-principles calculations have revealed multiple bulk bands crossing the Fermi level and pairs of low energy surface states.According to the parity and Wannier charge center analyses,these bulk bands possess nontrivial Z2 topology,establishing a strong topological insulator state in the nonmagnetic phase.Furthermore,the surface band pairs exhibit strong termination dependence which provides insight into their origin.Our results suggest GdAuAl_(4)Ge_(2)as a rare earth platform to explore the interplay between band topology,magnetism and f electron correlation,calling for further study targeting on its magnetic structure,magnetic topology state,transport behavior,and microscopic properties.
文摘In this paper, we introduce high-order finite volume methods for the multi-term time fractional sub-diffusion equation. The time fractional derivatives are described in Caputo’s sense. By using some operators, we obtain the compact finite volume scheme have high order accuracy. We use a compact operator to deal with spatial direction;then we can get the compact finite volume scheme. It is proved that the finite volume scheme is unconditionally stable and convergent in L<sub>∞</sub>-norm. The convergence order is O(τ<sup>2-α</sup> + h<sup>4</sup>). Finally, two numerical examples are given to confirm the theoretical results. Some tables listed also can explain the stability and convergence of the scheme.
