A、多尺度多物理场模拟
[1] Xu Zhang , Ran Yi, C P Chen*. Development of a multi-phase flamelet generated manifold for spray combustion simulation. Proceedings of the ASME 2020, Turbomachinery Technical Conference and Exposition. June 22 – 26, 2020, London, England, UK.
[2] Y. Liu, C. Cheng, V. Ziaei-Rad, Y. Shen*. A micromechanics-informed phase field model for brittle fracture accounting for the unilateral constraint. Engineering Fracture Mechanics. Accepted. (link)
[3] Y. Wang, Tomáš Šikola and Miroslav Kolíbal, Collector Droplet Behavior during Formation of Nanowire Junctions, J. Phys. Chem. Lett., 11, 6498-6504 (2020).
[4] Wenwei Wu, Enrico Calzavarini, François G. Schmitt, Lipo Wang, Fluctuations and correlations of reactive scalars near chemical equilibrium in incompressible turbulen, PHYSICAL REVIEW FLUIDS 5, 084608 (2020)
[5] Shouhang Li, Ao Wang, Yue Hu, Xiaokun Gu, Zhen Tong, Hua Bao*,Anomalous thermal transport in metallic transition-metal nitrides originated from strong electron-phonon interactions, Materials Today Physics, 100256, 2020
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[7] Ran Yi, Xu Zhang, Tao Yang, C P Chen*. Spray Flamelet Modeling of Kerosene Spray Combustion. AIAA Propulsion and Energy 2019 Forum. Indianapolis, IN, August 19-22, 2019.
[8] Ran Yi, Xiang Chen, C P Chen. Surrogate for emulating physicochemical and kinetics characteristics of RP-3 aviation fuel. Energy & fuels, 2019.
[9] Y. Wang, A. C. Meng, P. C. McIntyre and W. Cai, Phase-Field Investigation of the Stages in Radial Growth of Core-Shell Ge/Ge1-xSnx Nanowires, Nanoscale, 11, 21974-21980 (2019)
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[11] Y. Wang, P. Woytowitz, D. Mui and W. Cai, Stability of Nano-Fin Arrays Against Collapse Predicted by Phase Field Modeling, J. Vac. Sci. Technol. B, 36(5), 051602 (2018).
[12] Peipei Zhao, Lipo Wang*, Nilanjan Chakraborty, Analysis of the flame-wall interaction in premixed turbulent combustion, J. Fluid Mech. 2018(848), pp. 193_218. 2018
[13] Hua Bao*, Jie Chen*, Xiaokun Gu*, Bingyang Cao*, A Review of Simulation Methods for Micro/Nanoscale Heat Conduction, ES Energy & Environment, 1, 16-55, 2018
[14] Lipo Wang, Analysis of the filtered non-premixed turbulent flame, Combustion and Flame 175: 259-269 (2017)
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B、基于高通量计算模拟及数据挖掘的新材料设计
[1] Y. Liu, K. Weng, Y. Shen*. A Manifold Learning Approach to Accelerate Phase Field Fracture Simulations in the Representative Volume Element. SN Applied Sciences. (link)
[2] Y. Wang, T. Xie, A. France-Lanord, A. Berkley, J. A. Johnson, Y. Shao-Horn and J. C. Grossman, Toward Designing Highly Conductive Polymer Electrolytes by Machine Learning Assisted Coarse-Grained Molecular Dynamics, Chem. Mater., 32(10), 4144-4151 (2020).
[3] Xu, Z.; Zhu, H. Anion Charge and Lattice Volume Maps for Searching Lithium Superionic Conductors. Chem. Mater. 2020, 32 (11), 4618–4626.
[4] Han Wei, Hua Bao*, Xiulin Ruan*,Machine learning prediction of thermal transport in porous media with physics-based descriptors,International Journal of Heat and Mass Transfer, 160, 120176,2020
[5] Han Wei, Hua Bao*, Xiulin Ruan*,Genetic algorithm-driven discovery of unexpected thermal conductivity enhancement by disorder. Nano Energy, 71, 104619, 2020
[6] Xu, Z.; Chen, X.; Liu, K.; Chen, R.; Zeng, X.; Zhu, H. Influence of Anion Charge on Li Ion Diffusion in a New Solid-State Electrolyte, Li3LaI6. Chemistry of Materials 2019.
[7] Luo, Z.; Zhu, H.; Ying, T.; Li, D.; Zeng, X. First Principles Calculations on the Influence of Solute Elements and Chlorine Adsorption on the Anodic Corrosion Behavior of Mg (0001) Surface. Surface Science 2018, 672–673, 68–74.
[8] Han Wei, Shuaishuai Zhao, Qingyuan Rong, and Hua Bao*, Predicting the effective thermal conductivities of composite materials and porous media by machine learning methods, Int. J. Heat Mass Transfer, 127, 908-916, 2018
[9] Zhu, H.; Hautier, G.; Aydemir, U.; Gibbs, Z. M.; Li, G.; Bajaj, S.; Pöhls, J.-H.; Broberg, D.; Chen, W.; Jain, A.; White, M. A.; Asta, M.; Snyder, G. J.; Persson, K.; Ceder, G. Computational and Experimental Investigation of TmAgTe2 and XYZ2 Compounds, a New Group of Thermoelectric Materials Identified by First-Principles High-Throughput Screening. J. Mater. Chem. C 2015, 3 (40), 10554–10565.
C、Electronic design automation and digital design for computation-demanding applications
[1] Y. Wu and W. Qian, “ALFANS: Multi-level approximate logic synthesis framework by approximate node simplification,” in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 39, no. 7, pp. 1470-1483, 2020.
[2] C. Wang, W. Xiao, J. Hayes, and W. Qian, “Exploring target function approximation for stochastic circuit minimization,” in Proceedings of the 2020 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), virtual event, 2020. (acceptance rate: 27.0%)
[3] C. Meng, W. Qian, and A. Mishchenko, “ALSRAC: approximate logic synthesis by resubstitution with approximate care set,” in Proceedings of the 2020 Design Automation Conference (DAC), virtual event, 2020. (acceptance rate: 23.2%)
[4] C. Ma, Y. Sun, W. Qian, Z. Meng, R. Yang, and L. Jiang, “Go unary: a novel synapse coding and mapping scheme for reliable ReRAM-based neuromorphic computing,” in Proceedings of the 2020 Design, Automation, and Test in Europe Conference (DATE), virtual event, 2020. (acceptance rate: 25.9%)
[5] Z. Li, Z. Chen, Y. Zhang, Z. Huang, and W. Qian, “Simultaneous area and latency optimization for stochastic circuits by D flip-flop insertion,” in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 38, no. 7, pp. 1251-1264, 2019.
[6] Y. Wu, Y. Li, X. Ge, Y. Gao, and W. Qian, “An efficient method for calculating the error statistics of block-based approximate adders,” in IEEE Transactions on Computers, vol. 68, no. 1, pp. 21-38, 2019.
[7] X. Peng and W. Qian, “Stochastic circuit synthesis by cube assignment,” in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 37, no. 12, pp. 3109-3122, 2018.
[8] Z. Zhou, Y. Yao, S. Huang, S. Su, C. Men, and W. Qian, “DALS: Delay-driven approximate logic synthesis,” in Proceedings of the 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), San Diego, CA, USA, 2018, pp. 86:1-86:7. (acceptance rate: 24.7%)
[9] Su, Y. Wu, and W. Qian, “Efficient batch statistical error estimation for iterative multi-level approximate logic synthesis,” in Proceedings of the 2018 ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, 2018, pp. 54:1-54:6. (acceptance rate: 24.3%)
[10] M. Yang, J. Hayes, D. Fan, and W. Qian, “Design of accurate stochastic number generators with noisy emerging devices for stochastic computing,” in Proceedings of the 2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Irvine, CA, USA, 2017, pp. 638-644. (acceptance rate: 26.3%)
[11] Y. Wu and W. Qian, “An efficient method for multi-level approximate logic synthesis under error rate constraint”, in Proceedings of the 2016 ACM/IEEE Design Automation Conference (DAC), Austin, TX, USA, 2016, pp. 128:1-128:6. (acceptance rate: 22.6%)
[12] Z. Zhao and W. Qian, “A general design of stochastic circuit and its synthesis,” in Proceedings of the 2015 Design, Automation, and Test in Europe Conference (DATE), Grenoble, France, 2015, pp. 1467-1472. (acceptance rate: 22.4%)
[13] J. Hu and W. Qian, “A new approximate adder with low relative error and correct sign calculation,” in Proceedings of the 2015 Design, Automation, and Test in Europe Conference (DATE), Grenoble, France, 2015, pp. 1449-1454. (acceptance rate: 22.4%)
[14] W. Qian, M. D. Riedel, K. Bazargan, and D. J. Lilja, “The synthesis of combinational logic to generate probabilities,” in Proceedings of the 2009 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), San Jose, CA, USA, 2009, pp. 367-374. (acceptance rate: 26.3%)
[15] W. Qian, X. Li, M. D. Riedel, K. Bazargan, and D. J. Lilja, “An architecture for fault-tolerant computation with stochastic logic,” in IEEE Transactions on Computers, vol. 60, no. 1, pp. 93-105, 2011.
[16] W. Qian and M. D. Riedel, “The synthesis of robust polynomial arithmetic with stochastic logic,” in Proceedings of the 45th ACM/IEEE Design Automation Conference (DAC), Anaheim, CA, USA, 2008, pp. 648-653. (acceptance rate: 23.0%)