Under Review and Year 2024:

[70] Y. Lu, Z. Li, J. Song and G.-H. Hu. A single-particle energy-conserving dissipative particle dynamics approach for simulating thermophoresis of nanoparticles in polymer networks. The Journal of Chemical Physics, 2024, 161: 184101. [Link]

[69] M. Lu, C. Lin, M. Maxey, G. Karniadakis and Z. Li. Bridging scales in multiscale bubble growth dynamics with correlated fluctuations using neural operator learning. International Journal of Multiphase Flow, 2024, 180: 104959. [Link]

[68] Z. Diermyer, Y. Xia, A. Hamed, J. Klinger, V. Thompson, Z. Li and J. Li. Mesoscopic flow simulation to understand the percolation through fine-ground electronic waste particle bed. Powder Technology, 2024 (under review)

[67] P. Kunwar, A. Poudel, U. Aryal, R. Xie, Z. J. Geffert, H. Wittmann, T. H. Chiang, M. M. Maye, Z. Li and P. Soman. Multi-material Gradient Printing Using Meniscus-enabled Projection Stereolithography (MAPS). Advanced Materials Technologies, 2024: 2400675. [Open Access]

[66] M. Lu, Y. Xia, T. Bhattacharjee, J. Klinger and Z. Li. Predicting biomass comminution: Physical experiment, population balance model, and deep learning. Powder Technology, 2024, 441: 119830. [Open Access]

[65] P. Kunwar, U. Aryal, A. Poudel, D. Fougnier, Z. Geffert, R. Xie, Z. Li and P. Soman. Droplet bioprinting of acellular and cell-laden structures at high-resolutions. Biofabrication, 2024, 6: 035019. [Open Access]

[64] E. Kiyani, M. Kooshkbaghi, K. Shukla, R. Koneru, Z. Li, L. Bravo, A. Ghoshal, G. Karniadakis and M. Karttunen. Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs. Journal of Fluid Mechanics, 2024, 985: A7 [Open Access]

Year 2023:

[63] S. Sheikh, B. Lonetti, I. Touche, A. Mohammadi, Z. Li and M. Abbas. Brownian motion of soft particles near a fluctuating lipid bilayer. The Journal of Chemical Physics, 2023, 159: 244903. [DOI: 10.1063/5.0182499]

[62] Z. Li, G. Hu, Z. Wang and G.E. Karniadakis. Preface: machine-learning approaches for computational mechanics. Applied Mathematics and Mechanics, 2023, 44(7): 1035–1038. (Guest Editor of the AMM Special Issue) [Link]
Based on the Clarivate Journal Citation Reports 2022, AMM is ranked 5th out of 267 Applied Mathematics journals (Q1), and ranked 26th out of 137 Mechanics journals (Q1), with a journal impact factor of 4.4.

[61] X. Cai, Z. Li and X. Bian. Arbitrary slip length for fluid-solid interface of arbitrary geometry in smoothed particle dynamics. Journal of Computational Physics, 2023, 494: 112509. [DOI: 10.1016/j.jcp.2023.112509]

[60] M. Lu, A. Mohammadi, Z. Meng, X. Meng, G. Li and Z. Li. Deep neural operator for learning transient response of interpenetrating-phase composites subject to dynamic loading. Computational Mechanics, 2023, 72: 563–576. [Link]

[59] K.C. Chan, Z. Li and W. Wenzel. A Mori-Zwanzig dissipative particle dynamics approach for anisotropic coarse grained molecular dynamics. Journal of Chemical Theory and Computation, 2023, 19(3): 910–923. [Link]

Year 2022:

[58] R. Koneru, A. Flatau, Z. Li, L. Bravo, M. Murugan, A. Ghoshal and G. Karniadakis. Quantifying the dynamic spreading of a molten sand droplet using multiphase mesoscopic simulations. Physical Review Fluids, 2022, 7: 103602. [Link]

[57] Y. Xia, Q. Rao, A. Hamed, J. Kane, V. Semeykina, I. Zharov, M. Deo and Z. Li. Flow reduction in pore networks of packed silica nanoparticles: Insights from mesoscopic fluid models. Langmuir, 2022, 38(26): 8135–8152. [Link]

[56] M. Deng, F. Tushar, L. Bravo, A. Ghoshal, G. Karniadakis and Z. Li. Theory and simulation of electrokinetic fluctuations in electrolyte solutions at the mesoscale. Journal of Fluid Mechanics, 2022, 942: A29. [Link][Open Access]

[55] K. Zhang, J. Li, W, Fang, C. Lin, J. Zhao, Z. Li, Y. Liu, S. Chen, C. Lv and X.-Q. Feng. An energy-conservative many-body dissipative particle dynamics model for thermocapillary drop motion. Physics of Fluids, 2022, 34: 052011. [Link]

[54] H. Li, Y. Deng, Z. Li, A. Gallastegi, C. Mantzoros, G. Frydman and G. Karniadakis. Multiphysics and multiscale modeling of microthrombosis in COVID-19. PLOS Computational Biology, 2022, 18(3): e1009892. [Link]

[53] S. Ma, S. Wang, X. Qi, K. Han, X. Jin, Z. Li*, G. Hu and X. Li. Multiscale computational framework for predicting viscoelasticity of red blood cells in aging and mechanical fatigue. Computer Methods in Applied Mechanics and Engineering, 2022, 391: 114535. [Link][50 Days’ Free Access]

[52] H. Li, Y. Deng, K. Sampani, S. Cai, Z. Li, J.K. Sun and G. Karniadakis. Computational investigation of blood cell transport in retinal microaneurysms. PLOS Computational Biology, 2022, 18(1): e1009728. [Link][Journal Cover Article]

Year 2021:

[51] C. Lin, M. Maxey, Z. Li and G. Karniadakis. A seamless multiscale operator neural network for inferring bubble dynamics. Journal of Fluid Mechanics, 2021, 929: A18. [Link]

[50] Q. Rao, Y. Xia, J. Li, M. Deo and Z. Li*. Flow reduction of hydrocarbon liquid in silica nanochannel: Insight from many-body dissipative particle dynamics simulations. Journal of Molecular Liquids, 2021, 344: 117673. [Link] [50 Days’ Free Access]

[49] A. Blumers, M. Yin, H. Nakajima, Y. Hasegawa, Z. Li and G. Karniadakis. Multiscale parareal algorithm for long-time mesoscopic simulations of microvascular blood flow in zebrafish. Computational Mechanics, 2021, 68: 1131-1152. [Link]

[48] C. Lin, Z. Li, L. Lu, S. Cai, M. Maxey and G. Karniadakis. Operator learning for predicting multiscale bubble growth dynamics. The Journal of Chemical Physics, 2021, 154: 104118. [Link]

[47] A. Yazdani, Y. Deng, H. Li, E. Javadi, Z. Li*, S. Jamali, C. Lin, J. Humphrey, C. Mantzoros and G. Karniadakis. Integrating blood cell mechanics, platelet adhesive dynamics and coagulation cascade for modeling thrombus formation in normal and diabetic blood. Journal of the Royal Society Interface, 2021, 18: 20200834. [Link]

[46] Q. Rao, Y. Xia, J. Li, J. McConnell, J. Sutherland and Z. Li*. A modified many-body dissipative particle dynamics model for mesoscopic fluid simulation: methodology, calibration, and application for hydrocarbon and water. Molecular Simulation, 2021, 47(4): 363-375. [Link]

[45] L. Zhao, Z. Li*, Z. Wang, B. Caswell, J. Ouyang and G. Karniadakis. Active-and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows. Journal of Computational Physics, 2021, 427: 110069. [Link]

Year 2020:

[44] X. Meng, Z. Li*, D. Zhang and G. Karniadakis. PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs. Computer Methods in Applied Mechanics and Engineering, 2020, 370: 113250. [Link]

[43] Y. Wang, Z. Li*, J. Ouyang and G. Karniadakis. Controlled release of entrapped nanoparticles from thermoresponsive hydrogels with tunable network characteristics. Soft Matter, 2020, 16: 4756-4766. (Featured as Back Cover Article of Soft Matter) [Link]

[42] Y. Xia, A. Blumers, Z. Li*, L. Luo, Y.H. Tang, J. Kane, J. Goral, H. Huang, M. Deo and M. Andrew. A GPU-accelerated package for simulation of flow in nanoporous source rocks with many-body dissipative particle dynamics. Computer Physics Communications, 2020, 247: 106874. [Link]
— This work won the Best Research Poster Award of SC19 (SuperComputing 2019).

Year 2019:

[41] S. Wang, Z. Li and W. Pan. Implicit-solvent coarse-grained modeling for polymer solutions via Mori-Zwanzig formalism. Soft Matter, 2019, 15: 7567-7582. (Featured as Back Cover Article of Soft Matter) [Link]

[40] A. Hemeda, S. Pal, A. Mishra, M. Torabi, M. Ahmadlouydarab, Z. Li, J. Palko and Y. Ma. Effect of wetting and dewetting on the dynamics of atomic force microscopy measurements. Langmuir, 2019, 35(41): 13301-13310. [Link]

[39] L. Lu, Z. Li*, H. Li, P. Vekilov and G.E. Karniadakis. Quantitative prediction of erythrocyte sickling for the development of advanced sickle cell therapies. Science Advances, 2019, 5(8): eaax3905. [Link]

[38] A.L. Blumers, Z. Li* and G.E. Karniadakis. Supervised parallel-in-time algorithm for long-time Lagrangian simulations of stochastic dynamics: Application to hydrodynamics. Journal of Computational Physics, 2019, 393: 214-228. [Link]

[37] K. Zhang, Z. Li* and S. Chen. Analytical prediction of electrowetting-induced jumping motion for droplets on hydrophobic substrates. Physics of Fluids, 2019, 31: 081703. [Link]

[36] Z. Mao, Z. Li* and G.E. Karniadakis. Nonlocal flocking dynamics: Learning the fractional order of PDEs from particle simulations. Communication on Applied Mathematics and Computation, 2019, 1(4): 597-619 (Invited Paper for Special Issue). [Link]

[35] K. Zhang, Z. Li*, M. Maxey, S. Chen and G.E. Karniadakis. Self-cleaning of hydrophobic rough surfaces by coalescence-induced wetting transition. Langmuir, 2019, 35(6): 2431–2442. (Featured as Cover Article of Langmuir) [Link]

[34] Y. Wang, Z. Li*, J. Xu, C. Yang and G.E. Karniadakis. Concurrent coupling of atomistic simulation and mesoscopic hydrodynamics for flows over soft multi-functional surfaces. Soft Matter, 2019, 15(8): 1747-1757. (Featured as Back Cover Article of Soft Matter) [Link]

[33] B. Drawert, B. Jacob, Z. Li, T.-M. Yi and L. Petzold. Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method. Data in Brief, 2019, 22: 11-15. [Link]

[32] B. Drawert, B. Jacob, Z. Li, T.-M. Yi and L. Petzold. A hybrid smoothed dissipative particle dynamics spatial stochastic simulation algorithm for advection-diffusion-reaction problems. Journal of Computational Physics, 2019, 378: 1-17. [Link]

Year 2018 and Before:

[31] K. Kim, M.H. Han, C. Kim, Z. Li, G.E. Karniadakis and E.K. Lee. Nature of intrinsic uncertainties in equilibrium molecular dynamics estimation of shear viscosity for simple and complex fluids. The Journal of Chemical Physics, 2018, 149: 044510. [Link]

[30] L. Zhao, Z. Li*, J. Ouyang, B. Caswell and G.E. Karniadakis. Active learning of constitutive relation from mesoscopic simulations for continuum modeling of non-Newtonian fluids. Journal of Computational Physics, 2018, 363: 116-127. [Link]

[29] Z. Li, X. Bian, Y.H. Tang and G.E. Karniadakis. A dissipative particle dynamics method for arbitrarily complex geometries. Journal of Computational Physics, 2018, 355: 534-547. [Link]

[28] Z. Li, G. Hu and G.E. Karniadakis. Preface: theory, methods, and applications of mesoscopic modeling. Applied Mathematics and Mechanics, 2018, 39(1): 1-2. (Organizer of Special Issue) [Link]

[27] X. Bian, Z. Li and N.A. Adams. A note on hydrodynamics from dissipative particle dynamics. Applied Mathematics and Mechanics, 2018, 39(1): 63-82. (Invited Paper for Special Issue) [Link]

[26] Y. Yoshimoto, Z. Li, L. Kinefuchi and G.E. Karniadakis. Construction of non-Markovian coarse-grained models employing the Mori-Zwanzig formalism and iterative Boltzmann inversion. The Journal of Chemical Physics, 2017, 147: 244110. (Selected as Editor’s Pick featured article) [Link]

[25] A.L. Blumers, Y.H. Tang, Z. Li*, X.J. Li and G.E. Karniadakis. GPU-accelerated red blood cells simulations with transport dissipative particle dynamics. Computer Physics Communications, 2017, 217: 171-179. [Link]

[24] Z. Li, C.J. Lan, L.B. Jia and Y.B. Ma. Ground effects on separated laminar flows past an inclined flat plate. Theoretical and Computational Fluid Dynamics, 2017, 31(2): 127-136. [Link]

[23] Z. Li, H.S. Lee, E. Darve and G.E. Karniadakis. Computing the non-Markovian coarse-grained interactions derived from the Mori–Zwanzig formalism in molecular systems: Application to polymer melts. The Journal of Chemical Physics, 2017, 146(1): 014104. [Link]

[22] H. Lei, X. Yang, Z. Li and G.E. Karniadakis. Systematic parameter inference in stochastic mesoscopic modeling. Journal of Computational Physics, 2017, 330: 571-593. [Link]

[21] M.G. Deng, Z. Li*, O. Borodin and G.E. Karniadakis. cDPD: A new dissipative particle dynamics method for modeling electrokinetic phenomena at the mesoscale. The Journal of Chemical Physics, 2016, 145(14): 144109. [Link]

[20] Z. Li, X. Bian, X. Yang and G.E. Karniadakis. A comparative study of coarse-graining methods for polymeric fluids: Mori-Zwanzig vs. iterative Boltzmann inversion vs. stochastic parametric optimization. The Journal of Chemical Physics, 2016, 145(4): 044102. [Link]

[19] Y.H. Tang, Z. Li, X.J. Li, M.G. Deng and G.E. Karniadakis. Non-equilibrium dynamics of vesicles and micelles by self-assembly of block copolymers with double thermoresponsivity. Macromolecules, 2016, 49(7): 2895-2903. [Link]

[18] Z. Li, X. Bian, X.T. Li and G.E. Karniadakis. Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism. The Journal of Chemical Physics, 2015, 143(24): 243128. [Link]

[17] X. Bian, Z. Li, M. Deng and G.E. Karniadakis. Fluctuating hydrodynamics in periodic domains and heterogeneous adjacent multidomains: Thermal equilibrium. Physical Review E, 2015, 92(5): 053302. [Link]

[16] C.J. Lan, S. Pal, Z. Li and Y.B. Ma. Numerical Simulations of Digital Microfluidic Manipulation of Single Microparticles. Langmuir, 2015, 31 (35): 9636–9645. [Link]

[15] Z. Li, A. Yazdani, A. Tartakovsky and G.E. Karniadakis. Transport dissipative particle dynamics model for mesoscopic advection-diffusion-reaction problems. The Journal of Chemical Physics, 2015, 143: 014101. [Link]

[14] X. Bian, Z. Li and G.E. Karniadakis. Multi-resolution flow simulations by smoothed particle hydrodynamics via domain decomposition. Journal of Computational Physics, 2015, 297: 132-155. [Link]

[13] Z. Li, Y.H. Tang , X.J. Li and G.E. Karniadakis. Mesoscale modeling of phase transition dynamics of thermoresponsive polymers. Chemical Communications, 2015, 51: 11038-11040. [Link]

[12] Y.H. Tang, S. Kudo, X. Bian, Z. Li and G.E. Karniadakis. Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers.. Journal of Computational Physics, 2015, 297: 13-31. [Link]

[11] S. Pal, C.J. Lan, Z. Li, E.D. Hirleman and Y.B. Ma. Symmetry boundary condition in dissipative particle dynamics. Journal of Computational Physics, 2015, 292: 287-299. [Link]

[10] Z. Li, X. Bian, B. Caswell and G.E. Karniadakis. Construction of dissipative particle dynamics models for complex fluids via the Mori-Zwanzig formulation. Soft Matter, 2014,10: 8659-8672. [Link]

[9] Z. Li, Y.H. Tang, H. Lei, B. Caswell and G.E. Karniadakis. Energy-conserving dissipative particle dynamics with temperature-dependent properties. Journal of Computational Physics, 2014, 265: 113-127. [Link]

[8] Z. Li, G.H. Hu, Z.L. Wang, Y.B. Ma and Z.W. Zhou. Three dimensional flow structures in a moving droplet on substrate: a dissipative particle dynamics study. Physics of Fluids, 2013, 25: 072103. [Link]

[7] C. Lan, L. Jia, Z. Li and Y.B. Ma. Wall effect on separated flow around an inclined flat plate at high incidence. Proceedings of the ASME 2013 International Mechanical Engineering Congress and Exposition. 2013, IMECE2013-65261. [Link]

[6] Z. Li, G.H. Hu and Z.W Zhou. Dissipative particle dynamics simulation of droplet oscillations in AC electrowetting. Journal of Adhesion Science and Technology. 2012, 26: 1883-1895. [Link]

[5] Z. Li, C.J. Lan and Y.B. Ma. Effects on dust emission from an inclined flat solar panel. Proceedings of the ASME 2012 International Mechanical Engineering Congress and Exposition. 2012, 6: 619-624. [Link]

[4] C.J. Lan, Z. Li and Y.B. Ma. Numerical study of sand deposition and control by flat solar panels. Proceedings of the ASME 2012 International Mechanical Engineering Congress and Exposition. 2012, 6: 643-649. [Link]

[3] Z. Li, G.H. Hu, J.J. Zhou and Z.W Zhou. Effects of elasticity of substrate on dewetting process of evaporable ultra-thin liquid film. Chinese Journal of Theoretical and Applied Mechanics. (in Chinese) 2011, 43 (4): 699-706. [Link] [PDF]

[2] Z. Li, G.H. Hu and Z.W Zhou. A numerical method to impose slip boundary conditions in Dissipative Particle Dynamics. Journal of Shanghai University. (in Chinese) 2009, 15 (6): 628-633. [Link] [PDF]

[1] Z. Li, G.H. Hu and Z.W Zhou. Floquet instability of a large density ratio liquid-gas coaxial jet with periodic fluctuation. Applied Mathematics and Mechanics (English Edition). 2008, 29(8):975-984. [Link] [PDF]

Book/Chapters:

[4] Z. Li, W. Pan and A.M. Tartakovsky. Particle-based methods for mesoscopic transport processes. In book: Handbook of Materials Modeling, Editor: W. Andreoni and S. Yip. Publisher: Springer, Cham, 2020. [Link] [PDF]

[3] Z. Li, X. Bian, X.J. Li, M.G. Deng, Y.H. Tang, B. Caswell and G.E. Karniadakis. Dissipative Particle Dynamics: Foundation, Implementation and Applications. In book: Particles in Flows, Editor: T. Bodnár, G.P. Galdi and Š. Nečasová. Publisher: Birkhäuser, Cham, 2017. [Link] [PDF]

[2] X.J. Li, Z. Li, X. Bian, M.G. Deng, C. Kim, Y.H. Tang, A. Yazdani and G.E. Karniadakis. Dissipative Particle Dynamics, Overview. In book: Encyclopedia of Nanotechnology, Editor: B.Bhushan, Publisher: Springer, 2016. [Link] [PDF]

[1] Z. Li, G.H. Hu and Z.W Zhou. Dissipative Particle Dynamics for Complex Fluid. Mechanics and Engineering, SJTU Press (in Chinese), 2009, 385-397.