Papers, organized by year of completion of the preprint. Entries with only links to preprints are in various stages of submission and review with journals.

2022

• Partial differential equation-based inference of migration and proliferation mechanisms in cancer cell populations
  P.C. Kinnunen, S. Srivastava, Z. Wang, K.K.Y. Ho, B.A. Humphries, S. Chen, J.J. Linderman, G.D. Luker, K.E. Luker, K. Garikipati
  available on arXiv
  


• Bridging scales with Machine Learning: From first principles statistical mechanics to continuum phase field computations to study order disorder transitions in LixCoO2
  G.H. Teichert, S. Das, M. Faghih Shojaei, J. Holber, T. Mueller, L. Hung, V. Gavini, K. Garikipati
  available on arXiv
  


• Ferroelastic toughening: can it solve the mechanics challenges of solid electrolytes?
  A. Van der Ven, R.M. McMeeking, R.J. Clement, K. Garikipati
  Current Opinion in Solid State & Materials Science, to appear
  available on arXiv
  


• Label-free learning of elliptic partial differential equation solvers with generalizability across boundary value problems
  X. Zhang, K. Garikipati
  available on arXiv
  


• High order schemes for gradient flow with respect to a metric
  S. Han, S. Esedoglu, K. Garikipati
  available on arXiv
  


• Mechanics of stabilized intercellular bridges
  J. Singh, J. I. Alsous, K. Garikipati, S. Y. Shvartsman
  Biophysical Journal
  doi:10.1016/j.bpj.2022.06.033
  


• Oscillatory ERK Signaling and Morphology Determine Heterogeneity of Breast Cancer Cell Chemotaxis via MEK-ERK and p38-MAPK Signaling Pathways
  K.Y.H. Kenneth, S. Srivastava, P.C. Kinnunen, K. Garikipati, G.D. Luker, K.E. Luker
  Bioengineering, Special Issue on Engineering-Inspired Cancer Research
  10(2):269, 2023, doi:10.3390/bioengineering10020269
  [available on bioRxiv]
  


• Ogden Material Calibration via Magnetic Resonance Cartography, Parameter Sensitivity, and Variational System Identification
  D.P. Nikolov, S. Srivastava, B.A. Abeid, U.M. Scheven, E.M. Arruda, K. Garikipati, J.B. Estrada
  Philosophical Transactions of the Royal Society A, (Themed Issue) The Ogden model of rubber mechanics: Fifty years of impact on nonlinear elasticity
  Vol 380, Issue 2234, 2022, doi:10.1098/rsta.2021.0324
  [available on arXiv]
  


• Numerical analysis of non-local calculus on finite weighted graphs, with application to reduced-order modelling of dynamical systems
  M. Duschenes, S. Srivastava, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering, Special Issue in honor of J.T. Oden
  115513, 2022, doi:10.1016/j.cma.2022.115513
  [available on arXiv]
  

2021

• A fourth-order phase-field fracture model: Formulation and numerical solution using a continuous/discontinuous Galerkin method
  L. Svolos, H. M. Mourad, G. Manzini, K. Garikipati
  Journal of the Mechanics and Physics of Solids
  Vol 165, 104910, 2022, doi:10.1016/j.jmps.2022.104910
  [available on arXiv]
  


• Machine learning in heterogeneous porous materials
  M. D'Elia, H. Deng, C. Fraces, K. Garikipati, L. Graham-Brady, A. Howard, G. Karniadakis, V. Keshavarzzadeh, R.M. Kirby, N. Kutz, C. Li, X. Liu, H. Lu, P. Newell, D. O'Malley, M. Prodanovic, G. Srinivasan, A. Tartakovsky, D.M. Tartakovsky, H. Tchelepi, B. Vazic, H. Viswanathan, H. Yoon, P. Zarzycki
  [available on arXiv]
  


• A heteroencoder architecture for prediction of failure locations in porous metals using variational inference
  W. Bridgman*, X. Zhang*, G.H. Teichert, M. Khalil, K. Garikipati, R Jones
  Computer Methods in Applied Mechanics and Engineering
  Vol 398, 115236, 2022, doi:10.1016/j.cma.2022.115236
  [available on arXiv]
  


• mechanoChemML: A software library for machine learning in computational materials physics
  X. Zhang, G.H. Teichert, Z. Wang, M. Duschenes, S. Srivastava, E. Livingston, J. Holber, M. Faghih Shojaei, A. Sundararajan, K. Garikipati
  Computational Materials Science
  Vol 211, 111493, 2022, doi:10.1016/j.commatsci.2022.111493
  [available on arXiv]
  


• Methodology for sensitivity analysis of homogenized cross-sections to instantaneous and historical lattice conditions with application to AP1000® PWR lattice
  D. Price, T. Folk, M. Duschenes, K. Garikipati, B. Kochunas
  Energies
  Vol. 14, 3378, 2021


• Reduced order models from computed states of physical systems using non-local calculus on finite weighted graphs
  M. Duschenes, K. Garikipati
  [available on arXiv]
  


• System inference via field inversion for the spatio-temporal progression of infectious diseases: Studies of COVID-19 in Michigan and Mexico
  Z. Wang, M. Carrasco-Teja, X. Zhang, G.H. Teichert, K. Garikipati
  Arch Computat Methods Eng
  Vol 28, 4283-4295, 2021, doi:10.1007/s11831-021-09643-1
  [available on arXiv] [available on medRxiv]
  

2020

• Sensitivity of void mediated failure to geometric design features of porous metals
  G.H. Teichert, M. Khalil, C. Alleman, K. Garikipati, R.E. Jones
  International Journal of Solids and Structures
  Vol 236-237, 111309, 2022. doi:10.1016/j.ijsolstr.2021.111309
  [available on arXiv]


• Li_xCoO₂ phase stability studied by machine learning-enabled scale bridging between electronic structure, statistical mechanics and phase field theories
  G.H. Teichert, S. Das, M. Aykol, C. Gopal, V. Gavini, K. Garikipati
  [available on arXiv]


• Biomembranes undergo complex, non-axisymmetric deformations governed by Kirchhoff-Love kinematics and revealed by a three dimensional computational framework
  D. Auddya*, X. Zhang*, R. Gulati, R. Vasan, K. Garikipati, P. Rangamani, S. Rudraraju
  Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
  Vol 477, 20210246, 2021, doi:10.1098/rspa.2021.0246
  [available on arXiv] [available on bioRxiv]


• Bayesian neural networks for weak solution of PDEs with uncertainty quantification
  X. Zhang, K. Garikipati
  [available on arXiv]


• The graph theoretic approach for nodal cross section parameterization
  B. Kochunas, K. Garikipati, M. Duschenes, T. Folk
  [available on arXiv]


• CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation
  C.J. Arthurs, R. Khlebnikov, A. Melville, M. Marcan, A. Gomez, D. Dillon-Murphy, F. Cuomo, M. Silva Vieira, J. Schollenberger, S. R. Lynch, C. Tossas-Betancourt, K. Iyer, S. Hopper, E. Livingston, P. Youssefi, A. Noorani, S. Ben Ahmed, F. J. H. Nauta, T. M. J. van Bakel, Y. Ahmed, P. A. J. van Bakel, J. Mynard, P. Di Achille, H. Gharahi, K. D. Lau, V. Filonova, M. Aguirre, N. Nama, N. Xiao, S. Baek, K. Garikipati, O. Sahni, D. Nordsletten, C. A. Figueroa
  PLOS Computational Biology
  Vol 17, e1008881, 2021, doi:10.1371/journal.pcbi.1008881
  [available on bioRXiv]


• Discovery of deformation mechanisms and constitutive response of soft material surrogates of biological tissue by full-field characterization and data-driven variational system identification
  Z. Wang, J.B. Estrada, E.M. Arruda, K. Garikipati
  Journal of the Mechanics and Physics of Solids
  Vol. 153, 104474, 2021
  [available on bioRXiv]


• An inverse modelling study on the local volume changes during early growth of the fetal human brain
  Z. Wang, B. Martin, J. Johannes Weickenmeier, K. Garikipati
  Brain Multiphysics
  Vol 2, 100023, 2021. doi:10.1016/j.brain.2021.100023
  [available on bioRXiv]
  [YouTube]


• High order, semi-implicit, energy stable schemes for gradient flows
  A. Zaitzeff, S. Esedoglu, K. Garikipati
  Journal of Computational Physics
  Vol 447, 110688, 2021, doi:10.1016/j.jcp.2021.110688
  [available on arXiv]


• System inference for the spatio-temporal evolution of infectious diseases: Michigan in the time of COVID-19
  Z. Wang, X. Zhang, G.H. Teichert, M. Carrasco-Teja, K. Garikipati
  Computational Mechanics
  Vol 66, 1177, 2020. doi:10.1007/s00466-020-01894-2
  [available on arXiv]

2019

• Editorial: Special Issue on Uncertainty Quantification, Machine Learning, and Data-Driven Modeling of Biological Systems
  A.B Tepole, D. Nordsletten, K. Garikipati, E. Kuhl
  Computer Methods in Applied Mechanics and Engineering
  Vol 362, 112832, 2020, doi:10.1016/j.cma.2020.112832


• Active learning workflows and integrable deep neural networks for representing the free energy functions of alloys
  G.H. Teichert, A.R. Natarajan, A. Van der Ven, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol 371, 113281, 2020, doi:10.1016/j.cma.2020.113281
  [available on arXiv]


• A Perspective on Regression and Bayesian Approaches for System Identification of Pattern Formation Dynamics
  Z. Wang, B. Wu, K. Garikipati, X. Huan
  Theoretical and Applied Mechanics Letters
  Vol 10(3), 188-194, 2020, doi:10.1016/j.taml.2020.01.028
[available on arXiv]


• Variational system identification of the partial differential equations governing microstructure evolution in materials: Inference over sparse and spatially unrelated data
  Z. Wang, X. Huan, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol 377, 113706, 2021, doi.org/10.1016/j.cma.2021.113706
  [available on arXiv]


• Machine learning materials physics: Multi-resolution neural networks learn the free energy and nonlinear elastic response of evolving microstructures
  X. Zhang, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol 372, 113362, 2020, doi:10.1016/j.cma.2020.113362
  [available on arXiv]


• Modeling strength and failure variability due to porosity in additively manufactured metals
  M. Khalil, G.H. Teichert, C. Alleman, N.M. Heckman, R.E. Jones, K. Garikipati, B.L. Boyce
  Computer Methods in Applied Mechanics and Engineering
  To appear
  [available on arXiv]


• Multiscale modeling meets machine learning: What can we learn?
  M. Alber, A. Buganza Tepole, W. Cannon, S. De, S. Dura-Bernal, K. Garikipati, G. Karniadakis, W.W. Lytton, P. Perdikaris, L. Petzold, E. Kuhl
  Archives of Computational Methods in Engineering
  doi.org/10.1007/s11831-020-09405-5
  [available on arXiv]


• Second order threshold dynamics schemes for two phase motion by mean curvature
  A. Zaitzeff, S. Esedoglu, K. Garikipati
  Journal of Computational Physics
  Vol 410, 109404, 2020, doi.org/10.1016/j.jcp.2020.109404
  [available on arXiv]


• Integrating machine learning and multiscale modeling: perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences
  M. Alber, A.B. Tepole, W. Cannon, S. De, S. Dura-Bernal, K. Garikipati, G. Karniadakis, W.W. Lytton, P. Perdikaris, L. Petzold, E. Kuhl
  npj Digital Medicine
  Vol 2, Article number 115, 2019, doi:10.1038/s41746-019-0193-y
  [available on arXiv]


• Variational extrapolation of implicit schemes for general gradient flows
  A. Zaitzeff, S. Esedoglu, K. Garikipati
  SIAM Journal of Numerical Analysis
  To appear
  [available on arXiv]


• A mechanical model reveals that non-axisymmetric buckling lowers the energy barrier associated with membrane neck constriction
  R. Vasan, S. Rudraraju, M. Akamatsu, K. Garikipati, P. Rangamani
  Soft Matter
  doi: 10.1039/c9sm01494b
  [available on arXiv]


• The Materials Research Platform: Defining the requirements from user stories
  M. Aykol, J.S. Hummelshoj, A. Anapolsky, K. Aoyagi, M.Z. Bazant, T. Bligaard, R.D. Braatz, S. Broderick, D. Cogswell, J. Dagdelen, W. Drisdell, E. Garcia, K. Garikipati, V. Gavini, W. Gent, L. Giordano, C.P. Gomes, R. Gomez-Bombarelli, C.B. Gopal, J.M. Gregoire, J.C. Grossman, P. Herring, L. Hung, T.F. Jaramillo, L. King, H-K. Kwon, R. Maekawa, A.M. Minor, J. Montoya, T. Mueller, C. Ophus, K. Rajan, R. Ramprasad, B. Rohr, D. Schweigert, Y. Shao-Horn, Y. Suga, S.K. Suram, V. Viswanathan, J.F. Whitacre, A.P. Willard, O. Wodo, C. Wolverton, B.D. Storey
  Matter
  Available online 27 November 2019, doi.org/10.1016/j.matt.2019.10.024
  
  

2018

• A computational framework for the morpho-elastic development of molluskan shells by surface and volume growth
  S. Rudraraju, D.E. Moulton, R. Chirat, A. Goriely, K. Garikipati
  PLOS Computational Biology
  Cover page article. Vol 15(7), e1007213, 2019, doi.org/10.1371/journal.pcbi.1007213
  [available on arXiv]


• Machine learning materials physics: Integrable deep neural networks enable scale bridging by learning free energy functions
  G.H. Teichert, A.R. Natarajan, A. Van der Ven, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol 353, 201-216, 2019, doi.org/10.1016/j.cma.2019.05.019
  [available on arXiv]


• Variational system identification of the partial differential equations governing pattern-forming physics: Inference under varying fidelity and noise
  Z. Wang, X. Huan, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol 356, 44-74, 2019, doi.org/10.1016/j.cma.2019.07.007
  [available on arXiv]


• A graph theoretic framework for representation, exploration and analysis on computed states of physical systems
  R. Banerjee, K. Sagiyama, G.H. Teichert, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol 351, 501-530, 2019, doi.org/10.1016/j.cma.2019.03.053
  [available on arXiv]


• On the Voronoi implicit interface method
  A. Zaitzeff, S. Esedoglu, K. Garikipati
  To appear in SIAM Journal on Scientific Computing
  [available on arXiv]


• PRISMS: An integrated, open-source framework for accelerating predictive structural materials science
  L. K. Aagesen, J. F. Adams, J. E. Allison, W. B. Andrews, V. Araullo-Peters, T. Berman, Z. Chen, S. Daly, S. Das, S. DeWitt, S. Ganesan, K. Garikipati, V. Gavini, A. Githens, M. Hedstrom, Z. Huang, H. V. Jagadish, J. W. Jones, J. Luce, E. A. Marquis, A. Misra, D. Montiel, P. Motamarri, A. D. Murphy, A. R. Natarajan, S. Panwar, B. Puchala, L. Qi, S. Rudraraju, K. Sagiyama, E. L. S. Solomon, V. Sundararaghavan, G. Tarcea, G. H. Teichert, J. C. Thomas, K. Thornton, A. Van der Ven, Z. Wang, T. Weymouth, C. Yang
  Journal of Materials
  August 2018, doi.org/10.1007/s11837-018-3079-6


• Machine learning materials physics: Surrogate optimization and multi-fidelity algorithms predict precipitate morphology in an alternative to phase field dynamics
  G. Teichert, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol. 344: 666-693, 2019, doi.org/10.1016/j.cma.2018.10.025
  [available on arXiv]


• A diffuse interface framework for modelling the evolution of multi-cell aggregates as a soft packing problem due to growth and division of cells
  J. Jiang, S. Rudraraju, K. Garikipati
  Bulletin of Mathematical Biology
  2019, doi.org/10.1007/s11538-019-00577-1
  [available on arXiv]


• A multi-physics battery model with particle scale resolution of evolving porosity and electrolyte flow
  Z. Wang and K. Garikipati
  Journal of the Electrochemical Society
  Vol. 165: A2421-A438, 2018, doi:10.1149/2.0141811jes
  [available on arXiv]


• Machine learning materials physics: Deep neural networks trained on elastic free energy data from martensitic microstructures predict homogenized stress fields with high accuracy
  K. Sagiyama, K. Garikipati
  [available on arXiv]

2017

• A computational study of the mechanisms growth-driven folding patterns on shells, with application to the developing brain
  S.N. Verner, K. Garikipati
  Extreme Mechanics Letters
  Cover page article. Vol. 18: 58-69, January 2018, doi.org/10.1016/j.eml.2017.11.003
  [available on arXiv]


• Unconditionally stable, second-order schemes for gradient-regularized, non-convex, finite-strain elasticity modeling martensitic phase transformations
  K. Sagiyama, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol. 338: 597-617, August 2018, doi.org/10.1016/j.cma.2018.04.036
  [available on arXiv]


• A numerical study of branching and stability of solutions to three-dimensional martensitic phase transformations using gradient-regularized, non-convex, finite strain elasticity
  K. Sagiyama, S. Rudraraju, K. Garikipati
  [available on arXiv]


• Perspectives on the mathematics of biological patterning and morphogenesis
  K. Garikipati
  Journal of the Mechanics and Physics of Solids
  Vol. 99: 192-210, 2017, doi:10.1016/j.jmps.2016.11.013
  [available on arXiv]


• Intercalation driven porosity effects on the electro-chemo-thermo-mechanical response in continuum models for battery material electrodes
  Z. Wang, J. Siegel, K. Garikipati
  Journal of the Electrochemical Society
  Vol. 164: A2199-A2212, 2017, doi:10.1149/2.0081712jes
  [available on arXiv]


• A variational treatment of material configurations with application to interface motion and microstructural evolution
  G. Teichert, S. Rudraraju, K. Garikipati
  Journal of the Mechanics and Physics of Solids
  Vol. 99: 338–356, 2017, doi:10.1016/j.jmps.2016.11.008
  [available on arXiv]


• A comparison of Redlich-Kister polynomial and cubic spline representations of the chemical potential in phase field computations
  G. Teichert, H. Gunda, S. Rudraraju, A. Natarajan, B. Puchala, K. Garikipati, A. Van der Ven
  Computational Materials Science
  Vol. 128: 127-139, 2017, doi:10.1016/j.commatsci.2016.11.024
  [available on arXiv]

2016

• The spatial patterning potential of nonlinear diffusion Comment on “Phase separation driven by density-dependent movement: A novel mechanism for ecological patterns” by Quan-Xing Liu et al.
  P.K. Maini, K. Garikipati
  Physics of Life Reviews
  Vol. 19: 128-130, 2016, doi:10.1016/j.plrev.2016.10.011


• Multi-physics simulations of lithiation-induced stress in LiTiO electrode particles
  T. Jiang, S. Rudraraju, A. Roy, A. Van der Ven, K. Garikipati, M. L. Falk
  Journal of Physical Chemistry C
  Vol. 120: 27871–27881, 2016, doi:10.1021/acs.jpcc.6b09775
  [available on arXiv]


• Coordination of signaling and tissue mechanics during morphogenesis of murine intestinal villi: a role for mitotic cell rounding
  A.M. Freddo, S.K. Shoffner, Y. Shao, K. Taniguchi, A. S. Grosse, M.N. Guysinger, S. Wang, S. Rudraraju, B. Margolis, K. Garikipati, S. Schnell and D.L. Gumucio
  Integrative Biology
  Vol. 8: 918-928, 2016, doi:10.1039/C6IB00046K


• Unconditionally stable, second-order accurate schemes for solid state phase transformations driven by mechano-chemical spinodal decomposition
  K. Sagiyama, S. Rudraraju, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol. 311: 556–575, 2016, doi: 10.1016/j.cma.2016.09.003
  [available on arXiv]


• Mechano-chemical spinodal decomposition: A phenomenological theory of phase transformations in multi-component, crystalline solids
  S. Rudraraju, A. Van der Ven, K. Garikipati
  Nature npj Computational Materials
  Article number: 16012, 2016, doi:10.1038/npjcompumats.2016.12
  [available on arXiv]


• A three dimensional field formulation, and isogeometric solutions to point and line defects using Toupin's theory of gradient elasticity at finite strains
  Z. Wang, S. Rudraraju, K. Garikipati
  Journal of the Mechanics and Physics of Solids
  Vol. 94: 336-361, 2016, doi:10.1016/j.jmps.2016.03.028
  [available on arXiv]

2015

• The mechanochemistry of cytoskeletal force generation
  M. Maraldi, K. Garikipati
  Biomechanics and Modeling in Mechanobiology
  Vol 14: 59-72, 2015, doi:10.1007/s10237-014-0588-2
  [available on arXiv]

2014

• Rate dependence of swelling in lithium ion cells
  K. Y. Oh, J. B. Siegel, L. Secondo, S. U. Kim, N. A. Samad, J. W. Qin, D. Anderson, K. Garikipati, A., Knobloch, B. I. Epureanu, C. W. Monroe and A. Stefanopoulou
  Journal of Power Sources
  Vol 267: 197-202, 2014


• Elastic free energy drives the shape of prevascular tumors
  K.L. Mills, S. Rudraraju, R. Kemkemer, K. Garikipati
  PLoS ONE
  Vol 9(7):e103245, doi:10.1371/journal.pone.0103245 2014
  available on arXiv


• Three dimensional iso-geometric solutions to general boundary value problems of Toupin's theory of gradient elasticity at finite strains
  S. Rudraraju, A. Van der Ven, K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol 278: 705-728, 2014
  available on arXiv


• A computational study of stress fiber-focal adhesion dynamics governing cell contractility
  M. Maraldi, C. Valero, K. Garikipati
  Biophysical Journal
  Vol. 106: 1890-1901, 2014, doi:10.1016/j.bpj.2014.03.027
  available on arXiv

2012

• Predictions of crack propagation using a variational multiscale approach and its application to fracture in laminated fiber reinforced composites
  S. Rudraraju, A. Salvi, K. Garikipati, A.M. Waas
  Composite Structures
  Vol. 94: 3336–3346, 2012, doi: 10.1016/j.compstruct.2012.03.035


• Experimental observations and numerical simulations of curved crack propagation in laminated fiber composites
  S. Rudraraju, A. Salvi, K. Garikipati, A.M. Waas
  Composites Science and Technology
  Vol. 72: 1064-1074., 2012, doi:10.1016/j.compscitech.2011.07.020

2011

• p38Gamma Promotes breast cancer cell motility and metastasis through regulation of RhoC GTPase, cytoskeletal architecture, and a novel leading edge behavior
  D.T. Rosenthal, H. Iyer, S. Escudero, L. Bao, Z. Wu, A.C. Ventura, C.G. Kleer, E.M. Arruda, K. Garikipati, S.D. Merajver
  Cancer Research
  Vol 71: 6338-6349, 2011, doi:10.1158/0008-5472.CAN-11-1291


• Experimental characterization of tumor spheroids for studies of the energetics of tumor growth
  K.L. Mills, K. Garikipati, R. Kemkemer
  International Journal of Materials Research
  Vol. 7: 889-895., 2011, doi:10.3139/146.110532


• Perspectives on biological growth and remodeling
  D. Ambrosi, G.A. Ateshian, E.M. Arruda, S.C. Cowin, J. Dumais, A. Goriely, G.A. Holzapfel, J.D. Humphrey, R. Kemkemer, E. Kuhl, J.E. Olberding, L.A. Taber, K. Garikipati
  Journal of the Mechanics and Physics of Solids
  Vol. 59(4): 863-883., 2011, doi:10.1016/j.jmps.2010.12.011

2010

• The non-equilibrium thermodynamics and kinetics of focal adhesion dynamics
  J.E. Olberding, M.D. Thouless, E.M. Arruda, K. Garikipati
  PLoS ONE
  Vol. 5(8): e12043., 2010, DOI 10.1371/journal.pone.0012043


• In silico estimates of the free energy rates in growing tumor spheroids
  H. Narayanan, S.N. Verner, K.L. Mills, R. Kemkemer, K. Garikipati
  Journal of Physics: Condensed Matter, (Special Issue on Cell-Substrate Interactions)
  Vol. 22(19) 194122, 2010, DOI 10.1088/0953-8984/22/19/194122
  available on arXiv


• An energy basin finding algorithm for kinetic Monte Carlo acceleration
  B. Puchala, M.L. Falk, K. Garikipati
  Journal of Chemical Physics
  Vol. 132, 134104, 2010, DOI 10.1063/1.3369627


• In-plane fracture of laminated fiber reinforced composites with varying fracture resistance: Experimental observations and numerical crack propagation simulations
  S.S. Rudraraju, A. Salvi, K. Garikipati, A.M. Waas
  International Journal of Solids and Structures
  Vol. 47(7-8), 901 — 911, 2010, DOI 10.1016/j.ijsolstr.2009.12.006

2009

• The role of coherency strains on phase stability in LixFePO4: Needle crystallites minimize coherency strain and over-potential
  A. van der Ven, K. Garikipati, S. Kim, M. Wagemaker
  Journal of the Electrochemical Society
  Vol. 156(11) A949 — A957, 2009, DOI 10.1149/1.3222746


• The micromechanics of fluid-solid interactions during growth in porous soft biological tissue
  H. Narayanan, E. M. Arruda, K. Grosh, K. Garikipati
  Biomechanics and Modeling in Mechanobiology
  Vol. 8(3), pp 167 — 181, 2009, DOI 10.1007/s10237-008-0126-1
  available on arXiv


• The kinematics of biological growth
  K. Garikipati
  Applied Mechanics Review
  Vol. 62(3), Article no. 030801, 2009, DOI 10.1115/1.3090829

2008

• Elastic effects on relaxation volume tensor calculations
  B. Puchala, M. L. Falk, K. Garikipati
  Physical Review
  Vol. 77(7), Article no. 174116, 2008
  available on arXiv


• Elastica-based strain energy functions for soft biological tissue
  K. Garikipati, S. Goektepe and C. Miehe
  Journal of the Mechanics and Physics of Solids
  Vol. 56, pp 1693 – 1713, 2008 (available online since July, 2007)
  available on arXiv

2007

• On standard and vector finite element analysis of a strict anti-plane shear model with elastic curvature
  R. A. Regueiro, P. Dixit and K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol. 196, pp 2692 – 2712, 2007

2006

• The continuum elastic and atomistic viewpoints on the formation volume and strain energy of a point defect
  K. Garikipati, M. Falk, M. Bouville, B. Puchala, H. Narayanan
  Journal of the Mechanics and Physics of Solids
  Vol. 54 (9) pp. 1929 – 1951, September 2006
  available on arXiv


• Biological remodelling: Stationary energy, configurational change, internal variables and dissipation
  K. Garikipati, J. E. Olberding, H. Narayanan, E. M. Arruda, K. Grosh, S. Calve
  Journal of the Mechanics and Physics of Solids
  Vol. 54 (7) pp. 1493 – 1515, July 2006
  available on arXiv


• Advances in the numerical treatment of grain-boundary migration: Coupling with mass transport and mechanics
  H. Mourad and K. Garikipati
  Computer Methods in Applied Mechanics and Engineering
  Vol. 196 pp. 595 – 607, 2006
  available on arXiv


• A Discontinuous Galerkin method for the Cahn-Hilliard equation
  G. N. Wells, E. Kuhl and K. Garikipati
  Journal of Computational Physics
  Vol. 218 pp. 860 – 877, 2006


• A discontinuous Galerkin method for strain gradient-dependent damage: Study of interpolations and convergence
  L. Molari, G. N. Wells, K. Garikipati and F. Ubertini
  Computer Methods in Applied Mechanics and Engineering
  Vol. 195 pp. 1480 – 1498, 2006
  available on arXiv


• On the convexity of transversely-isotropic chain networks
  E. Kuhl, A. Menzel and K. Garikipati
  Philosophical Magazine
  Vol. 86 pp. 3241 – 3258, 2006


• Characterization and modeling of growth and remodeling in tendon and soft tissue constructs
  E. M. Arruda, S. Calve, K. Garikipati, K. Grosh, H. Narayanan
  Mechanics of Biological Tissue pp. 63 – 75
  Edited by G. A. Holzapfel and R. W. Ogden, Springer, 2006

2005

• Material forces in the context of biotissue remodelling
  K. Garikipati, H. Narayanan, E. M. Arruda, K. Grosh, S. Calve
  Mechanics of Material Forces
  pp. 77 – 84
  Edited by P. Steinmann and G. A. Maugin, Springer, 2005
  available on arXiv


• Remodelling of biological tissue: Mechanically-induced reorientation of a transversely isotropic chain network
  E. Kuhl, K. Garikipati, E. M. Arruda and K. Grosh
  Journal of the Mechanics and Physics of Solids
  Vol. 53, pp. 1552 – 1573, 2005
  available on arXiv

2004

• A continuum treatment of growth in biological tissue: The coupling of mass transport and mechanics
  K. Garikipati, E. M. Arruda, K. Grosh, H. Narayanan, S. Calve
  Journal of the Mechanics and Physics of Solids
  Vol. 52 (7) pp. 1595 – 1625, July 2004
  available on arXiv


• A variational multiscale method to incorporate strain gradients in a phenomenological plasticity model
  S. L. Creighton, R. A. Regueiro, K. Garikipati, P. A. Klein, E. B. Marin and D. J. Bammann
  Computer Methods in Applied Mechanics and Engineering
  Vol. 193, pp. 5453 – 5475, 2004


• A discontinuous Galerkin formulation for a strain gradient-dependent damage model
  G. N. Wells, K. Garikipati and L. Molari
  Computer Methods in Applied Mechanics and Engineering
  Vol. 193, pp. 3633 – 3645, 2004