113 citations · 268 across the 13 of their papers we have counts for
13 papers
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 +5
LixTMO2 (TM=Ni, Co, Mn) forms an important family of cathode materials for Li-ion batteries, whose performance is strongly governed by Li composition-dependent crystal structure an…
mechanoChemML: A software library for machine learning in computational materials physics
X. Zhang, G. H. Teichert, Z. Wang +7
We present mechanoChemML, a machine learning software library for computational materials physics. mechanoChemML is designed to function as an interface between platforms that are…
Sensitivity of void mediated failure to geometric design features of porous metals
Gregory H. Teichert, Mohammad Khalil, Coleman Alleman +2
Material produced by current metal additive manufacturing processes is susceptible to variable performance due to imprecise control of internal porosity, surface roughness, and con…
System inference via field inversion for the spatio-temporal progression of infectious diseases: Studies of COVID-19 in Michigan and Mexico
Zhenlin Wang, Mariana Carrasco Teja, Xiaoxuan Zhang +2
We present an approach to studying and predicting the spatio-temporal progression of infectious diseases. We treat the problem by adopting a partial differential equation (PDE) ver…
LiCoO phase stability studied by machine learning-enabled scale bridging between electronic structure, statistical mechanics and phase field theories
Gregory H. Teichert, Sambit Das, Muratahan Aykol +3
LiO (TM={Ni, Co, Mn}) are promising cathodes for Li-ion batteries, whose electrochemical cycling performance is strongly governed by crystal structure and phase stability…
System inference for the spatio-temporal evolution of infectious diseases: Michigan in the time of COVID-19
Zhenlin Wang, Xiaoxuan Zhang, Gregory Teichert +2
We extend the classical SIR model of infectious disease spread to account for time dependence in the parameters, which also include diffusivities. The temporal dependence accounts…
Scale bridging materials physics: Active learning workflows and integrable deep neural networks for free energy function representations in alloys
Gregory Teichert, Anirudh Natarajan, Anton Van der Ven +1
The free energy plays a fundamental role in descriptions of many systems in continuum physics. Notably, in multiphysics applications, it encodes thermodynamic coupling between diff…
Modeling strength and failure variability due to porosity in additively manufactured metals
M. Khalil, G. H. Teichert, C. Alleman +4
To model and quantify the variability in plasticity and failure of additively manufactured metals due to imperfections in their microstructure, we have developed uncertainty quanti…
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 +1
The free energy of a system is central to many material models. Although free energy data is not generally found directly, its derivatives can be observed or calculated. In this wo…
A graph theoretic framework for representation, exploration and analysis on computed states of physical systems
R. Banerjee, K. Sagiyama, G. H. Teichert +1
A graph theoretic perspective is taken for a range of phenomena in continuum physics in order to develop representations for analysis of large scale, high-fidelity solutions to the…
Machine learning materials physics: Surrogate optimization and multi-fidelity algorithms predict precipitate morphology in an alternative to phase field dynamics
Gregory Teichert, Krishna Garikipati
Machine learning has been effective at detecting patterns and predicting the response of systems that behave free of natural laws. Examples include learning crowd dynamics, recomme…
A comparison of Redlich-Kister polynomial and cubic spline representations of the chemical potential in phase field computations
Gregory H. Teichert, N. S. Harsha Gunda, Shiva Rudraraju +4
Free energies play a central role in many descriptions of equilibrium and non-equilibrium properties of solids. Continuum partial differential equations (PDEs) of atomic transport,…
A variational treatment of material configurations with application to interface motion and microstructural evolution
Gregory H. Teichert, Shiva Rudraraju, Krishna Garikipati
We present a unified variational treatment of evolving configurations in crystalline solids with microstructure. The crux of our treatment lies in the introduction of a vector conf…