Materials Computation and Theory Group

Welcome

We are engaged in theory and modeling of materials using a spectrum of computational methods, including electronic structure, molecular dynamics, machine learning, as well as our own algorithms. Our recent work has four primary directions:

Innovation of monolayer and few layer materials (i.e. graphene, MoS₂) for structural phase change electronic memories, electromechanical properties for NEMS, and van der Waals engineering.
Machine learning to predict materials properties, including for batteries and other energy technologies.
Development of fast algorithms and data-driven computational models for complex chemistry and structural phase transitions, including pyrolysis and shock compression of energetic and other organic and inorganic materials.
Experimental collaborations to realize our predictions in the lab.

See the Impact page for some of the exciting results that we have discovered.

Group News Feed
Graduate student Evan Antoniuk successfully defends his PhD thesis!
Graduate student Gowoon Cheon successfully defends her PhD thesis!
Postdoc Rodrigo Freitas will be joining MIT’s Department of Materials Science and Engineering as Assistant Professor in January. Congratulations Prof. Freitas!
Graduate student Gowoon Cheon re-ran her screening algorithm developed in Ref. [1] to identify 1D and 2D vdW bonded solids, identifying 599 (707 with different phases of the same formula) 1D vdW solids and 1755 (2805 with different phases of the same formula) 2D vdW solids. This represents significant increases over the 487 1D and 1173 2D materials identified in the original publication. This increase is due to the increase in the number of characterized materials contained in the ICSD and Materials Project databases over the last several years. The new database is published on our group webpage in a searchable and sortable format that includes DFT computed bandgaps and point group symmetries for each material: [link here]
Editors of the journal Chemistry of Materials included our recent work examining a promising new electrolyte chemistry that was identified by machine learning models in an editorial highlighting 22 notable papers in the materials informatics field.
Graduate student Aditi Krishnapriyan successfully defends her PhD thesis!
A new Stanford Engineering feature article “A new algorithm acts like facial recognition software for materials” is out! It features our group’s work on machine learning to identify promising battery and low-dimensional materials by grad students Austin Sendek and Gowoon Cheon. Article is located here
Check out our new website for predicting Li superionic conductivity by uploading a unit cell: Electrolyte AI (electrolyte-ai.stanford.edu).
Graduate student Danny Rehn successfully defends his PhD thesis!
Graduate student Austin Sendek successfully defends his PhD thesis!
Introducing the Materials and Megabytes podcast! We're excited to launch our podcast exploring the opportunities and challenges for applying machine learning to materials science, through interviews with researchers at the forefront of this growing interdisciplinary field. Check out the available episodes here!
Qian Yang (left) and Yao Zhou (right) receive their diplomas at graduation ceremonies! Qian is now an assistant professor at University of Connecticut and Yao is now at Google.
New group photo!
Graduate student Yao Zhou successfully defends her PhD thesis! Congratulations Yao!
Our group's work on discovering new materials using statistical-learning-based methods is featured in a new article at Singularity Hub.
Graduate student Austin Sendek gives a talk at the Energy Startup Showcase, an event sponsored by Stanford's Global Climate and Energy Project (GCEP).
The Zhang group at Berkeley reports the first observation of a structural phase change in 2D MoTe₂ induced by electrostatic gating, an effect predicted by our group. This exciting experimental demonstration may lead to fundamentally new device architectures for information storage
Graduate student Qian Yang successfully defends her PhD thesis!
Group member Austin Sendek to present at the 2017 Stanford Global Climate and Energy Project (GCEP) Symposium, October 17-18 Austin received the Distinguished Student Lecturer Award for his talk on machine learning-guided design of solid Li-ion electrolytes in the GCEP Student Energy Lectures series this summer and will present his talk at the 2017 GCEP Symposium at Stanford's Frances C. Arrillaga Alumni Center from October 17-18. More details will be shared when they are available.
Prof. Reed participates in a MIT Faculty Forum online panel on graphene and other two-dimensional materials. You can watch the video on YouTube here!
Congratulations Graduates! Dr. Yao Li and Dr. Yuan Shen received their PhDs and were hooded by Evan at the Physics and Applied Physics graduation ceremony held on June 18, 2017. Congratulations Yuan and Yao! More pics here.
We identify 1173 two-dimensional layered materials and 487 materials that consist of weakly bonded one-dimensional molecular chains. Moreover, we discover 98 weakly bonded heterostructures of two-dimensional and one-dimensional subcomponents within bulk materials, opening up new possibilities for the much-studied assembly of van der Waals heterostructures. These materials were found by using a novel data-mining algorithm that we developed to screen the Materials Project database of over 50,000 inorganic crystals. Click HERE to download the complete lists.(Updated October 2019)
Clean energy scientists launch the Alt-E Fund and Professor Reed joins as a technical advisor Scientists from the University of Colorado, Boulder and the National Renewable Energy Laboratory have launched the Alt-E Fund, the world's first foundational energy research fund that seeks to change the funding landscape by harnessing the passion of millions of citizens through grassroots funding efforts. The Alt-E Fund aims to collect and disburse funds for foundational clean energy research projects around the country at universities, national labs, and other organizations. Professor Reed brings his expertise in theory and modeling of materials for energy applications to the technical advisory board.
	A defined Lifshitz model provides fast van der Waals computations for layered materials We discover that a defined Lifshitz-based model can provide van der Waals (vdW) potentials to within 8-20% of advanced electronic structure calculations (ACFDT-RPA) while being orders of magnitude faster. Using this fast model, we study the vdW binding properties of 210 three-layered heterostructures and discover the potential for repulsive three-body vdW effects.
MathWorks blogs about Sendek et al.'s recent work using machine learning to build a better battery. Join the Facebook discussion here and here!
Austin Sendek's submission to the Global Energy Forum Video Competition is selected as one of this year's winners. Congratulations, Austin! The submitted video can be viewed here. The full director's cut is available here.
Yuan Shen successfully defends his PhD thesis.
Machine learning enables large-scale screening of candidate solid-state electrolytes for lithium-ion batteries We screen 12,000 candidate materials comprising all known lithium-containing inorganic crystalline solids and provide a list of 21 promising structures.
Yao Li successfully defends her PhD thesis.
Imagine a "cool" data-storage technology that's just a few atoms thick A news article on the Stanford Engineering website about recent group work on monolayer materials.
Lenson Pellouchoud successfully defends his PhD thesis.
	Electrostatic gating drives structural phase transitions in monolayer materials Two-dimensional transition metal dichalcogenides undergo structural semiconductor-to-semimetal phase transition under electrostatic gating of several volts.
	L₁ regularization enables efficient model reduction of large-scale chemical reaction networks We use L₁ regularization to reduce a large chemical reaction network observed from molecular dynamics simulations of shock compressed liquid methane, and find that CH₄ decomposition can be modeled with less than 9% relative error using 11% of reactions.
Congratulations to Qian Yang for receiving a speaking award for her Fall MRS meeting talk.
Atomistic simulation of shock-induced silica crystallization Using the Multi-Scale Shock Technique for molecular dynamics simulation of millions of atoms, we discover that SiO₂, a prototypical good glass former, can be transformed to a very bad glass former upon the application of high pressure by the shock compression of meteor impact.
QBMSST is added to the public distribution of LAMMPS The Quantum Thermal Bath Multi-Scale Shock Technique (QBMSST) has been incorporated into the public distribution of the LAMMPS molecular dynamics code by Yuan Shen with the key word fix_qbmsst. This method enables the simulation of shock compression of materials while incorporating some aspects of quantum nuclear effects in an approximate and computationally efficient fashion. These effects can play a significant role in the shock temperatures, kinetics, and potentially the chemical composition of the system at equilibrium.
	Simulated coherent control of an isomerization reaction using THz electric field pulses Using a tri-stable molecule (LiNC) and TDDFT-based Ehrenfest dynamics, our work shows that it may be possible to drive a prescribed reaction pathway with strong THz electric fields, without excessive heating, ionization, or electronic excitation of the target system.
Karel-Alexander Duerloo successfully defends his PhD thesis.
Yao Zhou is awarded a three year Stanford Graduate Fellowship.
Experimental Observations of Piezoelectricity in Two-Dimensional MoS₂ The first experimental observations of piezoelectricity in single-layer 2D materials have been reported in two independent experiments in Nature and Nature Nanotechnology by researchers at Columbia University, Georgia Tech, UC Berkeley, Lawrence Berkeley National Laboratory, and the Chinese Academy of Sciences. Articles highlighting these experiments and our calculations have appeared in MRS Bulletin and a News and Views article in Nature Nanotechnology.
	Strain Engineering in Monolayer Materials Using Patterned Adatom Adsorption Our work shows that strains as large as 5% can be produced in monolayer materials using patterned adatom adsorption.
	Deformations drive structural phase transitions in monolayer materials. Two-dimensional transition metal dichalcogenides undergo structural metal-to-insulator phase transitions under tension.
Evan Reed gave two tutorials at the Lawrence Livermore National Laboratory Computational Chemistry and Materials Science program. These provide an introduction and summary of our recent work on "Emergent Electromechanical Properties of Nanoscale Materials," and "Atomistic Calculations of Dynamic Compression of Materials" including semiclassical quantum nuclear effects.
Graduate student Karel-Alexander Duerloo is awarded a Stanford Graduate Fellowship. Congratulations Alexander!
Electromechanical Bending in Boron Nitride Bilayers Our work reveals a unique and manifestly nanoscale curvature-electric field coupling in boron nitride bilayers.
H and F coadsorption leads to piezoelectricity in graphene. Motivated by a search for electromechanical coupling in monolayer materials, we have discovered that two types of piezoelectricity can be engineered into graphene when it is chemically modified with H and F.
Quantum corrections bring 40% lower pressure onset for methane dissociaton under shock compression. We have developed a methodology for atomistic simulations of shock compressed materials that, for the first time, incorporates semi-classical quantum nuclear effects self-consistently. In our new method, the quantum nuclear effects are achieved with almost no additional computational expense.
Piezoelectricity in Two-Dimensional Materials Our research has discovered that many of the widely studied two-dimensional monolayer crystals have excellent piezoelectric properties, making them ideally suited for applications in nanoscale technology.
Graduate student Karel-Alexander Duerloo has received the Best Instructor Award for his C programming course at the AHPCRC Summer Institute, held at Stanford.
Graduate student Lenson Pellouchoud is awarded a NASA Space Technology Research Fellowship. Congratulations Lenson!
A roadmap for engineering piezoelectricity in graphene A news article on the NERSC website about recent group work on graphene.
Engineered Piezoelectricity in Graphene Piezoelectric effects can be engineered into non-piezoelectric graphene through the selective surface adsorption of atoms. Published in ACS Nano. > ACS Nano article highlight > ACS Nano podcast: interview about article