About

Joost J. Vlassak is the Abbott and James Lawrence Professor of Materials Engineering at Harvard University, serving as the Area Chair for Materials Science & Mechanical Engineering. He is a faculty member at the Harvard John A. Paulson School of Engineering and Applied Sciences and is also a Faculty Associate at the Harvard University Center for the Environment. His primary teaching areas include Materials Science and Mechanical Engineering. Vlassak's research focuses on applied physics, materials, soft matter, solid mechanics, and surface and interface science. His work involves understanding and manipulating materials at small scales, with applications spanning climate sensing, biological energy detection at the sub-cellular level, and the development of disruptive technological solutions. He is actively involved in advancing knowledge in materials science and mechanical engineering through both research and teaching.

Research topics

• Computer Science
• Materials science
• Engineering
• Physics
• Composite material
• Nanotechnology
• Mechanical engineering
• Computer vision
• Polymer chemistry
• Polymer science
• Structural engineering
• Electronic engineering
• Embedded system
• Aerospace engineering

Selected publications

• Boosting Grid Throughput for a Sustainable Energy Future: The Role of AI and Advanced Materials

  IEEE Energy Sustainability Magazine · 2025-08-01

  article

  As Electrification and Renewable Energy adoption accelerate, the electric grid faces growing challenges in delivering clean and reliable power to meet surging demand from sectors such as transportation, industry, and artificial intelligence (AI)-driven computing. However, expanding grid infrastructure remains constrained by regulatory, environmental, and economic barriers. This article explores how AI, advanced conductor materials, energy-aware computing, and energy storage can effectively enhance transmission capacity without new construction. AI enables real-time grid optimization and stability management, while advanced materials like composite-core conductors reduce losses and increase throughput. Additionally, energy-flexible computing dynamically aligns computational workloads with grid conditions, alleviating peak demand. The future integration of energy storage as a transmission asset offers new pathways for congestion management. Together, these innovations form a scalable blueprint for an efficient and sustainable power system that supports sustainable electrification goals.

  PublisherDOI

• Plastic-elastomer heterostructure for robust flexible brain-computer interfaces

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-04 · 2 citations

  preprintOpen access

  Electronics for neural signal recording must be robust across multiple and deep brain regions while preserving tissue-level flexibility to ensure stable tracking over months or years. However, existing electronics cannot simultaneously achieve robustness and tissue-level flexibility, limiting their potential for customizable and scalable neuroscience research and clinical applications. Here, we introduce FlexiSoft, an electronic platform based on a plastic-elastomer heterostructure that uniquely integrates mechanical robustness and tissue-level flexibility. Compared to conventional flexible electronics of similar thickness, the FlexiSoft platform demonstrates an order-of- magnitude improvement in both mechanical robustness (critical energy release rate) and flexibility (flexural rigidity). Leveraging these mechanical advantages, we developed FlexiSoft probe for robust implantation, demonstrated by its ability to withstand repeated insertion and removal, as well as to reach centimeter-scale depths comparable to those in the human brain. The platform enables long-term recording from the same neurons across the hippocampus (HPC) and primary motor cortex (M1) during a months-long motor learning task, thereby revealing long-term dynamic changes in neuronal firing patterns. Additionally, FlexiSoft's unique robustness and flexibility enable curved implantation routes, opening new directions of customizable implantation pathways. In summary, we present FlexiSoft as a novel, robust, and tissue-level flexible heterostructure electronics platform that advances flexible brain-computer interfaces (BCIs) with strong translational potential for neuroscience and clinical applications.

  PublisherOA PDFDOI

• Photophoretic flight of perforated structures in near-space conditions

  Nature · 2025-08-13 · 5 citations

  article
  PublisherDOI

• Biomimetic hierarchical fibrous hydrogels with high alignment and flaw insensitivity

  Matter · 2025-03-17 · 10 citations

  articleSenior author
  PublisherDOI

• A machine learning perspective on the inverse indentation problem: uniqueness, surrogate modeling, and learning elasto-plastic properties from pile-up

  Journal of the Mechanics and Physics of Solids · 2024-01-26 · 38 citations

  articleOpen accessSenior authorCorresponding
  PublisherOA PDFDOI

• Barocaloric Effects in Dialkylammonium Halide Salts

  Journal of the American Chemical Society · 2024-01-16 · 23 citations

  articleCorresponding

  Barocaloric effects─solid-state thermal changes induced by the application and removal of hydrostatic pressure─offer the potential for energy-efficient heating and cooling without relying on volatile refrigerants. Here, we report that dialkylammonium halides─organic salts featuring bilayers of alkyl chains templated through hydrogen bonds to halide anions─display large, reversible, and tunable barocaloric effects near ambient temperature. The conformational flexibility and soft nature of the weakly confined hydrocarbons give rise to order–disorder phase transitions in the solid state that are associated with substantial entropy changes (>200 J kg–1 K–1) and high sensitivity to pressure (>24 K kbar–1), the combination of which drives strong barocaloric effects at relatively low pressures. Through high-pressure calorimetry, X-ray diffraction, and Raman spectroscopy, we investigate the structural factors that influence pressure-induced phase transitions of select dialkylammonium halides and evaluate the magnitude and reversibility of their barocaloric effects. Furthermore, we characterize the cyclability of thin-film samples under aggressive conditions (heating rate of 3500 K s–1 and over 11,000 cycles) using nanocalorimetry. Taken together, these results establish dialkylammonium halides as a promising class of pressure-responsive thermal materials.

  PublisherDOI

• Phase discovery with active learning: Application to structural phase transitions in equiatomic NiTi

  arXiv (Cornell University) · 2024-01-10 · 1 citations

  preprintOpen access

  Nickel titanium (NiTi) is a protypical shape-memory alloy used in a range of biomedical and engineering devices, but direct molecular dynamics simulations of the martensitic B19' -> B2 phase transition driving its shape-memory behavior are rare and have relied on classical force fields with limited accuracy. Here, we train four machine-learned force fields for equiatomic NiTi based on the LDA, PBE, PBEsol, and SCAN DFT functionals. The models are trained on the fly during NPT molecular dynamics, with DFT calculations and model updates performed automatically whenever the uncertainty of a local energy prediction exceeds a chosen threshold. The models achieve accuracies of 1-2 meV/atom during training and are shown to closely track DFT predictions of B2 and B19' elastic constants and phonon frequencies. Surprisingly, in large-scale molecular dynamics simulations, only the SCAN model predicts a reversible B19' -> B2 phase transition, with the LDA, PBE, and PBEsol models predicting a reversible transition to a previously uncharacterized low-volume phase, which we hypothesize to be a new stable high-pressure phase. We examine the structure of the new phase and estimate its stability on the temperature-pressure phase diagram. This work establishes an automated active learning protocol for studying displacive transformations, reveals important differences between DFT functionals that can only be detected in large-scale simulations, provides an accurate force field for NiTi, and identifies a new phase.

  PublisherOA PDFDOI

• CCDC 2171720: Experimental Crystal Structure Determination

  The Cambridge Structural Database · 2024-01-20

  datasetOpen access

  An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

  PublisherDOI

• Cracking in semiconductor devices–effect of plasticity under triaxial constraint

  Journal of the Mechanics and Physics of Solids · 2024-09-08

  article
  PublisherDOI

• Initiation and arrest of cracks from corners in multi-chip semiconductor devices

  Journal of the Mechanics and Physics of Solids · 2024-06-27 · 7 citations

  article
  PublisherDOI

Recent grants

• Stretchable, Tough, Water-Retaining Hydrogels for Non-Traditional Applications

  NSF · $400k · 2014–2017

• Rational development of next-generation shape memory alloys

  NSF · $433k · 2018–2021

• Stress and Deformation caused by Insertion in Li Ion Batteries

  NSF · $371k · 2010–2013

• The mechanical behavior of hybrid organic/inorganic structures for flexible electronics

  NSF · $280k · 2006–2009

• An Experimental Study of the Work Hardening Behavior of Metallic Thin Films

  NSF · $315k · 2009–2012

Frequent coauthors

• Zhigang Suo

  Harvard University

  50 shared

• Kechao Xiao

  Harvard University

  29 shared

• Ehrenfried Zschech

  27 shared

• Patrick J. McCluskey

  General Electric (United States)

  26 shared

• Kong‐Boon Yeap

  26 shared

• John M. Gregoire

  California Institute of Technology

  25 shared

• Han Li

  State Administration of Work Safety

  24 shared

• Dongwoo Lee

  22 shared

Labs

• Vlassak Small-Scale Mechanics LabPI