I am broadly interested in understanding emergent phenomena in complex systems, statistical physics of soft matter (e.g., amorphous materials, liquid crystals, and self-assembled nanostructures) and in applications of statistical mechanics in solving material science problems. I am also interested in the statistical physics of machine learning algorithms.
Self-assembly of Anisotropic Particles
Systems of rod-like particles exhibit a very rich phase behavior with a variety of liquid crystalline phases and multiple phase transitions due to the interplay of orientational and translational degrees of freedom. Examples of such systems include colloids of polymethyl methacrylate, goethite, tobacco mosaic virus, fd-virus, and Silica particles. Successful synthesis of rod-like inorganic nanoparticles like CdS, CdSe, and metal nanorods have yielded various ordered superstructures with interesting device applications. Understanding their self-assembly mechanism in and out-of-equilibrium is essential in building target materials with specific functionalities. Models of rod-like particles serve as minimal models to study the self-assembly of such superstructures. However, standard simulation protocols are inefficient to establish detailed phase behavior of anisotropic particles on a substrate due to the difficulty of reaching high densities. This difficulty can be sidestepped by devising smart Monte Carlo algorithms with nonlocal moves. In the past, such an algorithm led us to discover various liquid crystalline phases in systems of hard rectangles on lattices. Currently, we are interested in investigating the role of shape anisotropy, interactions and size dispersity of the microscopic building blocks in designing self-assembled macroscopic soft materials with novel properties in and out-of-equilibrium using efficient numerical schemes and analytical calculations.
Relevant Publications:
Joyjit Kundu*, R. Rajesh, Deepak Dhar and Jürgen F. Stilck."Nematic-disordered phase transition in systems of long rigid rods on two-dimensional lattices", Phys. Rev. E, 87, 032103 (2013).
Joyjit Kundu* and R. Rajesh."Phase transitions in a system of hard rectangles on the square lattice", Phys. Rev. E, 89, 052124 (2014).
Douglas R Greer, Michael A. Stolberg, Joyjit Kundu, Rayan K. Spencer, Tod Pascal, David Prendergast, Nitash P. Balsara and Ronald N Zuckermann."Universal Relationship between Molecular Structure and Crystal Structure in Peptoid Polymers and Prevalence of the cis Backbone Conformation", J. Am. Chem. Soc. 140, 827 (2018).
Xi Jiang, Douglas R. Greer, Joyjit Kundu, Colin Ophus, Andrew M. Minor, David Prendergast, Ronald N. Zuckermann, Nitash P. Balsara and Kenneth H. Downing."Imaging Unstained Synthetic Polymer Crystals and Defects on Atomic Length Scales Using Cryogenic Electron Microscopy", Macromolecules, DOI: 10.1021/acs.macromol.8b01508.
Gas Capture by Porous Crystalline Materials
Developing technologies for gas separation and storage is crucial for clean, renewable energy and various industrial applications. Metal-organic frameworks (MOFs), a class of porous crystalline materials with largely tunable properties and huge surface area, are promising candidates in this regard. Most of the frameworks exhibit typical Langmuir-type adsorption isotherm where gas uptake varies gradually with pressure and temperature. However, it is technologically more convenient to have step-like isotherm where gas uptake varies in an abrupt way with pressure or temperature as it leads to higher working capacity. Examples of gas-framework combinations that exhibit cooperativity or step-like feature in equilibrium include CS₂, CO2 adsorption in diamine appended MOFs mmen-M2(dobpdc), CO adsorption in Fe2Cl2(bbta), CH4 adsorption in Fe(bdp). We are interested in understanding the basic mechanism that results in a step-like feature in different MOFs and how to control the step-position, and other properties of the step. For selective gas uptake in equilibrium, the framework has to bind most strongly to the desired gas-type compared to the others in the gas-mixture. This restricts the space of protocols and materials for which selective gas capture can be performed. One solution is to carry out gas uptake out-of-equilibrium which remains poorly understood. We are interested in exploring how the cooperative adsorption mechanism can be exploited to realize efficient gas separation under driven and thermodynamic conditions.
Relevant Publications:
Joyjit Kundu*, Tod Pascal, David Prendergast and Stephen Whitelam. "Selective gas capture via kinetic trapping", Phys. Chem. Chem. Phys. 18, 21760 (2016).
Joyjit Kundu*, Jürgen F. Stilck, Jung-Hoon Lee, Jefferey B. Neaton, David Prendergast and Stephen Whitelam."Cooperative Gas Adsorption without a Phase Transition in Metal-Organic Frameworks", Phys. Rev. Lett. 121, 015701 (2018).
John R. Edison, Rebecca L. Siegelman, Zdenek Preisler, Joyjit Kundu*, Jeffrey R. Long, Stephen Whitelam. "Hysteresis curves reveal the microscopic origin of cooperative CO2 adsorption in diamine-appended metal-organic frameworks", arXiv:2004.12206 (2020).
Statistical Physics of Amorphous Systems
The molecular structure of a glass resembles that of a liquid, yet the latter flows and the former is a solid. This conundrum is at the heart of the glass problem. Upon cooling, gas forming liquids exhibit a marked dynamical slowdown without any significant structural change. Despite several decades of rigorous theoretical and experimental investigation, the fundamental mechanism behind this glassy slowdown remains elusive. As a result, the central problem in glass physics remains actively debated: does the slowdown result from an underlying thermodynamic transition where the dynamics truly freezes or does it originate from purely kinetic effects without any thermodynamic singularity? One of the most compelling theories of glass transition is the Random First Order Transition (ROFT) theory that predicts the existence of an ideal glass transition with a diverging static length scale at a finite temperature. There exists another school of thought that advocates purely kinetic origin of glassy slowdown derived from certain lattice gas models with “facilitated dynamics” and disapproves the idea of a thermodynamic transition. We are interested in resolving this issue by verifying the ideal glass transition scenario in constrained glass forming liquids (e.g., liquids with pinning) using suitably optimized systems and smart numerical algorithms with improved sampling. Further, we are interested in understanding the connection between thermodynamics and dynamics to address the question of the origin of glassy slowdown.
Relevant Publication:
Ludovic Berthier, Patrick Charbonneau and Joyjit Kundu*, "Finite-dimensional vestige of spinodal criticality above the dynamical glass transition", too appear in Phys. Rev. Lett. (2020), arXiv:1912.11510
Ludovic Berthier, Patrick Charbonneau and Joyjit Kundu*, “Bypassing Sluggishness: the Swap Algorithm and Glassiness”, Physical Review E 99 (3), 031301 (R) (2019)
Patrick Charbonneau and Joyjit Kundu*, "Postponing the dynamical transition density using competing interactions", Granular Matter 22, 55 (2020)
Machine learning and Physics
We also interested in exploring how physics and machine learning can complement each other. Currently, we are trying to use machine learning to predict complex liquid crystalline phases and the related phase transitions in systems of rod-like particles. Interestingly the loss-landscape of machine learning algorithms resembles the free energy landscape of disordered systems-- usually, both have a rugged landscape with many metastable minima. We are interested in using tools developed in glass physics to understand the properties of loss-landscape of machine learning algorithms.