Siddhartha Das

In this paper, we establish a new machine learning technique to demonstrate two separate hydration states of the {N(CH3)3}+ of the PMETAC brushes. This is Raashiq’s 6th paper and Tanmay’s 4th paper from the group. Congrats to both !!!!!!

This paper probes the hydrogen bonding network inside boron nitride nanotubes (BNNTs). This is Bhargav’s 11th publication from the group.

SMIEL’s former Ph.D. student Vishal Sivasankar’s Ph.D. dissertation has been selected to receive “Honorable Mention” in the UMD’s Charles A. Caramello Distinguished Dissertation Award competition. This competition represents the competition among all the Ph.D. dissertations across all departments and this honor means that Vishal’s dissertation ranks among the best 1-2 dissertations in the entire Engineering,

This funding will help the SMIEL group to additively fabricate patch antennae using CNT-based conductive inks.

Prof. Siddhartha Das delivered an invited talk in the Department of Mechanical and Aerospace Engineering in SUNY Buffalo. The title of his talk was “Soft and Active Interfaces: Enhanced Liquid Flows in Polymer-Functionalized Nanochannels, Self-Assembly via Active Drops, and Reduced Conductivity of Printed Nanoparticle Traces”

In this paper, we employ all-atom MD simulations for studying the behavior of cationic brushes in presence of different halide counterions. This is Raashiq’s 5th paper from the group. Congratulations !!!!!

In this paper, we propose a theory for studying the evaporation of active drops. This is the first paper from the group on active drops. This is Ghansham’s 3rd paper and Vishal’s 24th paper. Congrats All !!!!

In this paper, we study the impact-driven coalescence between two dissimilar polymeric drops. This is Arka’s 2nd paper and Vishal’s 24th paper from the group.

In this paper, we fabricate soft PDMS based magnetic films and test their robustness in presence of different types of deformations. This is Swarup’s 6th paper and Beihan’s 10th paper from the group. Congrats !!!!!!

In this paper, we employ a combination of all-atom-MD-machine-learning approach to quantify water-water hydrogen bonding inside anionic polyelectrolyte brush layer with different charge fractions. This is Arka’s 1st paper, Tanmay’s 3rd paper, Raashiq’s 4th paper, Turash’s 13th paper from the group.