88 citations · 296 across the 17 of their papers we have counts for
17 papers
Liquid structure adjacent to solid surfaces follows the superposition principle
Qian Ai, Haiyi Wu, Lalith Krishna Samanth Bonagiri +7
Liquid structure at solid-liquid interfaces is critical for many natural and engineered processes ranging from biological signal transduction to electrochemical energy conversion.…
Invariant ionic conductance in an atomically thin polar nanopore
Shengping Zhang, Haiou Zeng, Ningran Wu +11
Ion channels regulate many essential properties of biological cells, especially the membrane potential. Despite decades of efforts on artificial channels, it remains a great challe…
Generative Quasi-Continuum Modeling of Confined Fluids at the Nanoscale
Bugra Yalcin, Ishan Nadkarni, Jinu Jeong +2
We present a data-efficient, multiscale framework for predicting the density profiles of confined fluids at the nanoscale. While accurate density estimates require prohibitively lo…
Towards Quantitative Interpretation of 3D Atomic Force Microscopy at Solid-Liquid Interfaces
Qian Ai, Lalith Krishna Samanth Bonagiri, Amir Farokh Payam +2
Three-dimensional atomic force microscopy (3D-AFM) has been a powerful tool to probe the atomic-scale structure of solid-liquid interfaces. As a nanoprobe moves along the 3D volume…
Integrating Experiment with Theory to Determine the Structure of Electrode-Electrolyte Interfaces
Lalith Krishna Samanth Bonagiri, Amir Farokh Payam, Narayana R. Aluru +1
Electrode-electrolyte interfaces are crucial for electrochemical energy conversion and storage. At these interfaces, the liquid electrolytes form electrical double layers (EDLs). H…
Water Isotope Separation using Deep Learning and a Catalytically Active Ultrathin Membrane
Jinu Jeong, Chenxing Liang, Narayana Aluru
Water isotope separation, specifically separating heavy from light water, is a socially significant issue due to the usage of heavy water in applications such as nuclear magnetic r…
Tuning Interfacial Water Friction through Moiré Twist
Chenxing Liang, Narayana R Aluru
Nanofluidics is pivotal in fundamental research and diverse applications, from water desalination to energy harvesting and biological analysis. Dynamically manipulating nanofluidic…
A Data-Driven Approach to Coarse-Graining Simple Liquids in Confinement
Ishan Nadkarni, Haiyi Wu, Narayana. R. Aluru
We propose a data-driven framework for identifying coarse-grained (CG) Lennard-Jones (LJ) potential parameters in confined systems for simple liquids. Our approach involves the use…
Imaging the electron charge density in monolayer MoS2 at the Ångstrom scale
Joel Martis, Sandhya Susarla, Archith Rayabharam +15
Four-dimensional scanning transmission electron microscopy (4D-STEM) has recently gained widespread attention for its ability to image atomic electric fields with sub-Ångstrom spat…
Surrogate Neural Network Model for Sensitivity Analysis and Uncertainty Quantification of the Mechanical Behavior in the Optical Lens-Barrel Assembly
Shantanu Shahane, Erman Guleryuz, Diab W Abueidda +7
Surrogate neural network-based models have been lately trained and used in a variety of science and engineering applications where the number of evaluations of a target function is…
Anomalous interfacial dynamics of single proton charges in binary aqueous solutions
Jean Comtet, Archith Rayabharam, Evgenii Glushkov +6
Understanding the dynamics of charge exchange between a solid surface and a liquid is fundamental to various situations, ranging from nanofiltration to catalysis and electrochemist…
Optimization of Solidification in Die Casting using Numerical Simulations and Machine Learning
Shantanu Shahane, Narayana Aluru, Placid Ferreira +2
In this paper, we demonstrate the combination of machine learning and three dimensional numerical simulations for multi-objective optimization of low pressure die casting. The cool…
Finite Volume Simulation Framework for Die Casting with Uncertainty Quantification
Shantanu Shahane, Narayana Aluru, Placid Ferreira +2
The present paper describes the development of a novel and comprehensive computational framework to simulate solidification problems in materials processing, specifically casting p…
Uncertainty Quantification in Three Dimensional Natural Convection using Polynomial Chaos Expansion and Deep Neural Networks
Shantanu Shahane, Narayana R. Aluru, Surya Pratap Vanka
This paper analyzes the effects of input uncertainties on the outputs of a three dimensional natural convection problem in a differentially heated cubical enclosure. Two different…
Strain Modulation of Graphene by Nanoscale Substrate Curvatures: A Molecular View
Yingjie Zhang, Mohammad Heiranian, Blanka Janicek +7
Spatially nonuniform strain is important for engineering the pseudomagnetic field and band structure of graphene. Despite the wide interest in strain engineering, there is still a…
Structural Disorder and Electronic Structure in Alloyed SrTiO3/SrFeO2.5 Compounds: A Theoretical Study
Bin Ouyang, Tim Mueller, Nicola H. Perry +2
Many mixed ionic/electronic conductors (MIECs) applied in fuel cell electrodes can be considered as alloys between perovskite oxides and ordered oxygen vacancy compounds. For examp…
Capacitive Sensing of Intercalated H2O Molecules Using Graphene
Eric J. Olson, Rui Ma, Tao Sun +5
Understanding the interactions of ambient molecules with graphene and adjacent dielectrics is of fundamental importance for a range of graphene-based devices, particularly sensors,…