13 citations · 20 across the 13 of their papers we have counts for
15 papers
Materials Behavior as Mechanism Ensembles: A Probabilistic Framework for Emergent Behaviors
Brad L. Boyce, Mitchell A. Wood, Krishna Garikipati +16
Materials behavior is often treated as a deterministic mapping from structure to properties, yet many important phenomena emerge from the conditional activation of multiple mechani…
LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMs
Sanchit Kabra, Nikhil Abhyankar, Saaketh Desai +2
Scientific discovery is a closed-loop process in which hypotheses guide data acquisition and observations refine the hypothesis space. Yet most approaches reduce discovery to super…
Boltzmann Reinforcement Learning for Noise resilience in Analog Ising Machines
Aditya Choudhary, Saaketh Desai, Prasad Iyer
Analog Ising machines (AIMs) have emerged as a promising paradigm for combinatorial optimization, utilizing physical dynamics to solve Ising problems with high energy efficiency. H…
Learning interpretable surface elasticity properties from bulk properties
Saaketh Desai, Prasad P. Iyer, Remi Dingreville
Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface s…
A broadband silicon photonic-integrated-circuit based RF spectrum analyzer with 10 MHz spectral resolution
Brandon Redding, Joseph B. Murray, Matthew J. Murray +10
Designing miniaturized optical spectrometers is an increasingly active area of research as spectrometers are crucial components for a wide range of applications including chemical…
LLEMA: Evolutionary Search with LLMs for Multi-Objective Materials Discovery
Nikhil Abhyankar, Sanchit Kabra, Saaketh Desai +1
Materials discovery requires navigating vast chemical and structural spaces while satisfying multiple, often conflicting, objectives. We present LLM-guided Evolution for MAterials…
AutoSciLab: A Self-Driving Laboratory For Interpretable Scientific Discovery
Saaketh Desai, Sadhvikas Addamane, Jeffrey Y. Tsao +4
Advances in robotic control and sensing have propelled the rise of automated scientific laboratories capable of high-throughput experiments. However, automated scientific laborator…
Self-driving lab discovers principles for steering spontaneous emission
Saaketh Desai, Sadhvikas Addamane, Jeffery Y. Tsao +3
We developed an autonomous experimentation platform to accelerate interpretable scientific discovery in ultrafast nanophotonics, targeting a novel method to steer spontaneous emiss…
Rethinking materials simulations: Blending direct numerical simulations with neural operators
Vivek Oommen, Khemraj Shukla, Saaketh Desai +2
Direct numerical simulations (DNS) are accurate but computationally expensive for predicting materials evolution across timescales, due to the complexity of the underlying evolutio…
Active learning and molecular dynamics simulations to find high melting temperature alloys
David E. Farache, Juan C. Verduzco, Zachary D. McClure +2
Active learning (AL) can drastically accelerate materials discovery; its power has been shown in various classes of materials and target properties. Prior efforts have used machine…
Sim2Ls: FAIR simulation workflows and data
Martin Hunt, Steven Clark, Daniel Mejia +2
Just like the scientific data they generate, simulation workflows for research should be findable, accessible, interoperable, and reusable (FAIR). However, while significant progre…
Parsimonious neural networks learn interpretable physical laws
Saaketh Desai, Alejandro Strachan
Machine learning is playing an increasing role in the physical sciences and significant progress has been made towards embedding domain knowledge into models. Less explored is its…
Implementing a neural network interatomic model with performance portability for emerging exascale architectures
Saaketh Desai, Samuel Temple Reeve, James F. Belak
The two main thrusts of computational science are more accurate predictions and faster calculations; to this end, the zeitgeist in molecular dynamics (MD) simulations is pursuing m…
Tuning martensitic transformations via coherent second phases in nanolaminates using free energy landscape engineering
Saaketh Desai, Samuel Temple Reeve, Karthik Guda Vishnu +1
We explore the possibilities and limitations of using a coherent second phase to engineer the thermo-mechanical properties of a martensitic alloy by modifying the underlying free e…
Molecular Modeling of the Microstructure Evolution during the Carbonization of PAN-Based Carbon Fibers
Saaketh Desai, Chunyu Li, Tongtong Shen +1
Development of high strength carbon fibers (CFs) requires an understanding of the relationship between the processing conditions, microstructure and resulting properties. We develo…