N. M. Anoop Krishnan
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View article: Bringing ML to the real world: rewards are all we need
Bringing ML to the real world: rewards are all we need Open
Realizing the promise of artificial intelligence (AI) to accelerate scientific progress and deliver technological impact depends on how effectively AI can be integrated into real-world decision- making processes. As Peter Norvig states, “S…
View article: On the Equivalence of Regression and Classification
On the Equivalence of Regression and Classification Open
A formal link between regression and classification has been tenuous. Even though the margin maximization term $\|w\|$ is used in support vector regression, it has at best been justified as a regularizer. We show that a regression problem …
View article: Hybrid models combining trend and seasonality components with machine learning algorithms provide accurate forecasting of malaria incidence
Hybrid models combining trend and seasonality components with machine learning algorithms provide accurate forecasting of malaria incidence Open
Forecasting malaria incidence is vital for effective resource allocation during malaria elimination. In this study, we highlight robust models for forecasting incidence using climatic and malaria data from Goa, India. Multi-collinearity an…
View article: Optimization of Transferable Interatomic Potentials for Glasses toward Experimental Properties
Optimization of Transferable Interatomic Potentials for Glasses toward Experimental Properties Open
The accuracy of molecular simulations is fundamentally limited by the interatomic potentials that govern atomic interactions. Traditional potential development, which relies heavily on ab initio calculations, frequently struggles to reprod…
View article: Evaluating large language model agents for automation of atomic force microscopy
Evaluating large language model agents for automation of atomic force microscopy Open
Large language models (LLMs) are transforming laboratory automation by enabling self-driving laboratories (SDLs) that could accelerate materials research. However, current SDL implementations rely on rigid protocols that fail to capture th…
View article: Perspective on artificial intelligence for accelerated materials design (AI4Mat) workshops in 2024
Perspective on artificial intelligence for accelerated materials design (AI4Mat) workshops in 2024 Open
The intersection of artificial intelligence and materials science has become increasingly interconnected, driving ambitious research initiatives across both fields. Since 2022, the AI for accelerated materials design (AI4Mat) workshops hav…
View article: MatSKRaFT
MatSKRaFT Open
Scientific progress increasingly depends on synthesizing knowledge across vast literature, yet most experimental data remains trapped in semi-structured formats that resist systematic extraction and analysis. Here, we present MatSKRAFT, a …
View article: Author Correction: Probing the limitations of multimodal language models for chemistry and materials research
Author Correction: Probing the limitations of multimodal language models for chemistry and materials research Open
View article: Probing the limitations of multimodal language models for chemistry and materials research
Probing the limitations of multimodal language models for chemistry and materials research Open
Recent advancements in artificial intelligence have sparked interest in scientific assistants that could support researchers across the full spectrum of scientific workflows, from literature review to experimental design and data analysis.…
View article: Pressure-induced structural transformations at different length scales in soda-lime silica glasses
Pressure-induced structural transformations at different length scales in soda-lime silica glasses Open
View article: Precise Real‐Time Measurement of Liquid Viscosity Using Digital Video Data
Precise Real‐Time Measurement of Liquid Viscosity Using Digital Video Data Open
Quantitative knowledge of liquid viscosity is of fundamental importance in many areas of materials synthesis and processing. However, the determination of viscosity often relies on specialized experimental equipment, offline experimentatio…
View article: Industrial-scale prediction of cement clinker phases using machine learning
Industrial-scale prediction of cement clinker phases using machine learning Open
View article: Reactive Glass Metal Interaction under Ambient Conditions Enables Surface Modification of Gold Nanoislands
Reactive Glass Metal Interaction under Ambient Conditions Enables Surface Modification of Gold Nanoislands Open
Stabilizing gold nanoparticles with tunable surface composition via reactive metal support interactions under ambient conditions remains a significant challenge. We discovered that a reactive glass metal interaction (RGMI) under ambient co…
View article: CoNO: Complex neural operator for continous dynamical physical systems
CoNO: Complex neural operator for continous dynamical physical systems Open
Neural operators extend data-driven models to map between infinite-dimensional functional spaces. While these operators perform effectively in either the time or frequency domain, their performance may be limited when applied to non-statio…
View article: A neural operator for forecasting carbon monoxide evolution in cities
A neural operator for forecasting carbon monoxide evolution in cities Open
Real-time forecasting of carbon monoxide (CO) concentrations is essential for enabling timely interventions to improve urban air quality. Conventional air quality models often require extensive computational resources for accurate, multi-s…
View article: Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials
Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials Open
Universal Machine Learning Interactomic Potentials (MLIPs) enable accelerated simulations for materials discovery. However, current research efforts fail to impactfully utilize MLIPs due to: 1. Overreliance on Density Functional Theory (DF…
View article: Disorder-induced enhancement of lithium-ion transport in solid-state electrolytes
Disorder-induced enhancement of lithium-ion transport in solid-state electrolytes Open
View article: CoNOAir: A Neural Operator for Forecasting Carbon Monoxide Evolution in Cities
CoNOAir: A Neural Operator for Forecasting Carbon Monoxide Evolution in Cities Open
Carbon Monoxide (CO) is a dominant pollutant in urban areas due to the energy generation from fossil fuels for industry, automobile, and domestic requirements. Forecasting the evolution of CO in real-time can enable the deployment of effec…
View article: Evaluation of Methods Employed in Establishing Preclinical Similarity of Adalimumab Biosimilars
Evaluation of Methods Employed in Establishing Preclinical Similarity of Adalimumab Biosimilars Open
Adalimumab, marketed as Humira, is a fully humanized monoclonal antibody that blocks the activity of tumor necrosis factor‐alpha and is used in treating several autoimmune disorders. As one of the top‐grossing pharmaceuticals, its global s…
View article: Autonomous Microscopy Experiments through Large Language Model Agents
Autonomous Microscopy Experiments through Large Language Model Agents Open
The emergence of large language models (LLMs) has accelerated the development of self-driving laboratories (SDLs) for materials research. Despite their transformative potential, current SDL implementations rely on rigid, predefined protoco…
View article: Autonomous Microscopy Experiments through Large Language Model Agents
Autonomous Microscopy Experiments through Large Language Model Agents Open
The emergence of large language models (LLMs) has accelerated the development of self-driving laboratories (SDLs) for materials research. Despite their transformative potential, current SDL implementations rely on rigid, predefined protoco…
View article: Industrial-scale Prediction of Cement Clinker Phases using Machine Learning
Industrial-scale Prediction of Cement Clinker Phases using Machine Learning Open
Cement production, exceeding 4.1 billion tonnes and contributing 2.4 tonnes of CO2 annually, faces critical challenges in quality control and process optimization. While traditional process models for cement manufacturing are confined to s…
View article: Foundational Large Language Models for Materials Research
Foundational Large Language Models for Materials Research Open
Materials discovery and development are critical for addressing global challenges. Yet, the exponential growth in materials science literature comprising vast amounts of textual data has created significant bottlenecks in knowledge extract…
View article: Probing the limitations of multimodal language models for chemistry and materials research
Probing the limitations of multimodal language models for chemistry and materials research Open
Recent advancements in artificial intelligence have sparked interest in scientific assistants that could support researchers across the full spectrum of scientific workflows, from literature review to experimental design and data analysis.…
View article: Reverse Polarizability of Rare Earth Ions (La<sup>3+</sup>, Gd<sup>3+</sup>, Lu<sup>3+</sup>, Y<sup>3+</sup>) in Tellurite Glasses and Glass Ceramics for Optical Limiting
Reverse Polarizability of Rare Earth Ions (La<sup>3+</sup>, Gd<sup>3+</sup>, Lu<sup>3+</sup>, Y<sup>3+</sup>) in Tellurite Glasses and Glass Ceramics for Optical Limiting Open
All-optical modulation using inherent third-order optical nonlinearity of a medium has garnered considerable interest in photonics and optoelectronics. Herein, nonlinear optical (NLO) properties of tellurite glasses and glass ceramics (GCs…
View article: Force field optimization by end-to-end differentiable atomistic simulation
Force field optimization by end-to-end differentiable atomistic simulation Open
The accuracy of atomistic simulations depends on the precision of force fields. Traditional numerical methods often struggle to optimize the empirical force field parameters for reproducing target properties. Recent approaches rely on trai…
View article: Interpretable machine learning for understanding compositional and testing condition effects on refractive index, density, dielectric constant, and loss tangent of inorganic melts and glasses
Interpretable machine learning for understanding compositional and testing condition effects on refractive index, density, dielectric constant, and loss tangent of inorganic melts and glasses Open
Artificial intelligence (AI) and machine learning (ML) have enabled property-targeted design of glasses. Several machine learning models and open-source tools in the literature allow researchers to predict the optical, physical, mechanical…
View article: Discovering symbolic laws directly from trajectories with hamiltonian graph neural networks
Discovering symbolic laws directly from trajectories with hamiltonian graph neural networks Open
The time evolution of physical systems is described by differential equations, which depend on abstract quantities like energy and force. Traditionally, these quantities are derived as functionals based on observables such as positions and…
View article: Developing on-the-fly machine learning force-fields for alkali silicate glasses
Developing on-the-fly machine learning force-fields for alkali silicate glasses Open
View article: TAGMol: Target-Aware Gradient-guided Molecule Generation
TAGMol: Target-Aware Gradient-guided Molecule Generation Open
3D generative models have shown significant promise in structure-based drug design (SBDD), particularly in discovering ligands tailored to specific target binding sites. Existing algorithms often focus primarily on ligand-target binding, c…