arXiv subjects

Manas Sharma

Publications and source records attributed to Manas Sharma.

6 recordsLinked to original sources

arXiv2026

MLIP Studio: An Open Platform for Interactive Benchmarking and Atomistic Simulations Using Machine Learning Interatomic Potentials

Universal machine learning interatomic potentials (MLIPs) are foundation AI models transforming atomistic simulations, but their practical use remains hindered by fragmented software ecosystems, dependency conflicts, and the lack of accessible benchmarking tools. These models approach first-principles density functional theory (DFT) accuracy at a fraction of the computational cost. We introduce MLIP Studio (available at https://mlipstudio.iisc.ac.in), an open and free platform that brings more than 60 universal MLIPs into a unified interactive interface for molecules and materials. The platform enables end-to-end MLIP-driven workflows, including property prediction, geometry optimization, vibrational and equation-of-state analysis, spin-state determination, custom model deployment, and high-throughput benchmarking against reference data. Automated parity plots and sortable error tables facilitate rapid identification of element-wise outliers and problematic data points. We demonstrate that MLIP-based pre-optimization can reduce subsequent DFT optimization effort by ~33$\times$. Additionally, the application enables benchmarking of computational performance. Through a comprehensive case study involving the 2D magnetic material CrCl$_3$ on a sapphire substrate, we show how cross-model comparisons of various properties and potential-energy landscapes can guide task-specific MLIP selection. Overall, MLIP Studio lowers the barrier to the reliable use of foundation models in end-to-end research workflows, benchmarking, and education in computational chemistry and materials science.

cond-mat.mtrl-sci↗

arXiv2026

Direct nanoscale mapping of band alignment in single-layer semiconducting lateral heterojunctions

Atomic-scale control over band alignment in single-layer lateral heterostructures (LHSs) of dissimilar transition metal dichalcogenides (TMDCs) is critical for nextgeneration electronic, optoelectronic, and quantum technologies. However, direct experimental access to interfacial electronic states with nanometer precision remains a significant challenge. Here, we employ angle-resolved photoemission spectroscopy with nanoscale spatial resolution (nanoARPES) to directly map the epitaxial alignment and valence band evolution across MoSe2-WSe2 LHSs. By combining nanoARPES with spatially resolved photoluminescence, we correlate the evolution of the valence band maximum and exciton features across both atomically sharp and compositionally graded diffusive interfaces. We identified type-II band alignments governed by both material composition and interstitial-induced modifications of band offsets, in close agreement with density functional theory calculations. These results reveal fundamental mechanisms of electronic structure modulation at 1D TMDC heterointerfaces and provide a robust platform for tailored band engineering in van der Waals materials.

cond-mat.mes-hall↗

arXiv2026

PersistBench: When Should Long-Term Memories Be Forgotten by LLMs?

Conversational assistants are increasingly integrating long-term memory with large language models (LLMs). This persistence of memories, e.g., the user is vegetarian, can enhance personalization in future conversations. However, the same persistence can also introduce safety risks that have been largely overlooked. Hence, we introduce PersistBench to measure the extent of these safety risks. We identify two long-term memory-specific risks: cross-domain leakage, where LLMs inappropriately inject context from the long-term memories; and memory-induced sycophancy, where stored long-term memories insidiously reinforce user biases. We evaluate 18 frontier and open-source LLMs on our benchmark. Our results reveal a surprisingly high failure rate across these LLMs - a median failure rate of 53% on cross-domain samples and 97% on sycophancy samples. To address this, our benchmark encourages the development of more robust and safer long-term memory usage in frontier conversational systems.

cs.AI↗

arXiv2025

Tailored Vapor Deposition Unlocks Large-Grain, Wafer-Scale Epitaxial Growth of 2D Magnetic CrCl3

Two-dimensional magnetic materials (2D-MM) are an exciting playground for fundamental research, and for spintronics and quantum sensing. However, their large-grain large-area synthesis using scalable vapour deposition methods is still an unsolved challenge. Here, we develop a tailored approach for centimetre-scale growth of semiconducting 2D-MM CrCl3 films on mica substrate, via physical vapour transport deposition. A controlled synthesis protocol, enabled via innovations concerning light management, very-high carrier-gas flow, precursor flux, and oxygen/moisture removal, is critical for wafer-scale growth. Optical, stoichiometric, structural, and magnetic characterization identify crystalline, phase-pure 2D-MM CrCl3. Substrate temperature tunes thickness of films from few-layers to tens of nanometres. Further, selective-area growth and large-area transfer are demonstrated. Substrate-dependent growth features are explained by density functional theory and state-of-the-art machine learning interatomic potential-based atomic-scale simulations. This scalable vapour deposition approach can be applied for growth of several 2D-MM, and low growth temperature (~500 C) will enable creation of hybrid heterostructures.

cond-mat.mtrl-sci↗

arXiv2022

Resonance effects in Brunel harmonic generation in thin film organic semiconductors

Organic semiconductors have attracted extensive attention due to their excellent optical and electronic properties. Here, we present an experimental and theoretical study of Brunel harmonic generation in two types of porphyrin thin films: tetraphenylporphyrin (TPP) and its organometallic complex derivative Zinc tetraphenylporphyrin (ZnTPP). Our results show that the $\pi$-$\pi^\ast$ excitation of the porphyrin ringsystem plays a major role in the harmonic generation process. We uncovered the contribution of an interband process to Brunel harmonic generation. In particular, the resonant ($S_0 \rightarrow S_2$ transition) enhanced multiphoton excitation is found to lead to an early onset of non-perturbative behavior for the 5th harmonic. Similar resonance effects are expected in Brunel harmonic generation with other organic materials.

physics.optics↗

arXiv2021

The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification

The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR), and the Medical Image Computing and Computer Assisted Interventions (MICCAI) society. Since its inception, BraTS has been focusing on being a common benchmarking venue for brain glioma segmentation algorithms, with well-curated multi-institutional multi-parametric magnetic resonance imaging (mpMRI) data. Gliomas are the most common primary malignancies of the central nervous system, with varying degrees of aggressiveness and prognosis. The RSNA-ASNR-MICCAI BraTS 2021 challenge targets the evaluation of computational algorithms assessing the same tumor compartmentalization, as well as the underlying tumor's molecular characterization, in pre-operative baseline mpMRI data from 2,040 patients. Specifically, the two tasks that BraTS 2021 focuses on are: a) the segmentation of the histologically distinct brain tumor sub-regions, and b) the classification of the tumor's O[6]-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. The performance evaluation of all participating algorithms in BraTS 2021 will be conducted through the Sage Bionetworks Synapse platform (Task 1) and Kaggle (Task 2), concluding in distributing to the top ranked participants monetary awards of $60,000 collectively.

cs.CV↗