arXiv subjects

Sudipta Biswas

Publications and source records attributed to Sudipta Biswas.

9 recordsLinked to original sources

arXiv2026

Symmetry-selective field-induced triplet superconductivity in Ising-superconductor monolayer NbSe$_2$

We investigate superconductivity in monolayer NbSe$_2$, an Ising superconductor, under an in-plane Zeeman field $h_x$, focusing on the emergence of symmetry selected equal-spin triplet pairing. Using a self-consistent Bogoliubov--de Gennes approach with realistic hopping parameters for monolayer NbSe$_2$ on a triangular lattice, we determine the energetically favored singlet pairing states in a range of chemical potentials $\mu$ for onsite, nearest-neighbor, and next-nearest-neighbor pairing channels, and map the resulting phase diagram in $(h_x,\mu)$ plane. A momentum-resolved analysis reveals distinct dominant contributions in order parameters arise from the surroundings of $\Gamma$, $K$, and $K'$ points of the Brillouin zone. We find that an in-plane magnetic field helps to induce a triplet pairing whose symmetry is determined by the parent singlet state, upon opening the triplet interaction channel. For the nonlocal pairing channels, chiral-$d$ pairing is energetically favored and it induces chiral-$p$ equal-spin triplet component with opposite chirality. We further find that Rashba spin-orbit coupling, relevant to substrate coupling and electrostatic gating, suppresses the superconducting orders and reduces the critical field. Our results establish a direct link between the symmetry of the parent singlet condensate and the emergent triplet superconductivity, highlighting monolayer NbSe$_2$ as a promising platform for field-tunable mixed-parity superconducting states.

cond-mat.supr-con↗

arXiv2026

MxDiffusion: A Physics-Aware Maxwells Law-Guided Diffusion Model Strategy for Inverse Photonic Metasurface Design

We introduce MxDiffusion, a hybrid physics- and data-driven diffusion-based framework that enables efficient and highly accurate generation of photonic structures from target optical properties. The improved accuracy is achieved through a two-stage generation strategy, in which the first diffusion model is explicitly trained with Maxwells equation-based loss to embed physical insight directly into the inverse design process, while the second model maps the physically consistent intermediate representation to the final structural geometry with significantly higher fidelity than solely data-driven approaches. The performance of MxDiffusion is validated on two representative applications: gold nanostructures patterned on a silica substrate and a highly tunable bandpass filter based on phase change material. In both cases, the proposed framework consistently outperforms a conventional data-driven diffusion model benchmark, particularly for out-of-training-distribution design targets and highly constrained resonance conditions. These results demonstrate the efficacy and superiority of MxDiffusion as a general physics-guided inverse design paradigm.

physics.optics↗

arXiv2025

Inhomogeneous phase stiffness in two-dimensional $s$-wave disordered superconductors

We investigate the effect of white-noise disorder on the local phase stiffness and thermodynamic properties of a two-dimensional $s$-wave superconductor. Starting from a local attractive model and using path-integral formalism, we derive an effective action by decoupling the superconducting order parameter into amplitude and phase components in a gauge-invariant manner. Perturbative techniques are applied to the phase fluctuation sector to derive an effective phase-only XY model for disordered superconducting systems. Solving the saddle-point Green's function using Bogoliubov-de Gennes theory, we calculate the distributions of nearest-neighbor couplings for various disorder strengths. A single-peak distribution is observed for low disorder strength, which becomes bimodal with one peak at negative couplings as the disorder strength increases. The local phase stiffness remains randomly distributed throughout the lattice and shows no correlation with pairing amplitudes. The temperature dependence of the superfluid stiffness ($J_s$) is studied using Monte Carlo simulations. At strong disorder and low temperatures, $J_s$ increases with increasing temperature, exhibiting anomalous behavior that may indicate the onset of a glassy transition. Additionally, calculations of the Edwards-Anderson order parameter in this disorder regime suggest the emergence of a $phase$-$glass$ state at very low temperatures.

cond-mat.supr-con↗

arXiv2025

Xenon-metal pair formation in UO2 investigated using DFT+U

A recent experimental study on a spent uranium dioxide (UO2) fuel sample from Belgium Reactor 3 (BR3) identified a unique pair structure formed by the noble metal phase (NMP) and fission gas (xenon [Xe]) precipitate. However, the fundamental mechanism behind this structure remains unclear. The present study aims to provide an understanding of the interaction between five different metal precipitates (molybdenum [Mo], ruthenium [Ru], palladium [Pd], technetium [Tc], and rhodium [Rh]) and the Xe fission gas atoms in UO2, by using density functional theory (DFT) in combination with the Hubbard U correction to compute the formation energies involved. All DFT+U calculations were performed with occupation matrix control to ensure antiferromagnetic ordering of UO2. The calculated formation and binding energies of the Xe and solid fission products in the NMP reveal that these metal precipitates form stable pair structures with Xe. Notably, the formation energy of Xe-metal pairs is lower than that of the isolated single defects in all instances, with Pd and Mo showing the most favourable binding energy, likely accounting for the observed pair structure formation.

cond-mat.mtrl-sci↗

arXiv2024

Benchmarking Floworks against OpenAI & Anthropic: A Novel Framework for Enhanced LLM Function Calling

Large Language Models (LLMs) have shown remarkable capabilities in various domains, yet their economic impact has been limited by challenges in tool use and function calling. This paper introduces ThorV2, a novel architecture that significantly enhances LLMs' function calling abilities. We develop a comprehensive benchmark focused on HubSpot CRM operations to evaluate ThorV2 against leading models from OpenAI and Anthropic. Our results demonstrate that ThorV2 outperforms existing models in accuracy, reliability, latency, and cost efficiency for both single and multi-API calling tasks. We also show that ThorV2 is far more reliable and scales better to multistep tasks compared to traditional models. Our work offers the tantalizing possibility of more accurate function-calling compared to today's best-performing models using significantly smaller LLMs. These advancements have significant implications for the development of more capable AI assistants and the broader application of LLMs in real-world scenarios.

cs.AI↗

arXiv2023

A coupled magneto-structural continuum model for multiferroic $\mathrm{BiFeO}_3$

A continuum approach to study magnetoelectric multiferroic $\mathrm{BiFeO}_3$ (BFO) is proposed. Our modeling effort marries the ferroelectric (FE) phase field method and micromagnetic simulations in order to describe the entire multiferroic order parameter sector (polarization, oxygen antiphase tilts, strain, and magnetism) self-consistently on the same time and length scale. In this paper, we discuss our choice of ferroelectric and magnetic energy terms and demonstrate benchmarks against known behavior. We parameterize the lowest order couplings of the structural distortions against previous predictions from density functional theory calculations giving access to simulations of the FE domain wall (DW) topology. This allows us to estimate the energetic hierarchy and thicknesses of the numerous structural DWs. We then extend the model to the canted antiferromagnetic order and demonstrate how the ferroelectric domain boundaries influence the resulting magnetic DWs. We also highlight some capabilities of this model by providing two examples relevant for applications. We demonstrate spin wave transmission through the multiferroic domain boundaries which identify rectification in qualitative agreement with recent experimental observations. As a second example of application, we model fully-dynamical magnetoelectric switching, where we find a sensitivity on the Gilbert damping with respect to switching pathways. We envision that this modeling effort will set the basis for further work on properties of arbitrary 3D nanostructures of BFO (and related multiferroics) at the mesoscale.

cond-mat.mtrl-sci↗

arXiv2022

Superior-catalytic performance of Ni-Co Layered double hydroxide nanosheets for the reduction of p-nitrophenol

Layered double-hydroxides (LDHs) are superior to the conventional (Transition Metal Oxides) TMOs as their lamellar morphology accommodates higher active sites contributing to the facile electron transfer towards the material degradation relations, thus attracts an immense attention for catalysis application. Moreover, the high catalytic activity of LDHs is linked to their facile anion exchange, specific electronic structures, and versatile chemical compositions. Recently, LDHs with bimetallic or ternary combinations are preferably used for hydrogenation of p-nitrophenol, a toxic and carcinogenic pollutant commonly found in industrial wastewater. Herein, a cost-effective co-precipitation fabrication protocol to obtain Ni-Co layered double hydroxide is proposed. The well-defined arrangement of active sites in the 2D structure of LDH, and the synergistic catalytic effect of Ni and Co greatly improves the efficiency for the conversion of p-nitrophenol (p-NP) to p-aminophenol (p-AMP). The catalytic performance at higher temperatures is also shown. The obtained results are further extended to explore the advantage of Ni-Co LDH as an electrocatalyst for Hydrogen Evolution Reaction (HER).

cond-mat.mtrl-sci↗

arXiv2022

Role of porosity and diffusion coefficient in porous electrode used in supercapacitors- Correlating theoretical and experimental studies

Porous electrodes are fast emerging as essential components for next generation supercapacitors. Using porous structures of Co3O4, Mn3O4, alpha Fe2O3, and carbon, their advantages over the solid counterpart is unequivocally established. The improved performance in porous architecture is linked to the enhanced active specific surface and direct channels leading to improved electrolyte interaction with the redox active sites. A theoretical model utilizing the Fick's law is proposed, that can consistently explain the experimental data. The porous structures exhibit nearly 50 - 80 percentage increment in specific capacitance, along with high rate capabilities and excellent cycling stability due to the higher diffusion coefficients.

cond-mat.mtrl-sci↗

arXiv2016

Electronic Single Molecule Identification of Carbohydrate Isomers by Recognition Tunneling

Glycans play a central role as mediators in most biological processes, but their structures are complicated by isomerism. Epimers and anomers, regioisomers, and branched sequences contribute to a structural variability that dwarfs those of nucleic acids and proteins, challenging even the most sophisticated analytical tools, such as NMR and mass spectrometry. Here, we introduce an electron tunneling technique that is label-free and can identify carbohydrates at the single-molecule level, offering significant benefits over existing technology. It is capable of analyzing sub-picomole quantities of sample, counting the number of individual molecules in each subset in a population of coexisting isomers, and is quantitative over more than four orders of magnitude of concentration. It resolves epimers not well separated by ion-mobility and can be implemented on a silicon chip. It also provides a readout mechanism for direct single-molecule sequencing of linear oligosaccharides.

physics.chem-ph↗