arXiv subjects

Sunita Kumari

Publications and source records attributed to Sunita Kumari.

16 recordsLinked to original sources

arXiv2026

Charge Regulated conformational properties of polyelectrolyte near an oppositely charged nanoparticle

Customizing the surface characteristics and stimuli-responsive behavior of nanoparticles with polyelectrolytes ushers in a new era across many aspects of our lives, ranging from advanced diagnostics to practical applications. Here, using hybrid CR Monte Carlo/ molecular dynamics simulations, we investigate how charge regulation can play a crucial role in shaping the adsorption dynamics of polyelectrolyte (PE) on oppositely charged nanoparticle (NP). We systematically investigate the influence of salt density, and polymer chain length on the PE-NP interaction. To complement CR results, we also perform molecular simulations under constant charge conditions. At high salt concentrations, CR enhances the adsorption of PE onto the NP surface, leading to a rapid decrease in the radius of gyration of PE; conversely, CC promotes the extended conformation of PE. No clear effect of PE length is observed at either low or high salt concentrations, whereas in CC simulations, the PE relaxes faster on the NP in the case of short chains. Furthermore, By comparing these results, we demonstrate that the MSD of PE follows a more direct path during adsorption implying a ballistic motion, whereas in the CC case, it exhibits subdiffusive behavior and delayed adsorption in both low and high salt density. Our findings indicates that 'tunable CR' is a robust strategy for controlling nanoparticle stability and interaction within a complex biochemical cues.

cond-mat.soft↗

arXiv2026

Emergence of Dynamical Anisotropy induced by Demixing in a Binary System with Differential Diffusivity under an External Potential

Spontaneous demixing in active matter is a ubiquitous phenomenon that is crucial for numerous living processes ranging from bacterial swarming to sorting of cells in dense tissues. Here, we systematically investigate the effect of spatially varying potential acting along one direction and packing fraction on the binary mixture of particles with different diffusivities. Our results indicate that the presence of an external potential promotes demixing over a larger range of packing fractions, while also fostering a more pronounced 'hexatic order' within the bands of less diffusive "cold") particles formed near the minima of the potential. The mean-squared displacements (MSD) of "cold" and "hot" particles in different directions exhibit a distinct behavior. In contrast to the long-time sub-diffusive behavior of the "cold" particles, the "hot" ones display diffusive nature following an intermediate plateau. However, in the direction transverse to the applied potential, both types of particles undergo normal diffusion. Furthermore, interesting non-Gaussian characteristics are observed, corresponding to the spatial distribution of the displacement of "hot" and "cold" particles. Interestingly, our results reveal the formation of a 'percolating band', and the emergence of such dynamic anisotropy is not observed in the absence of an external potential. These aspects are highly relevant to the dynamics of various systems-including densely packed tissues, bacterial motility in confined spaces, and granular segregation in the pharmaceutical industry.

cond-mat.soft↗

arXiv2025

Charge Regulation Effect on Nanoparticles Interaction Mediated by Polyelectrolyte

The ability to precisely control surface charge using charged polymers is fundamental to many nanotechnology applications, enabling the design and fabrication of materials with tailored properties and functionalities. Here, we study the effect of charge regulation (CR) on the interaction between two nanoparticles (NPs) mediated by an oppositely charged polyelectrolyte (PE) in an electrolyte solution. To this end, we employ a hybrid CR Monte Carlo / molecular dynamics simulation framework to systematically explore the effects of pH, salt concentration, and polymer chain length on NP surface charge behavior. For comparison, we also conduct molecular simulations under constant charge (CC) conditions. Our results reveal that CR enhances PE adsorption onto NP surfaces compared to the CC case, where polymer bridging dominates across a wide range of NP intersurface separations. This enhanced adsorption under CR leads to a weak net repulsion driven by osmotic forces. In contrast, the CC model yields a stronger net attraction due to the bridging force. Furthermore, we find that the CR effects are more pronounced at low salt concentration, whereas at high salt concentration, counterion screening dominates in both CR and CC cases, diminishing the CR effect. These findings highlight the importance of incorporating charge regulation in characterizing nanoparticle interactions within a complex biochemical environment, particularly in low salt concentrations.

cond-mat.soft↗

arXiv2025

Effect of charge regulation on the screening properties of zwitterionic macroion solutions

Precisely controlling the surface charge of zwitterionic macromolecules is crucial for tailoring their properties and optimizing them for specific applications. Here, we present a generalized calculation scheme for determining the screening length in solutions containing zwitterionic macroions, where the charge of the macroion is controlled by the electrolyte solution. This scheme bypasses the need to solve the Poisson Boltzmann equation by expressing the inverse screening parameter in terms of the derivative of pressure with respect to chemical potential. The scheme reveals that the screening length has two components: one related to the Debye length with effective charges, and another stemming from the macroion surface dissociation equilibrium, which exhibits a screening resonance behavior. Furthermore, we find that the nonuniform surface charge distribution induced by pH responsive charge regulation strongly affects the screening behavior. The charge regulation properties of macroions, even in dilute solutions, are a key factor in the screening of electrostatic interactions, offering insights into complex biological and nanomaterial systems.

cond-mat.soft↗

arXiv2025

Nanocrystal tuned ammonia gas sensing technique via impedance spectroscopy

Ammonia is a harmful chemical hazard known for its widespread industrial use. Exposure to ammonia can cause environmental damage, human health hazards, and huge economic losses. Therefore, ammonia gas sensors are essential for detecting ammonia leaks to avoid serious accidental injury and death. In this study, we synthesize a nanostructured (WO3) n-type metal oxide semiconductor doped with a rare earth element-transition metal (Ce-Cu) via hydrothermal method for ammonia gas sensing application. Structural analysis was performed using XRD and FESEM. Further we investigate the optical properties via UV-visible spectroscopy, FTIR, and PL. We found that doping of (Ce-Cu) led to significant improvement in thermal stability for ammonia detection and selectivity performance compared to that pure one, across a wide frequency range. We believe that these studies will pave the way for exploring the use of Ce-Cu to improve the gas sensing properties of semiconductor-based gas sensors.

cond-mat.mtrl-sci↗

arXiv2024

Computational Investigation of Reactivity Parameters, UV-Vis and IR Spectra, NLO Properties, and Temperature-Dependent Thermodynamic Characteristics of Schiff-Based Interdigitated 5O.m (m=14,16) Liquid Crystalline Compounds: A DFT Analysis

The article studies the different physical, vibrational, nonlinear optical, and thermodynamical properties of higher homologs 5O.m (m = 14,16) liquid crystalline compounds using density functional theory. The optimized structure of 5O.m (m= 14,16) liquid crystals was obtained by using density functional theory (DFT) with B3LYP functional and standard basis set 6-31G (d, p). The Infrared spectra (IR), various physical properties such as HOMO-LUMO, nonlinear optical properties (NLO), reactivity parameters, relative energy gaps, and electrostatic potential function are computed and analyzed using the optimized structure of 5O liquid crystal. The time-dependent density functional theory (TD-DFT) has been used to analyze and obtain UV-Vis spectra for both LC compounds. It is observed that the 5O.m (m=14,16) liquid crystals are showing the lower value of HOMO-LUMO energy gaps as 4.17ev which resulted in some highly fascinating optical and physical properties. Using DFT excellent agreement is observed between all spectrum patterns and the simulated UV-Vis and IR spectra. This article, however, also discussed temperature-dependent thermodynamical properties such as zero-point vibrational energy (ZPVE), total thermal energy, total specific heat capacity, rotational constants, and total entropy which enable us to understand the phase transition behavior and specific transition temperatures of different phases

cond-mat.mtrl-sci↗

arXiv2023

On the nature of screening in charge regulated macroion solutions

We present a derivation of the screening length for a solution containing a charge regulated macroion, e.g. protein, with its counterions. We show that it can be obtained directly from the second derivatives of the total free energy by taking recourse to the ``uncertainty relation" of the Legendre transform which connects the Hessians or the local curvatures of the free energy as a function of density and its Legendre transform, i.e., osmotic pressure, as a function of chemical potentials. Based on the Fowler-Guggenheim-Frumkin model of charge regulation we then analyze the ``screening resonance" and the ``overscreening" of the screening properties of the charge-regulated macroion solution.

physics.bio-ph↗

arXiv2023

Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the AgBioData Consortium

Over the last several decades, there has been rapid growth in the number and scope of agricultural genetics, genomics and breeding (GGB) databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as 'databases' throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, conducted a survey to assess the status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data sharing practices by AgBioData databases are in a healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that ontology use has not substantially changed since a similar survey was conducted in 2017. We recommend 1) providing training for database personnel in specific data sharing techniques, as well as in ontology use; 2) further study on what metadata is shared, and how well it is shared among databases; 3) promoting an understanding of data sharing and ontologies in the stakeholder community; 4) improving data sharing and ontologies for specific phenotypic data types and formats; and 5) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means.

cs.DB↗

arXiv2022

On the nature of screening in Voorn-Overbeek type theories

By using the recently formulated Legendre transform approach to the thermodynamics of charged systems, we explore the general form of the screening length in the Voorn-Overbeek type theories, that remains valid also in the cases where the entropy is not given by the ideal gas form as in the Debye-Huckel theory. The screening length consistent with the non-electrostatic terms in the free energy Ansatz for the Flory-Huggins and Voorn-Overbeek type theories, derived from the local curvature properties of the Legendre transform, has distinctly different behavior than the often invoked standard Debye screening length, though it reduces to it in some limiting cases.

physics.chem-ph↗

arXiv2021

Complete Scanning Application Using OpenCv

In the following paper, we have combined the various basic functionalities provided by the NumPy library and OpenCv library, which is an open source for Computer Vision applications, like conversion of colored images to grayscale, calculating threshold, finding contours and using those contour points to take perspective transform of the image inputted by the user, using Python version 3.7. Additional features include cropping, rotating and saving as well. All these functions and features, when implemented step by step, results in a complete scanning application. The applied procedure involves the following steps: Finding contours, applying Perspective transform and brightening the image, Adaptive Thresholding and applying filters for noise cancellation, and Rotation features and perspective transform for a special cropping algorithm. The described technique is implemented on various samples.

cs.CV↗

arXiv2021

Neural Computing

This chapter aims to provide next-level understanding of the problems of the world and the solutions available to those problems, which lie very well within the domain of neural computing, and at the same time are intelligent in their approach, to invoke a sense of innovation among the educationalists, researchers, academic professionals, students and people concerned, by highlighting the work done by major researchers and innovators in this field and thus, encouraging the readers to develop newer and more advanced techniques for the same. By means of this chapter, the societal problems are discussed and various solutions are also given by means of the theories presented and researches done so far. Different types of neural networks discovered so far and applications of some of those neural networks are focused on, apart from their theoretical understanding, the working and core concepts involved in the applications.

cs.NE↗

arXiv2021

Recombinant Sort: N-Dimensional Cartesian Spaced Algorithm Designed from Synergetic Combination of Hashing, Bucket, Counting and Radix Sort

Sorting is an essential operation which is widely used and is fundamental to some very basic day to day utilities like searches, databases, social networks and much more. Optimizing this basic operation in terms of complexity as well as efficiency is cardinal. Optimization is achieved with respect to space and time complexities of the algorithm. In this paper, a novel left-field N-dimensional cartesian spaced sorting method is proposed by combining the best characteristics of bucket sort, counting sort and radix sort, in addition to employing hashing and dynamic programming for making the method more efficient. Comparison between the proposed sorting method and various existing sorting methods like bubble sort, insertion sort, selection sort, merge sort, heap sort, counting sort, bucket sort, etc., has also been performed. The time complexity of the proposed model is estimated to be linear i.e. O(n) for the best, average and worst cases, which is better than every sorting algorithm introduced till date.

cs.DS↗

arXiv2021

WisdomNet: Prognosis of COVID-19 with Slender Prospect of False Negative Cases and Vaticinating the Probability of Maturation to ARDS using Posteroanterior Chest X-Rays

Coronavirus is a large virus family consisting of diverse viruses, some of which disseminate among mammals and others cause sickness among humans. COVID-19 is highly contagious and is rapidly spreading, rendering its early diagnosis of preeminent status. Researchers, medical specialists and organizations all over the globe have been working tirelessly to combat this virus and help in its containment. In this paper, a novel neural network called WisdomNet has been proposed, for the diagnosis of COVID-19 using chest X-rays. The WisdomNet uses the concept of Wisdom of Crowds as its founding idea. It is a two-layered convolutional Neural Network (CNN), which takes chest x-ray images as input. Both layers of the proposed neural network consist of a number of neural networks each. The dataset used for this study consists of chest x-ray images of COVID-19 positive patients, compiled and shared by Dr. Cohen on GitHub, and the chest x-ray images of healthy lungs and lungs affected by viral and bacterial pneumonia were obtained from Kaggle. The network not only pinpoints the presence of COVID-19, but also gives the probability of the disease maturing into Acute Respiratory Distress Syndrome (ARDS). Thus, predicting the progression of the disease in the COVID-19 positive patients. The network also slender the occurrences of false negative cases by employing a high threshold value, thus aids in curbing the spread of the disease and gives an accuracy of 100% for successfully predicting COVID-19 among the chest x-rays of patients affected with COVID-19, bacterial and viral pneumonia.

eess.IV↗

arXiv2021

Model of metameric locomotion in active directional filaments

Locomotion in segmented animals, such as annelids and myriapods (centipedes and millipedes), is generated by a coordinated movement known as metameric locomotion, which can be also implemented in robots designed to perform specific tasks. We introduce a theoretical model, based on an active directional motion of the head segment and a passive trailing of the rest of the body segments, in order to formalize and study the metameric locomotion. The model is specifically formulated as a steered Ornstein-Uhlenbeck curvature process, preserving the continuity of the curvature along the whole body filament, and thus supersedes the simple active Brownian model, which would be inapplicable in this case. We obtain the probability density by analytically solving the Fokker-Planck equation pertinent to the model. We also calculate explicitly the correlators, such as the mean-square orientational fluctuations, the orientational correlation function and the mean-square separation between the head and tail segments, both analytically either via the Fokker-Planck equation or directly by either solving analytically or implementing it numerically from the Langevin equations. The analytical and numerical results coincide. Our theoretical model can help understand the locomotion of metameric animals and instruct the design of metameric robots.

cond-mat.soft↗

arXiv2020

Ordering of adsorbed rigid rods mediated by the Boussinesq interaction on a soft substrate

Orientational ordering driven by mechanical distortion of soft substrates plays a major role in material transformation processes such as elastocapillarity and surface anchoring. We present a theoretical model of the orientational response of anisotropic rods deposited onto a surface of a soft, elastic substrate of finite thickness. We show that anisotropic rods exhibit a continuous isotropic-nematic phase transition, driven by orientational interactions between surface deposited rods. This interaction is mediated by the deformation of the underlying elastic substrate, and is quantified by the Boussinesq solution adapted to the case of slender, surface deposited rods. From the microscopic rod-rod interactions we derive the appropriate Maier-Saupe mean-field description, which includes the Boussinesq elastic free-energy contribution due to the substrate elasticity, derive the conditions for the existence of a continuous orientational ordering transition and discuss the implication of results in the soft (bio) systems context.

cond-mat.soft↗

arXiv2017

Demixing of active particles in the presence of external fields

Active systems are inherently out of equilibrium, as they collect energy from their surroundings and transform it into directed motion. A recent theoretical study suggests that binary mixtures of active particles with distinct effective diffusion coefficients exhibit dynamical demixing above a threshold ratio of the diffusion coefficients. Here, we show that this threshold may be reduced drastically in the presence of external fields. We investigate the demixing as a function of the ratio of the diffusion coefficients and discuss the implications of the results for active systems.

cond-mat.soft↗