Aerosol Route Synthesis and Applications of Doped Nanostructured Materials

Nanotechnology presents an attractive opportunity to address various challenges in air and water purification, energy, and other environment issues. Thus, the development of new nanoscale materials in low-cost scalable synthesis processes is important. Furthermore, the ability to independently manipulate the material properties as well as characterize the material at different steps along the synthesis route will aide in product optimization. In addition, to ensure safe and sustainable development of nanotechnology applications, potential impacts need to be evaluated. In this study, nanomaterial synthesis in a single-step gas phase reactor to continuously produce doped metal oxides was demonstrated. Copper-doped TiO2 nanomaterial properties: composition, size, and crystal phase) were independently controlled based on nanoparticle formation and growth mechanisms dictated by process control parameters. Copper dopant found to significantly affect TiO2 properties such as particle size, crystal phase, stability in the suspension, and absorption spectrum: shift from UV to visible light absorption). The in-situ charge distribution characterization of the synthesized nanomaterials was carried out by integrating a tandem differential mobility analyzer: TDMA) set up with the flame reactor synthesis system. Both singly- and doubly- charged nanoparticles were measured, with the charged fractions dependent on particle mobility and dopant concentration. A theoretical calculation was conducted to evaluate the relative importance of the two charging mechanisms, diffusion and thermo-ionization, in the flame. Nanoparticle exposure characterization was conducted during synthesis as a function of operating condition, product recovery and handling technique, and during maintenance of the reactors. Strategies were then indentified to minimize the exposure risk. The nanoparticle exposure potential varied depending on the operating conditions such as precursor feed rate, working conditions of the fume hood, ventilation system, and distance from the reactors. Nanoparticle exposure varied during product recovery and handling depending on the quantity of nanomaterial handled. Most nanomaterial applications require nanomaterials to be in solution. Thus, the role of nanomaterial physio-chemical properties: size, crystal phase, dopant types and concentrations) on dispersion properties was investigated based on hydrodynamic size and surface charge. Dopant type and concentration were found to significantly affect iso-electric point: IEP)-shifting the IEP to a high or lower pH value compared to pristine TiO2 based on the oxidation state of the dopant. The microbial inactivation effectiveness of as-synthesized nanomaterials was investigated under different light irradiation conditions. Microbial inactivation was found to strongly depend on the light irradiation condition as well as on material properties such chemical composition, crystal phase, and particle size. The potential interaction mechanisms of copper-doped TiO2 nanomaterial with microbes were also explored. The studies conducted as part of this dissertation addressed issues in nanomaterial synthesis, characterization and their potential environmental applications

Singlet-Doublet Self-interacting Dark Matter and Radiative Neutrino Mass

Self-interacting dark matter (SIDM) with a light mediator is a promising scenario to alleviate the small-scale problems of the cold dark matter paradigm while being consistent with the latter at large scales, as suggested by astrophysical observations. This, however, leads to an under-abundant SIDM relic due to large annihilation rates into mediator particles, often requiring an extension of the simplest thermal or non-thermal relic generation mechanism. In this work, we consider a singlet-doublet fermion dark matter scenario where the singlet fermion with a light scalar mediator gives rise to the velocity-dependent dark matter self-interaction through a Yukawa type attractive potential. The doublet fermion, by virtue of its tiny mixing with the singlet, can be long-lived and can provide a non-thermal contribution to the singlet relic at late epochs, filling the deficit in the thermal relic of singlet SIDM. The light scalar mediator, due to its mixing with the standard model Higgs, paves the path for detecting such SIDM at terrestrial laboratories leading to constraints on model parameters from CRESST-III and XENON1T experiments. Enlarging the dark sector particles by two more singlet fermions and one scalar doublet, all odd under an unbroken $\mathcal{Z}_2$ symmetry can also explain non-zero neutrino mass in scotogenic fashion.Comment: 17 pages, 16 captioned figures, Version accepted for publication in PR

Majorana Dark Matter and Neutrino mass in a singlet-doublet extension of the Standard Model

A minimal extension of the Standard Model (SM) by a vector-like fermion doublet and three right handed (RH) singlet neutrinos is proposed in order to explain dark matter and tiny neutrino mass simultaneously. The DM arises as a mixture of the neutral component of the fermion doublet and one of the RH neutrinos, both assumed to be odd under an imposed $\mathcal{Z}_2$ symmetry. Being Majorana in nature, the DM escapes from $Z$-mediated direct search constraints to mark a significant difference from singlet-doublet Dirac DM. The other two $\mathcal{Z}_2$ even heavy RH neutrinos give rise masses and mixing of light neutrinos via Type-I Seesaw mechanism. Relic density and direct search allowed parameter space for the model is investigated through detailed numerical scan.Comment: DAE-BRNS-HEP symposium 2020 Procceding

Mechanistic Understanding of Stability and Photocatalytic Efficiency of Titanium Dioxide Nanomaterials in Aquatic Media: A Sol-Gel Approach

Titanium dioxide (TiO2) nanoparticles enhance the intrinsic value of commercial products like various cosmetics, paints, self-cleaning products, etc. Several research on the fabrication of TiO2, stabilization of TiO2 to retain its nanometric scale and increasing the inherent property of the material (i.e., photocatalytic) is ongoing for the last few decades. Still, the synthesis of highly efficient, stable, reproducible and cost-effective TiO2 nanoparticles remains a grand challenge for the researchers and scientific community. Further research is needed to develop an in-depth understanding of synthesis, aggregation kinetics and efficiency to improve the performance of TiO2 nanomaterial for the degradation of persistent organic pollutants (POPs). In this book chapter, we have summarized the synthesis process using the sol-gel pathway followed by its stability behavior and photocatalytic activity in the aqueous solutions. This study also highlighted the effects of various process variables such as pH, catalyst concentration, inorganic species etc. in the photocatalytic performance of TiO2 nanoparticles. Finally, we have reviewed various strategies that have been performed for increasing the photocatalytic efficiency of TiO2 by overcoming its limitations

FOHC: Firefly Optimizer Enabled Hybrid approach for Cancer Classification

Early detection and prediction of cancer, a group of chronic diseases responsible for a large number of deaths each year and a serious public health hazard, can lead to more effective treatment at an earlier stage in the disease's progression. In the current era, machine learning (ML) has widely been used to develop predictive models for incurable diseases such as cancer, heart disease, and diabetes, among others, taking into account both existing datasets and personally collected datasets, more research is still being conducted in this area. Using recursive feature elimination (RFE), principal component analysis (PCA), the Firefly Algorithm (FA), and a support vector machine (SVM) classifier, this study proposed a Firefly Optimizer-enabled Hybrid approach for Cancer classification (FOHC). This study considers feature selection and dimensionality reduction techniques RFE and PCA, and FA is used as the optimization algorithm. In the last stage, the SVM is applied to the pre-processed dataset as the classifier. To evaluate the proposed model, empirical analysis has been carried out on three different kinds of cancer disease datasets including Brain, Breast, and Lung cancer obtained from the UCI-ML warehouse. Based on the various performance parameters like accuracy, error rate, precision, recall, f-measure, etc., some experiments are carried out on the Jupyter platform using Python codes. This proposed model, FOHC, surpasses previous methods and other considered state-of-the-art works, with 98.94% accuracy for Breast cancer, 95.58% accuracy for Lung cancer, and 96.34% accuracy for Brain cancer. The outcomes of these experiments represent the effectiveness of the proposed work

Social, economic, and resource predictors of variability in household air pollution from cookstove emissions

We examine if social and economic factors, fuelwood availability, market and media access are associated with owning a modified stove and variation in household emissions from biomass combustion, a significant environmental and health concern in rural India. We analyze cross-sectional household socio-economic data, and PM(2.5) and particulate surface area concentration in household emissions from cookstoves (n = 100). This data set combines household social and economic variables with particle emissions indexes associated with the household stove. The data are from the Foundation for Ecological Society, India, from a field study of household emissions. In our analysis, we find that less access to ready and free fuelwood and higher wealth are associated with owning a replacement/modified stove. We also find that additional kitchen ventilation is associated with a 12% reduction in particulate emissions concentration (p<0.05), after we account for the type of stove used. We did not find a significant association between replacement/modified stove on household emissions when controlling for additional ventilation. Higher wealth and education are associated with having additional ventilation. Social caste, market and media access did not have any effect on the presence of replacement or modified stoves or additional ventilation. While the data available to us does not allow an examination of direct health outcomes from emissions variations, adverse environmental and health impacts of toxic household emissions are well established elsewhere in the literature. The value of this study is in its further examination of the role of social and economic factors and available fuelwood from commons in type of stove use, and additional ventilation, and their effect on household emissions. These associations are important since the two direct routes to improving household air quality among the poor are stove type and better ventilation

Diagnostic yield of cartridge based nucleic acid amplification test in Mycobacterium tuberculosis in a tertiary care medical college and hospital of Southern Odisha, India

Background: Tuberculosis is the ninth leading cause of death worldwide. India contributes to about one fifth of global TB burden. It is very important to diagnose early and treat tuberculosis to cut down transmission of tuberculosis.Methods: Author conducted a retrospective study in Department of Pulmonary Medicine SLN Medical College, Koraput, Odisha to analyze the utility and yield of CBNAAT. Study period was from April 2018 to March 2019. Inclusion criteria was all patients whose samples were subjected to CBNAAT were included in our study.  Sputum samples from pulmonary tuberculosis patients, and extra pulmonary samples (pleural fluid, ascitic fluid, CSF, synovial fluid and gastric lavage etc. were included in our study population. Exclusion criteria was patients who were under anti tubercular therapy for pulmonary, extra pulmonary and MDR TB were excluded from this study. Data were collected from Pulmonary Medicine Department, ART center, DOTS center and CBNAAT center. Total number of samples tested for CBNAAT, different sample collection sites, age and sex distribution of patients, HIV status of all patients, result of smear microscopy for AFB and CBNAAT and Rifampicin resistance status were analyzed.The detail statistical analysis was done in tabulation form.Results: A total of 2621 samples were tested in CBNAAT during the study period. Mean age of the study population was 38.03 years. 1881 tested were negative and 740 samples were positive for CBNAAT. Of these 2621 samples, 2526 were pulmonary samples (sputum, pleural fluid samples) and 95 were extra pulmonary samples. Author found rifampicin resistance rate of 0.54% (4/740)) in pulmonary tuberculosis cases. There was no rifampicin resistance detected in extra pulmonary samples. CBNAAT could identify 536 cases (23.2%) that were smear negative. Author found TB- HIV co-infection rate of 6.22%.Conclusions: CBNAAT is an important diagnostic modality especially in sputum negative patients for early diagnosis and treatment. In our study it detected Mycobacterium tuberculosis in 23.2% of patients with negative smear for microscopy. Rifampicin resistance rate detected was very low compared to other studies

Self-interacting inelastic dark matter in the light of XENON1T excess

We propose a self-interacting inelastic dark matter (DM) scenario as a possible origin of the recently reported excess of electron recoil events by the XENON1T experiment. Two quasidegenerate Majorana fermion DM particles interact within themselves via a light hidden sector massive gauge boson and with the standard model particles via gauge kinetic mixing. We also consider an additional long-lived singlet scalar, which helps in realizing correct dark matter relic abundance via a hybrid setup comprising both freeze-in and freeze-out mechanisms. While being consistent with the required DM phenomenology along with sufficient self-interactions to address the small-scale issues of cold dark matter, the model with GeV-scale DM can explain the XENON1T excess via inelastic down-scattering of the heavier DM component into the lighter one. All these requirements leave a very tiny parameter space, keeping the model very predictive for near-future experiments. © 2021 authors

Muon (g − 2) and XENON1T excess with boosted dark matter in L − L model

Motivated by the growing evidence for lepton flavour universality violation after the first results from Fermilab's muon (g−2) measurement, we revisit one of the most widely studied anomaly free extensions of the standard model namely, gauged Lμ−Lτ model, known to be providing a natural explanation for muon (g−2). We also incorporate the presence of dark matter (DM) in this model in order to explain the recently reported electron recoil excess by the XENON1T collaboration. We show that the same neutral gauge boson responsible for generating the required muon (g−2) can also mediate interactions between electron and dark fermions boosted by dark matter annihilation. The required DM annihilation rate into dark fermion require a hybrid setup of thermal and non-thermal mechanisms to generate DM relic density. The tightly constrained parameter space from all requirements remains sensitive to ongoing and near future experiments, keeping the scenario very predictive.