Scanning Tunneling Microscopy Studies of an Electron Doped High-T<subscript>c</subscript> Superconductor Pr<subscript>0.88</subscript>LaCe<subscript>0.12</subscript>CuO<subscript>4-&#948;</subscript>

Thesis advisor: Vidya MadhavanIt has been more than two decades since the first high temperature superconductor was discovered. In this time there has been tremendous progress in understanding these materials both theoretically and experimentally. Some important questions however remain to be answered; one of them is the temperature dependence of the superconducting gap which is in turn tied to question of the origin of the pseudogap and its connection with superconductivity. In this thesis, we present detailed Scanning Tunneling Microscopy (STM) spectroscopic studies of an electron doped superconductor, Pr0.88LaCe0.12CuO4-&#948; (PLCCO). The electron doped compounds form an interesting venue for STM studies for many reasons. In the hole-doped materials, especially in the underdoped side of the phase diagram, there is mounting evidence of a second gap that survives to high temperatures (high temperature pseudogap) that may have a different origin from superconductivity. This complicates studies of the temperature dependence of the superconducting gap in these materials. In PLCCO however, there is little evidence for a high temperature pseudogap potentially allowing us to address the question of the temperature evolution of the superconducting gap without the complication of a second gap. Secondly, the low Tc of the optimally doped materials makes it easily accessible to temperature dependent STM studies. Finally, while hole-doped materials have been extensively studied by scanning tunneling microscopy (STM), there have been no detailed STM spectroscopic studies on the electron doped compounds. In the first part of the thesis, we investigate the effect of temperature on the superconducting gap of optimally doped PLCCO with Tc = 24K. STM spectroscopy data is analyzed to obtain the gap as a function of temperature from 5K to 35K. The gap is parameterized with a d-wave form and the STM spectra are fit at each temperature to extract the gap value. A plot of this gap value as a function of temperature shows clear deviations from what is expected from BCS theory. We find that similar to the hole-doped superconductors a fraction of the surface still shows a gap above Tc. The implications of our finding to the pseudogap phase are discussed. In the second part of the thesis, STM spectra are analyzed to determine the effect of impurities or vacancies on the local density of states. Electron doped superconductors require a post-annealing process to induce superconductivity. It is claimed that Cu vacancies in the CuO2 planes which suppress superconductivity are healed by this process. This implies that for the same doping, a sample with higher Tc should have fewer impurities compared to a sample with lower Tc. We studied two PLCCO samples with 12% Ce doping; one with higher Tc (24K) and the other with lower Tc (21K). Through quasiparticle scattering study we find that there are more impurities in 21K samples than 24K sample, consistent with the picture of Cu vacancies in as grown samples. Finally, we present a discussion of the bosonic modes observed in the STM spectra and their connection to the spin excitations measured by neutron scattering.Thesis (PhD) — Boston College, 2009.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Physics

Next-Generation IoT Networks: Integrated Sensing Communication and Computation

peer reviewedTo enable the exponential expansion of Internet of Things (IoT) applications, IoT devices must gather and transmit massive amounts of data to the server for further processing. By employing the same signals for both radar sensing and data transmission, the integrated sensing and communication (ISAC) approach provides simultaneous data gathering and delivery in the physical layer. Over-the-air computation (AirComp), which leverages the analog-wave addition property in multi-access channels, is a communication method that also supports function computation. In order to leverage the individual benefits of ISAC and AirComp, this work focuses on Integrated Sensing Communication and Computation (ISCCO) framework for the IoT network. Since the IoT sensors are small size low cost devices and each is equipped with single antenna, and hence to make the processing of received echo simple this work assume that the waveform transmitted by each sensor is orthogonal to each other. Furthermore, joint optimal power allocation for each sensor in the IoT network and the combining vector at the EC is designed such that the signal-to-noise (SNR) ratio at the EC is maximized. However, the design challenge lies in the non-convex joint optimal power allocation for each IoT device and the combining vector at the server. To address this, an iterative algorithm is proposed which provides closed-form solution for each quantity in each iteration. Results show that the proposed optimal power allocation and orthogonal waveform design scheme outperforms the equal power allocation-based design.9. Industry, innovation and infrastructur

Distributed Sensing and Centric Computing via FMCW Waveform in Wireless Sensor Network

peer reviewe

Electron-Spin Excitation Coupling in an Electron Doped Copper Oxide Superconductor

High-temperature (high-Tc) superconductivity in the copper oxides arises from electron or hole doping of their antiferromagnetic (AF) insulating parent compounds. The evolution of the AF phase with doping and its spatial coexistence with superconductivity are governed by the nature of charge and spin correlations and provide clues to the mechanism of high-Tc superconductivity. Here we use a combined neutron scattering and scanning tunneling spectroscopy (STS) to study the Tc evolution of electron-doped superconducting Pr0.88LaCe0.12CuO4-delta obtained through the oxygen annealing process. We find that spin excitations detected by neutron scattering have two distinct modes that evolve with Tc in a remarkably similar fashion to the electron tunneling modes in STS. These results demonstrate that antiferromagnetism and superconductivity compete locally and coexist spatially on nanometer length scales, and the dominant electron-boson coupling at low energies originates from the electron-spin excitations.Comment: 30 pages, 12 figures, supplementary information include

Bio-nanotechnology application in wastewater treatment

The nanoparticles have received high interest in the field of medicine and water purification, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modification of nanoparticles and their properties were also discussed

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

CoFAR Clutter Channel Estimation via Sparse Bayesian Learning

peer reviewedA cognitive fully adaptive radar (CoFAR) alters its behavior autonomously to accomplish desired tasks. The knowledge of the target environment is essential to the efficient operation of CoFAR. In this work, we consider the enhanced environment sensing aspect and study the problem of clutter channel impulse response (CIR) estimation in CoFAR. Using the high-fidelity modeling and simulation tool RFView, we show that the clutter CIR is sparse. Subsequently, we propose a sparse Bayesian learning (SBL) framework for estimating the underlying sparse clutter CIR, which does not require the a priori knowledge of the unknown clutter CIR's sparsity profile. Further, we derive the Bayesian Cramér-Rao bound (BCRB) for the proposed method and show the effectiveness of the proposed SBL-based clutter channel estimation method by comparing its performance with the derived BCRB.European Office of Aerospace Research & Development, part of the US Airforce Office of Scientific Research9. Industry, innovation and infrastructur

Nighttime particle growth observed during spring in New Delhi: Evidences for the aqueous phase oxidation of SO2

Aerosol size distributions were measured using a scanning mobility particle sizer (SMPS), and also PM1 (particulate matter <= 1 mu m in aerodynamic diameter) samples were collected in parallel at a representative site in New Delhi during spring in 2013 and 2014. Based on the temporal variation of particle count mean diameter (CMD), sampling periods are characterized as growth events and non-growth events. Particle size distribution measurements suggest that some consecutive nights experienced unique nighttime subsequent growth of particles, which sustained for a longer period. Average particle growth rate measured during growth events was 5.64 +/- 3.03 nm h(-1). Atmospheric trace gas concentrations and meteorological data show that these growth events (nighttime) are influenced by higher concentrations of gases, e.g., NO2 (56.5 +/- 29.7 mu g m(-3)), SO2 (9.34 +/- 1.14 mu g m(-3)) and RH (45.7 +/- 9.5%) than those of non-growth events (daytime) (37.9 +/- 18.6 mu g m(-3), 7.19 +/- 2.08 mu g m(-3) and 37.7 +/- 6.9%, respectively). Further, analysis of PM1 samples collected during the study period shows that the particulate water-soluble organic carbon (WSOC) (12.7 +/- 4.1 mu g m(-3)), NH4+ (9.4 +/- 3.2 mu g m(-3)), SO42- (2.03 +/- 0.70 mu g m(-3)), K+ (1.06 +/- 0.40 mu g m(-3)), and NO2- + NO3- (0.59 +/- 0.36 mu g m(-3)) are the major contributors of particulate mass, wherein NH4+, SO42-, K+, NO2- + NO3- mass concentrations were higher during growth events. Correlation study shows that nighttime aerosol composition during growth (in sub-micron range) events are more enriched by inorganic species (i.e., NH4NO3, (NH4)(2)SO4 and H2SO4 vapors) as compared to organics (i.e., WSOC, does not show much difference in growth events and non events). Our results suggest that nighttime sulfate formation at the site is mostly mediated by high NO2 and NH3 at elevated RH. For the formation of sulfate and other inorganic species, a nighttime atmospheric chemistry is proposed, which is linked to particle growth. Growth events observed typically in nighttime have both biomass burning and anthropogenic influences as indicated by high concentrations of WSOC, K+ and black carbon in PM1 and carbon monoxide in gas phase