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The authors present a comparative analysis of ultraviolet-O3 (UVO) and O2 plasma-based surface activation processes of multiwalled carbon nanotubes (MWCNTs), enabling highly effective functionalization with metal oxide nanocrystals (MONCs). Experimental results from transmission electron microscopy, scanning electron microscopy, x-ray photoelectron spectroscopy, and Raman spectroscopy show that by forming COOH (carboxyl), C-OH (hydroxyl), and C=O (carbonyl) groups on the MWCNT surface that act as active nucleation sites, O2 plasma and UVO-based dry pretreatment techniques greatly enhance the affinity between the MWCNT surface and the functionalizing MONCs. MONCs, such as ZnO and SnO2, deposited by the atomic layer deposition technique, were implemented as the functionalizing material following UVO and O2 plasma activation of MWCNTs. A comparative study on the relative resistance changes of O2 plasma and UVO activated MWCNT functionalized with MONC in the presence of 10 ppm methane (CH4) in air is presented as well.

Air pollution monitoring using mobile ground-based measurement platforms can provide high-quality spatiotemporal air pollution information. As mobile air quality monitoring campaigns extend to entire fleets of vehicles and integrate smaller-scale air quality sensors, it is important to address the need to assess these measurements in a scalable manner. We explore the collocation-based evaluation of air quality measurements in a mobile platform using fixed regulatory sites as a reference. We compare two approaches: a standard collocation assessment technique, in which the mobile platform is parked near the fixed regulatory site for a period of time, and an expanded approach, which uses measurements while the mobile platform is in motion in the general vicinity of the fixed regulatory site. Based on the availability of fixed-reference-site data, we focus on three pollutants (ozone, nitrogen dioxide, and nitric oxide) with distinct atmospheric lifetimes and behaviors. We compare measurements from a mobile laboratory with regulatory site measurements in Denver, CO, USA, and in the San Francisco Bay Area, CA, USA. Our 1-month Denver dataset includes both parked collocation periods near the fixed regulatory sites and general driving patterns around the sites, allowing a direct comparison of the parked and mobile collocation techniques on the same dataset. We show that the mobile collocation approach produces similar performance statistics, including coefficients of determination and mean bias errors, to the standard parked collocation technique. This is particularly true when the comparisons are restricted to specific road types, with residential streets showing the closest agreement and highways showing the largest differences. We extend our analysis to a larger (yearlong) dataset in California, where we explore the relationships between the mobile measurements and the fixed reference sites on a larger scale. We show that using a 40 h running median converges to within ± 4 ppbv of the fixed reference site for nitrogen dioxide and ozone and up to about 8 ppbv for nitric oxide. We propose that this agreement can be leveraged to assess instrument performance over time during large-scale mobile monitoring campaigns. We demonstrate an example of how such relationships can be employed during large-scale monitoring campaigns using small sensors to identify potential measurement biases. [ABSTRACT FROM AUTHOR]

Chemoresistive sensors based on multiwalled carbon nanotubes (MWCNTs) functionalized with SnO2 nanocrystals (NCs) have great potential for detecting trace gases at low concentrations (single ppm levels) at room temperature, because the SnO2 nanocrystals act as active sites for the chemisorption of gas molecules, and carbon nanotubes (CNTs) act as an excellent current carrying platform, allowing the adsorption of gas on SnO2 to modulate the resistance of the CNTs. However, uniform conjugation of SnO2 NCs with MWCNTs is challenging. An effective atomic layer deposition based approach to functionalize the surface of MWCNTs with SnO2 NCs, resulting in a novel CH4 sensor with 10ppm sensitivity, is presented in this paper. Scanning electron microscopy, transmission electron microscopy (TEM), energy dispersive x-ray spectroscopy, and Raman spectroscopy were implemented to study the morphology, elemental composition, and the crystal quality of SnO2 functionalized MWCNTs. High resolution TEM images showed that the crystal quality of the functionalizing SnO2 NCs was of high quality with clear lattice fringes and the dimension almost three times smaller than shown thus far in literature. A lift-off based photolithography technique comprising bilayer photoresists was optimized to fabricate SnO2 functionalized MWCNTs-based chemoresistor sensor, which at room temperature can reliably sense below 10ppm of CH4 in air. Such low level gas sensitivity, with significant reversible relative resistance change, is believed to be the direct result of the successful functionalization of the MWCNT surface by SnO2 NCs.

This paper presents a highly sensitive, energy efficient, and low-cost distributed methane (CH4) sensor system (DMSS) for continuous monitoring, detection, and localization of CH4 leaks in natural gas infrastructure, such as transmission and distribution pipelines, wells, and production pads. The CH4 sensing element, a key component of the DMSS, consists of a metal-oxide nanocrystal functionalized multi-walled carbon nanotube mesh, which, in comparison with the existing literature, shows stronger relative resistance change while interacting with lower parts per million concentration of CH4. A Gaussian plume triangulation algorithm has been developed for the DMSS. Given a geometric model of the surrounding environment, the algorithm can precisely detect and localize a CH4 leak as well as estimate its mass emission rate. A UV-based surface recovery technique making the sensor recover ten times faster than the reported ones is presented for the DMSS. A control algorithm based on the UV-accelerated recovery is developed, which facilitates faster leak detection.

This paper presents a novel atomic layer deposition (ALD) based ZnO functionalization of surface pretreated multiwalled carbon nanotubes (MWCNTs) for highly sensitive methane chemoresistive sensors. The temperature optimization of the ALD process leads to enhanced ZnO nanoparticle functionalization and improvement in their crystalline quality as shown by energy dispersive x-ray and Raman spectroscopy. The behavior of ZnO-MWCNT sensors in presence of methane concentrations down to 2 ppm level has been compared with that of pristine MWCNTs demonstrating that ZnO functionalization is an essential factor behind the highly sensitive chemoresistive nature of the ZnO-MWCNT heterostructures. The sensor is currently being tested under a range of conditions that include potentially interfering gases and changes to relative humidity.

Analog memory presents a promising solution in the face of the growing demand for energy-efficient artificial intelligence (AI) at the edge. In this study, we demonstrate efficient deep neural network transfer learning utilizing hardware and algorithm co-optimization in an analog resistive random-access memory (ReRAM) array. For the first time, we illustrate that in open-loop deep neural network (DNN) transfer learning for image classification tasks, convergence rates can be accelerated by approximately 3.5 times through the utilization of cooptimized analog ReRAM hardware and the hardware-aware Tiki-Taka v2 (TTv2) algorithm. A simulation based on statistical 14 nm CMOS ReRAM array data provides insights into the performance of transfer learning on larger network workloads, exhibiting notable improvement over conventional training with random initialization. This study shows that analog DNN transfer learning using an optimized ReRAM array can achieve faster convergence with a smaller dataset compared to training from scratch, thus augmenting AI capability at the edge. [ABSTRACT FROM AUTHOR]

Results of recent research show that particulate matter (PM) composition and size vary widely with both space and time. Despite the variability in PM characteristics, which are believed to influence human health risks, the observed relative health risk estimates per unit PM mass falls within a narrow range of values. Furthermore, no single chemical species appears to dominate health effects; rather the effects appear to be due to a combination of species. Non-PM factors such as socioeconomic status and lifestyle are also believed to affect the health risk, although accounting for these confounding factors is challenging. Airborne PM is also responsible for a number of effects aside from human health, such as alterations in visibility and climate. Because the PM problem is associated with a range of societal issues such as energy production and economic development, making progress on reducing the effects of PM will require integrated strategies that bring together scientists and decision makers from different disciplines to consider tradeoffs holistically. Copyright © American Association for Aerosol Research.

Air pollution monitoring using mobile ground-based measurement platforms can provide high quality spatiotemporal air pollution information. As mobile air quality monitoring campaigns extend to entire fleets of vehicles and integrate smaller scale air quality sensors, it is important to address the quality assurance needs for validating these measurements. We explore collocation-based evaluation of air quality instruments in a mobile platform against fixed regulatory sites, both when the mobile platform is parked at the fixed regulatory site and when moving at distances of meters to kilometers from the site. We demonstrate agreement within 4 ppbv (for NO2 and O3+NO2) to 10 ppbv (for NO) when using a running median of 40 hourly differences between the moving mobile platform measurements and stationary site measurements. The comparability is strong when only measurements from residential roads are used but are only slightly diminished when all roads except highways are included in the analysis. We present a method for assessing mobile measurements of ozone (O3), nitrogen dioxide (NO2), and odd oxygen (OX = O3 + NO2) on an ongoing basis through comparisons with fixed regulatory sites. [ABSTRACT FROM AUTHOR]

The transient thermal crosstalk between the field-effect transistors (FETs) implemented on a silicon-on-insulator (SOI) substrate is examined. Findings reveal the achievement of a temperature resolution of ~50 mK, a time resolution of 5 ns and a temperature sensitivity of ~0.6 A/K.

The competitiveness of metal-gated (MG) devices is investigated using mixed-mode simulations of inverter delay chains for both low-power and high-power applications. The applications that are suitable for the in-gap MGs and valuable guidance to the industry regarding the range of work functions that would maximize performance for each application are described.

The study stated that a general approach, the EQ approach, to assess the scaling potential of nanoscale Si FETs based on both gate control (electrostatics) and quantum confinement. The report stated that with this EQ approach, the cylindrical wire FET and the planar double-gate MOSFET have approximately equal scaling capability, while the nonplanar wire structures are significantly better where the effective mass in the confinement direction of the planar MOSFET is relatively small.