A gas sensor based on the suspended carbon nanomesh functionalized with metal oxide nanowires and their junctions

Department of Mechanical EngineeringThis study reports the development of a high performance gas sensor platform based on the suspended carbon nanomesh (line width ~300nm, thickness ~ 400nm) functionalized with 1-D metal oxide nanowires (NWs). Thanks to the unique nanomesh structure, 1-D metal oxide NWs grown from each line of the mesh cross each other making junctions. These junctions provide an additional gas sensing mechanism to the sensor result in higher gas response and wider sensing range. In this research, the sensor was constructed by integrating ZnO nanowires (diameter ~ 30 - 70nm, length ~3 ??m), and high sensitivity (200.59ppb-1) and wide detection range (50ppb ??? 5ppm) were confirmed to NO2 gas. Furthermore, the suspended carbon nanomesh, that is backbone of the sensor platform, provides enhanced mass transfer, high surface to volume ratio and elimination of noise from the bottom substrate. Thanks to these properties, fast response and recovery and reliability of the sensor were also confirmed. The fabrication of this sensor platform is wafer-level fabrication process including carbon-microelectromechanical systems(C-MEMS) and hydrothermal method making proposed sensor platform cost-effective. Most of all, this study is about gas sensor platform, so that it can be a cornerstone of further studies simply by employing other sensing materials. Thus, the proposed gas sensor that based on the suspended carbon nanomesh functionalized with metal oxide nanowires and their junctions suggests a novel, high-performance, reliable and cost-effective sensor platform.clos

Learning Rotation-Equivariant Features for Visual Correspondence

Extracting discriminative local features that are invariant to imaging variations is an integral part of establishing correspondences between images. In this work, we introduce a self-supervised learning framework to extract discriminative rotation-invariant descriptors using group-equivariant CNNs. Thanks to employing group-equivariant CNNs, our method effectively learns to obtain rotation-equivariant features and their orientations explicitly, without having to perform sophisticated data augmentations. The resultant features and their orientations are further processed by group aligning, a novel invariant mapping technique that shifts the group-equivariant features by their orientations along the group dimension. Our group aligning technique achieves rotation-invariance without any collapse of the group dimension and thus eschews loss of discriminability. The proposed method is trained end-to-end in a self-supervised manner, where we use an orientation alignment loss for the orientation estimation and a contrastive descriptor loss for robust local descriptors to geometric/photometric variations. Our method demonstrates state-of-the-art matching accuracy among existing rotation-invariant descriptors under varying rotation and also shows competitive results when transferred to the task of keypoint matching and camera pose estimation.Comment: Accepted to CVPR 2023, Project webpage at http://cvlab.postech.ac.kr/research/REL

A Three-Step Resolution-Reconfigurable Hazardous Multi-Gas Sensor Interface for Wireless Air-Quality Monitoring Applications

This paper presents a resolution-reconfigurable wide-range resistive sensor readout interface for wireless multi-gas monitoring applications that displays results on a smartphone. Three types of sensing resolutions were selected to minimize processing power consumption, and a dual-mode front-end structure was proposed to support the detection of a variety of hazardous gases with wide range of characteristic resistance. The readout integrated circuit (ROIC) was fabricated in a 0.18 ??m CMOS process to provide three reconfigurable data conversions that correspond to a low-power resistance-to-digital converter (RDC), a 12-bit successive approximation register (SAR) analog-to-digital converter (ADC), and a 16-bit delta-sigma modulator. For functional feasibility, a wireless sensor system prototype that included in-house microelectromechanical (MEMS) sensing devices and commercial device products was manufactured and experimentally verified to detect a variety of hazardous gases

Development of a Novel Gas-Sensing Platform Based on a Network of Metal Oxide Nanowire Junctions Formed on a Suspended Carbon Nanomesh Backbone

Junction networks made of longitudinally connected metal oxide nanowires (MOx NWs) have been widely utilized in resistive-type gas sensors because the potential barrier at the NW junctions leads to improved gas sensing performances. However, conventional MOx-NW-based gas sensors exhibit limited gas access to the sensing sites and reduced utilization of the entire NW surfaces because the NW networks are grown on the substrate. This study presents a novel gas sensor platform facilitating the formation of ZnO NW junction networks in a suspended architecture by growing ZnO NWs radially on a suspended carbon mesh backbone consisting of sub-micrometer-sized wires. NW networks were densely formed in the lateral and longitudinal directions of the ZnO NWs, forming additional longitudinally connected junctions in the voids of the carbon mesh. Therefore, target gases could efficiently access the sensing sites, including the junctions and the entire surface of the ZnO NWs. Thus, the present sensor, based on a suspended network of longitudinally connected NW junctions, exhibited enhanced gas response, sensitivity, and lower limit of detection compared to sensors consisting of only laterally connected NWs. In addition, complete sensor structures consisting of a suspended carbon mesh backbone and ZnO NWs could be prepared using only batch fabrication processes such as carbon microelectromechanical systems and hydrothermal synthesis, allowing cost-effective sensor fabrication

Increased cerebral blood volume in small arterial vessels is a correlate of amyloid-β-related cognitive decline

The protracted accumulation of amyloid-β (Aβ) is a major pathologic hallmark of Alzheimer's disease and may trigger secondary pathological processes that include neurovascular damage. This study was aimed at investigating long-term effects of Aβ burden on cerebral blood volume of arterioles and pial arteries (CBVa), possibly present before manifestation of dementia. Aβ burden was assessed by 11C Pittsburgh compound-B positron emission tomography in 22 controls and 18 persons with mild cognitive impairment (MCI), [ages: 75(±6) years]. After 2 years, inflow-based vascular space occupancy at ultra-high field strength of 7-Tesla was administered for measuring CBVa, and neuropsychological testing for cognitive decline. Crushing gradients were incorporated during MR-imaging to suppress signals from fast-flowing blood in large arteries, and thereby sensitize inflow-based vascular space occupancy to CBVa in pial arteries and arterioles. CBVa was significantly elevated in MCI compared to cognitively normal controls and regional CBVa related to local Aβ deposition. For both MCI and controls, Aβ burden and follow-up CBVa in several brain regions synergistically predicted cognitive decline over 2 years. Orbitofrontal CBVa was positively associated with apolipoprotein E e4 carrier status. Increased CBVa may reflect long-term effects of region-specific pathology associated with Aβ deposition. Additional studies are needed to clarify the role of the arteriolar system and the potential of CBVa as a biomarker for Aβ-related vascular downstream pathology

Runoff Reduction Effects at Installation of LID Facilities under Different Climate Change Scenarios

In order to prepare for floods and droughts that occur as a result of climate change, various studies in water-related fields are being carried out in various countries around the world. Among them, special attention is being paid to the low-impact development (LID) technique. This study measured the annual maximum daily rainfall data from 2019 to 2100 by climate change scenario, which is the annual maximum daily rainfall series observed for rainfall stations, and tested the hydrological data using statistical analysis. After determining whether the data could be analyzed, the probability distribution was selected, and the parameters of the selected probability distribution were calculated using the L-moment method for each rainfall station. The probabilities of rainfall data were derived using GEV distribution, and the United States Environmental Protection Agency Storm Water Management Model (SWMM), a runoff simulation program, was used to compare and analyze the runoff reduction rate before and after the installation of a permeable pavement as an LID facility. The results of the analysis showed that representative concentration pathway (RCP) 4.5 and RCP 8.5 had the effect of reducing the runoff for more than 100 years at a 30% reduction rate compared with before installation

Heterogeneous Catalytic H2S Oxidation within Supercritical CO2 for a New Sulfur Recovery Process

Many natural gas sources can have small amounts of acid gases (H2S and CO2). These acid gases are removed from the natural gas for the consumers due to toxicity and low heating value. Conventionally, acid gas is removed by absorption into aqueous amine solutions. This separated acid gas can then be injected into reservoirs for sequestration or can be further processed to convert the H2S to S8 by sulfur recovery. For low-quality acid gases (< 1% H2S in CO2), available methods to remove H2S results in waste rather than marketable sulfur. The remaining CO2 is at near atmospheric pressure, often being released to the environment due to high recompression costs. In this thesis, an alternative sulfur recovery process is investigated to produce marketable sulfur and high-pressure CO2 using post cryogenic separation of low-quality acid gases. Cryogenic distillation for acid gas separation is beneficial, resulting in a high-pressure liquid form of acid gas that does not require recompression. However, currently available low-pressure methods to convert H2S to S8 do not take the advantage of this high-pressure. Heterogeneous catalysis was utilized to convert H2S to S8 within the high-pressure CO2 in this thesis. For the high-pressure sulfur recovery process to be viable, several studies were completed in order to provide the best conditions to carry out the heterogeneous catalysis in high-pressure CO2. Sulfur solubility within high-pressure CO2 was initially studied to define the process conditions to maintain a single-phase product and subsequent separation of produced sulfur and CO2. The sulfur solubility study also allowed for the modelling of the sulfur fugacity coefficient within high-pressure CO2, which was utilized in a high-pressure Gibbs Free Energy Minimization routine to calculate the theoretical equilibrium conversion limit of H2S to S8. Heterogeneous H2S oxidation catalyses were experimentally carried out to verify calculated high-pressure thermodynamic conversion limits by the Gibbs Free Energy Minimization routine. Kinetic limitations were found at lower temperatures and higher pressures in pursuit of improving the thermodynamic conversion limit. The kinetics of the high-pressure heterogeneous H2S oxidation catalysis were studied to model the kinetic limitations of the reaction within the high-pressure CO2. The three models developed allow for high-pressure calculations of S8/CO2 solubility conditions, thermodynamic H2S equilibrium conversion limits, and minimum residence times required for the equilibrium conversion limits to establish. These models therefore enable practical industrial condition optimization to carry out the heterogeneous catalytic oxidation of H2S within high-pressure CO2