Channel-Width Dependent Enhancement in Nanoscale Field Effect Transistor

We report the observation of channel-width dependent enhancement in nanoscale field effect transistors containing lithographically-patterned silicon nanowires as the conduction channel. These devices behave as conventional metal-oxide-semiconductor field-effect transistors in reverse source drain bias. Reduction of nanowire width below 200 nm leads to dramatic change in the threshold voltage. Due to increased surface-to-volume ratio, these devices show higher transconductance per unit width at smaller width. Our devices with nanoscale channel width demonstrate extreme sensitivity to surface field profile, and therefore can be used as logic elements in computation and as ultrasensitive sensors of surface-charge in chemical and biological species.Comment: 5 pages, 4 figures, two-column format. Related papers can be found at http://nano.bu.ed

Predicting Changes of Rainfall Erosivity and Hillslope Erosion Risk Across Greater Sydney Region, Australia

Rainfall changes have significant effect on rainfall erosivity and hillslope erosion, but the magnitude of the impact is not well quantified because of the lack of high resolution rainfall data. Recently, the 2-km rainfall projections from regional climate models have become available for the Greater Sydney Region (GSR) at daily time step for the current (1990-2009) and future (2040-2059) periods. These climate projections allow predicting of rainfall erosivity changes and the associated hillslope erosion risk for climate change assessment and mitigation. In this study, we developed a daily rainfall erosivity model for GSR to predict rainfall erosivity from the current and future daily rainfall data. We produced time-series hillslope erosion risk maps using the revised universal soil loss equations on monthly and annual bases for the two contrasting periods. These products were spatially interpolated to a fine resolution (100 m) useful for climate impact assessment and erosion risk mitigation. The spatial variation was assessed based on the state plan regions and the temporal variation on monthly and annual bases. These processes have been implemented in a geographic information system so that they are automated, fast, and repeatable. Our prediction shows relatively good correlation with point-based Pluviograph calculation on rainfall erosivity and the previous study (both R2 and Ec \u3e 0.70). The results indicate that hillslope erosion risk is likely to increase 10-60% in the GSR within the next 50 years, and changes are greater in the coastal and the Blue Mountains, particularly in late summer (January and February). The methodology developed in this study is being extended to south-east Australia

Computation of Wind Wave Flow Field with Moving Boundary Based on Image Processing

Based on image processing technology, a solution to the interference of moving boundary in wind wave flow field calculation is proposed. Invariant background is extracted from image sequence by means of the minimum method, and the differences between image sequence and invariant background image are used to remove the invariant background of image sequence. The image segmentation threshold is determined based on maximum interclass variance method, and the scatter interference is removed by image filtering and morphological technology, to obtain the target image. Then the flow field is calculated by PIV technology and the results of the flow field before and after the boundary treatment are compared. The experimental results show that the accuracy and speed of flow field calculation are greatly improved after removal of moving boundary disturbance, and the results of wind wave flow field calculation accord with the motion mechanism of hydraulic wind wave

Silicon-based nanochannel glucose sensor

Silicon nanochannel biological field effect transistors have been developed for glucose detection. The device is nanofabricated from a silicon-on-insulator wafer with a top-down approach and surface functionalized with glucose oxidase. The differential conductance of silicon nanowires, tuned with source-drain bias voltage, is demonstrated to be sensitive to the biocatalyzed oxidation of glucose. The glucose biosensor response is linear in the 0.5-8 mM concentration range with 3-5 min response time. This silicon nanochannel-based glucose biosensor technology offers the possibility of high density, high quality glucose biosensor integration with silicon-based circuitry.Comment: 3 pages, 3 figures, two-column format. Related papers can be found at http://nano.bu.ed

Nanoscale field effect transistor for biomolecular signal amplification

We report amplification of biomolecular recognition signal in lithographically defined silicon nanochannel devices. The devices are configured as field effect transistors (FET) in the reversed source-drain bias region. The measurement of the differential conductance of the nanowire channels in the FET allows sensitive detection of changes in the surface potential due to biomolecular binding. Narrower silicon channels demonstrate higher sensitivity to binding due to increased surface-to-volume ratio. The operation of the device in the negative source-drain region demonstrates signal amplification. The equivalence between protein binding and change in the surface potential is described

Field Effect Transistor Nanosensor for Breast Cancer Diagnostics

Silicon nanochannel field effect transistor (FET) biosensors are one of the most promising technologies in the development of highly sensitive and label-free analyte detection for cancer diagnostics. With their exceptional electrical properties and small dimensions, silicon nanochannels are ideally suited for extraordinarily high sensitivity. In fact, the high surface-to-volume ratios of these systems make single molecule detection possible. Further, FET biosensors offer the benefits of high speed, low cost, and high yield manufacturing, without sacrificing the sensitivity typical for traditional optical methods in diagnostics. Top down manufacturing methods leverage advantages in Complementary Metal Oxide Semiconductor (CMOS) technologies, making richly multiplexed sensor arrays a reality. Here, we discuss the fabrication and use of silicon nanochannel FET devices as biosensors for breast cancer diagnosis and monitoring

TQ-Net: Mixed Contrastive Representation Learning For Heterogeneous Test Questions

Recently, more and more people study online for the convenience of access to massive learning materials (e.g. test questions/notes), thus accurately understanding learning materials became a crucial issue, which is essential for many educational applications. Previous studies focus on using language models to represent the question data. However, test questions (TQ) are usually heterogeneous and multi-modal, e.g., some of them may only contain text, while others half contain images with information beyond their literal description. In this context, both supervised and unsupervised methods are difficult to learn a fused representation of questions. Meanwhile, this problem cannot be solved by conventional methods such as image caption, as the images may contain information complementary rather than duplicate to the text. In this paper, we first improve previous text-only representation with a two-stage unsupervised instance level contrastive based pre-training method (MCL: Mixture Unsupervised Contrastive Learning). Then, TQ-Net was proposed to fuse the content of images to the representation of heterogeneous data. Finally, supervised contrastive learning was conducted on relevance prediction-related downstream tasks, which helped the model to learn the representation of questions effectively. We conducted extensive experiments on question-based tasks on large-scale, real-world datasets, which demonstrated the effectiveness of TQ-Net and improve the precision of downstream applications (e.g. similar questions +2.02% and knowledge point prediction +7.20%). Our code will be available, and we will open-source a subset of our data to promote the development of relative studies.Comment: This paper has been accepted for the AAAI2023 AI4Edu Worksho

Multifunctional photonic integrated circuit for diverse microwave signal generation, transmission and processing

Microwave photonics (MWP) studies the interaction between microwave and optical waves for the generation, transmission and processing of microwave signals (i.e., three key domains), taking advantages of broad bandwidth and low loss offered by modern photonics. Integrated MWP using photonic integrated circuits (PICs) can reach a compact, reliable and green implementation. Most PICs, however, are recently developed to perform one or more functions restricted inside a single domain. In this paper, as highly desired, a multifunctional PIC is proposed to cover the three key domains. The PIC is fabricated on InP platform by monolithically integrating four laser diodes and two modulators. Using the multifunctional PIC, seven fundamental functions across microwave signal generation, transmission and processing are demonstrated experimentally. Outdoor field trials for electromagnetic environment surveillance along an in-service high-speed railway are also performed. The success to such a PIC marks a key step forward for practical and massive MWP implementations.Comment: 17 page

Creating New Near-Surface Air Temperature Datasets to Understand Elevation-Dependent Warming in the Tibetan Plateau

The Tibetan Plateau has been undergoing accelerated warming over recent decades, and is considered an indicator for broader global warming phenomena. However, our understanding of warming rates with elevation in complex mountain regions is incomplete. The most serious concern is the lack of high-quality near-surface air temperature (Tair) datasets in these areas. To address this knowledge gap, we developed an automated mapping framework for the estimation of seamless daily minimum and maximum Land Surface Temperatures (LSTs) for the Tibetan Plateau from the existing MODIS LST products for a long period of time (i.e., 2002–present). Specific machine learning methods were developed and linked with target-oriented validation and then applied to convert LST to Tair. Spatial variables in retrieving Tair, such as solar radiation and vegetation indices, were used in estimation of Tair, whereas MODIS LST products were mainly focused on temporal variation in surface air temperature. We validated our process using independent Tair products, revealing more reliable estimates on Tair; the R2 and RMSE at monthly scales generally fell in the range of 0.9–0.95 and 1–2 °C. Using these continuous and consistent Tair datasets, we found temperature increases in the elevation range between 2000–3000 m and 4000–5000 m, whereas the elevation interval at 6000–7000 m exhibits a cooling trend. The developed datasets, findings and methodology contribute to global studies on accelerated warming