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Technology Roadmap for Flexible Sensors

ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Optimized Chlorine Bulk Decay Models and a Machine-Learning-Guided Water Quality Responsive Kinetic Model for Residual Chlorine Prediction

SSRN

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SSRN 2023年

作者： Jafari, Iman Luo, Rongmo Lim, Fang Yee Hui, Ng Szu Jiangyong, Hu Department of Civil & Environmental Engineering National University of Singapore 1 Engineering Drive 2 Singapore117576 Singapore Research and Development Department Xylem Water Solutions Singapore Pte Ltd 3A International Business Park Tower B #10-10/18 ICON@IBP Singapore609935 Singapore Department of Industrial Systems Engineering and Management National University of Singapore 1 Engineering Drive 2 Singapore117576 Singapore

The quality of water changes from source to tap, presenting challenges in maintaining consistent water quality across the system. Predicting water quality in distribution systems, including disinfectant residual loss and by-product generation, has been the subject of research since the early 1990s. Although numerous models have been proposed to predict chlorine decay, disputes exist among researchers and experts over the superiority of certain models. Accordingly, this study modified the existing process-based bulk decay models by replacing the initial chlorine concentration parameter with chlorine demand, leading to an improvement in the models' performance. The modification resulted in a 38.03%, 28.02%, 23.11%, and 33.29% average improvement in the First Order Model (FOM), Parallel First Order Model (PFOM), Second Order Model (SOM), and Parallel Second Order Model (PSOM), respectively. The study also introduced an online predictive method based on a machine learning algorithm that predicts the first-order chlorine bulk decay rate by using water quality parameters as inputs. A Gaussian Process Regression model was used to predict the kinetic parameters in FOM, which accurately predicted the test sets for most of the cases. In addition, a new methodology was proposed in this study for predicting residual chlorine in water distribution systems that incorporates the variability of source natural organic matter, operational actions, and water demands. This method seeks to develop high-fidelity and robust water quality predictions that provide operational decision support for optimized distribution system management. In conclusion, this study emphasizes the importance of understanding water quality changes from source to tap and the challenges of maintaining consistent water quality across the system. The study suggests modifying existing models and introducing a novel methodology for predicting residual chlorine in water distribution systems that can improve water qual

关键词： Water quality

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Development of a Hardware-in-the-loop Testbed for Laboratory Performance Verification of Flexible Building Equipment in Typical Commercial Buildings

arXiv

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arXiv 2023年

作者： Chen, Zhelun Lo, L. James Pertzborn, Amanda Grajewski, Gabriel Wen, Jin O'Neill, Zheng Calfa, Caleb Li, Yicheng Bushby, Steven T. Payne, W. Vance Fu, Yangyang Yang, Zhiyao The Department of Civil Architectural & Environmental Engineering Drexel University PhiladelphiaPA United States The Department of Mechanical Engineering Texas A&M University College StationTX United States The Mechanical Systems and Controls Group The HVAC&R Equipment Performance Group The Building Energy and Environment Division of the Engineering Laboratory The National Institute of Standards and Technology GaithersburgMD United States

The goals of reducing energy costs, shifting electricity peaks, increasing the use of renewable energy, and enhancing the stability of the electric grid can be met in part by fully exploiting the energy flexibility potential of buildings and building equipment. The development of strategies that exploit these flexibilities could be facilitated by publicly available high-resolution datasets illustrating how control of HVAC systems in commercial buildings can be used in different climate zones to shape the energy use profile of a building for grid needs. This article presents the development and integration of a Hardware-In-the-Loop Flexible load Testbed (HILFT) that integrates physical HVAC systems with a simulated building model and simulated occupants with the goal of generating datasets to verify load flexibility of typical commercial buildings. Compared to simulation-only experiments, the hardware-in-the-loop approach captures the dynamics of the physical systems while also allowing efficient testing of various boundary conditions. The HILFT integration in this article is achieved through the co-simulation among various software environments including LabVIEW, MATLAB, and EnergyPlus. Although theoretically viable, such integration has encountered many real-world challenges, such as: 1) how to design the overall data infrastructure to ensure effective, robust, and efficient integration;2) how to avoid closed-loop hunting between simulated and emulated variables;3) how to quantify system response times and minimize system delays;and 4) how to assess the overall integration quality. Lessons-learned using the examples of an AHU-VAV system, an air-source heat pump system, and a water-source heat pump system are presented. Copyright © 2023, The Authors. All rights reserved.

关键词： Synthetic apertures

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Stochastic Time-Optimal Trajectory Planning for Connected and Automated Vehicles in Mixed-Traffic Merging Scenarios

arXiv

引用

arXiv 2023年

作者： Le, Viet-Anh Chalaki, Behdad Tzortzoglou, Filippos N. Malikopoulos, Andreas A. The Department of Mechanical Engineering University of Delaware NewarkDE19716 United States The Systems Engineering Cornell University IthacaNY14850 United States Honda Research Institute USA Inc. Ann ArborMI48103 United States The University of Delaware United States The School of Civil and Environmental Engineering Cornell University IthacaNY14850 United States

Addressing safe and efficient interaction between connected and automated vehicles (CAVs) and human-driven vehicles in a mixed-traffic environment has attracted considerable attention. In this paper, we develop a framework for stochastic time-optimal trajectory planning for coordinating multiple CAVs in mixed-traffic merging scenarios. We present a data-driven model, combining Newell’s car-following model with Bayesian linear regression, for efficiently learning the driving behavior of human drivers online. Using the prediction model and uncertainty quantification, a stochastic time-optimal control problem is formulated to find robust trajectories for CAVs. We also integrate a replanning mechanism that determines when deriving new trajectories for CAVs is needed based on the accuracy of the Bayesian linear regression predictions. Finally, we demonstrate the performance of our proposed framework using a realistic simulation environment. Copyright © 2023, The Authors. All rights reserved.

关键词： Trajectories

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Biochar derived from rice husk: Impact on soil enzyme and microbial dynamics, lettuce growth, and toxicity

引用

Chemosphere 2024年 349卷 140868页

作者： Akumuntu, Athanasie Hong, Jin-Kyung Jho, Eun Hea Omidoyin, Kehinde Caleb Park, Seong-Jik Zhang, Qianru Zhao, Xin Department of Agricultural Chemistry Chonnam National University Gwangju61186 Korea Republic of Department of Environmental and Energy Engineering Yonsei University Wonju26493 Korea Republic of Department of Agricultural and Biological Chemistry Chonnam National University Gwangju61186 Korea Republic of Department of Bioresources and Rural Systems Engineering Hankyong National University Anseong17579 Korea Republic of State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China the Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing100081 China Department of Civil and Environmental Engineering Seoul National University Seoul08826 Korea Republic of

This study was set to investigate the effects of rice husk biochar (RHB) on soil characteristics and growth of lettuce (Lactuca sativa). A comprehensive research approach was employed to examine the effect of different RHB concentrations (i.e., 0–1.5%) on soil pH, soil enzyme activities (i.e., alkaline phosphatase, beta-glucosidase, and dehydrogenase), soil microbial community, lettuce growth, and earthworm toxicity. The results showed that, within the studied RHB concentration range, the RHB application did not have significant effects on the soil pH. However, the enzyme activities were increased with increasing RHB concentration after the 28 d-lettuce growth period. The RHB application also increased the abundances of the bacterial genera Massilia and Bacillus and fungal genus Trichocladium having the plant growth promoting abilities. Furthermore, the study revealed that the root weight and number of lettuce leaves were significantly increased in the presence of the RHB, and the growth was dependent on the RHB concentration. The improved lettuce growth can be explained by the changes in the enzyme and microbial dynamics, which have resulted from the increased nutrient availability with the RHB application. Additionally, the earthworm toxicity test indicated that the tested RHB concentrations can be safely applied to soil without any significant ecotoxicity. In conclusion, this study underscores the potential of RHB as a soil amendment with positive effects on crop growth, highlighting the utilization of agricultural byproducts to enhance soil biological quality and plant growth through biochar application. © 2023 Elsevier Ltd

关键词： Lettuce

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Approximate Gibbs Sampler for Efficient Inference of Hierarchical Bayesian Models for Grouped Count Data

arXiv

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arXiv 2022年

作者： Yü, Jin-Zhu Baroud, Hiba Department of Civil Engineering University of Texas at Arlington ArlingtonTX United States Department of Industrial Manufacturing and Systems Engineering University of Texas at Arlington ArlingtonTX United States Department of Civil and Environmental Engineering Vanderbilt University NashvilleTN United States Department of Computer Science Vanderbilt University NashvilleTN United States

Hierarchical Bayesian Poisson regression models (HBPRMs) provide a flexible modeling approach of the relationship between predictors and count response variables. The applications of HBPRMs to large-scale datasets require efficient inference algorithms due to the high computational cost of inferring many model parameters based on random sampling. Although Markov Chain Monte Carlo (MCMC) algorithms have been widely used for Bayesian inference, sampling using this class of algorithms is time-consuming for applications with large-scale data and time-sensitive decision-making, partially due to the non-conjugacy of many models. To overcome this limitation, this research develops an approximate Gibbs sampler (AGS) to efficiently learn the HBPRMs while maintaining the inference accuracy. In the proposed sampler, the data likelihood is approximated with Gaussian distribution such that the conditional posterior of the coefficients has a closed-form solution. Numerical experiments using real and synthetic datasets with small and large counts demonstrate the superior performance of AGS in comparison to the state-of-the-art sampling algorithm, especially for large datasets. © 2022, CC BY.

关键词： Markov chains

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Impact of polystyrene nanoplastics on primary sludge fermentation under acidic and alkaline conditions: Significance of antibiotic resistance genes

引用

Chemosphere 2024年 364卷 142777页

作者： Saila, Romana Zakaria, Basem S. Mirsoleimani Azizi, Seyed Mohammad Mostafa, Alsayed Dhar, Bipro Ranjan Department of Civil and Environmental Engineering University of Alberta EdmontonT6G 1H9 Canada Biological Systems and Engineering Division Lawrence Berkeley National Laboratory BerkeleyCA United States Advanced Biofuels and Bioproducts Process Development Unit EmeryvilleCA United States Stantec 10220 103 Ave NW #300 EdmontonABT5J 0K4 Canada

As a part of industrial or commercial discharge, the influx of nanoplastics (NPs) to the wastewater treatment plants is inevitable. Consequently, it has become a must to understand the effects of these NPs on different unit processes. This study aimed to investigate the impact of three different concentrations of polystyrene nanoplastics (PsNPs) on the fermentation of primary sludge (PrS), implemented in batch anaerobic bioreactors, at pH 5 and 10, considering the pH-dependent nature of the fermentation process. The results showed that PsNPs stimulated hydrogen gas production at a lower dose (50 μg/L), while a significant gas suppression was denoted at higher concentrations (150 μg/L, 250 μg/L). In both acidic and alkaline conditions, propionic and acetic acid predominated, respectively, followed by n-butyric acid. Under both acidic and alkaline conditions, exposure to PsNPs boosted the propagation of various antibiotic resistance genes (ARGs), including tetracycline, macrolide, β-lactam and sulfonamide resistance genes, and integrons. Notably, under alkaline condition, the abundance of sul2 gene in the 250 μg PsNPs/L batch exhibited a 2.4-fold decrease compared to the control batch. The response of the microbial community to PsNPs exposure exhibited variations at different pH values. Bacteroidetes prevailed at both pH conditions, with their relative abundance increasing after PsNPs exposure, indicating a positive impact of PsNPs on PrS solubilization. Adverse impacts, however, were detected in Firmicutes, Chloroflexi and Actinobacteria. The observed variations in the survival rates of various microbes stipulate that they do not have the same tolerance levels under different pH conditions. © 2024 Elsevier Ltd

关键词： Alkalinity

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Forest Clearances, Compensatory Afforestation, and Biodiversity Offsetting in Forests: An Analysis of Stakeholder Preferences in Switzerland

SSRN

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SSRN 2023年

作者： Schulz, Tobias Ohmura, Tamaki Troxler, David Lieberherr, Eva WSL Swiss Federal Institute for Forest Snow and Landscape Research Zürcherstrasse 111 Birmensdorf8903 Switzerland Institute for Spatial and Landscape Development Department of Civil Environmental and Geomatic Engineering ETH Zurich Switzerland Natural Resource Policy Group Climate Policy Group Institute for Environmental Decisions Department of Environmental Systems Science ETH Zurich Switzerland

While the settlement area is mainly expanding at the cost of agricultural land in densely populated regions such as Central Europe, this development is also affecting the forest. Forest clearances due to, e.g. traffic and energy infrastructure development require afforestation elsewhere but surfaces providing appropriate soil are increasingly becoming *** is an important case in this respect. It is densely populated, exhibits a fairly large amount of forest – also in the lowland – and although it features a particularly strong forest protection law, it recently allowed compensating forest clearances with non-forest related offsets. Based on the results Q-methodology survey conducted during a stakeholder workshop, we show that while pressure for more flexible forest sector specific rules largely stems from "outside", i.e. the agriculture and development sector and while there is a smaller group of actors aiming at going back to the more restrictive regime, the largest group of actors embraces the status quo. This group rejects expansion of more flexible rules and adheres to strengthening the top of the mitigation hierarchy, i.e. prioritizing the mitigation of habitat loss caused by development. This interpretation of biodiversity offsetting aligns with the conviction that development needs to respect the limits of growth. While prioritizing the mitigation hierarchy requires a planning rather than a market coordination approach, innovative options (such as afforestation on urban wasteland) and improved guidelines for biodiversity offsetting in the forest are also urgently needed. © 2023, The Authors. All rights reserved.

关键词： Biodiversity

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FedBEVT: Federated Learning Bird’s Eye View Perception Transformer in Road Traffic systems

arXiv

引用

arXiv 2023年

作者： Song, Rui Xu, Runsheng Festag, Andreas Ma, Jiaqi Knoll, Alois Fraunhofer Institute for Transportation and Infrastructure Systems IVI Ingolstadt85051 Germany Technical University of Munich Garching85748 Germany The Department of Civil and Environmental Engineering University of California Los AngelesCA90024 United States Ingolstadt85049 Germany

Bird’s eye view (BEV) perception is becoming increasingly important in the field of autonomous driving. It uses multi-view camera data to learn a transformer model that directly projects the perception of the road environment onto the BEV perspective. However, training a transformer model often requires a large amount of data, and as camera data for road traffic are often private, they are typically not shared. Federated learning offers a solution that enables clients to collaborate and train models without exchanging data but model parameters. In this paper, we introduce FedBEVT, a federated transformer learning approach for BEV perception. In order to address two common data heterogeneity issues in FedBEVT: (i) diverse sensor poses, and (ii) varying sensor numbers in perception systems, we propose two approaches – Federated Learning with Camera-Attentive Personalization (FedCaP) and Adaptive Multi-Camera Masking (AMCM), respectively. To evaluate our method in real-world settings, we create a dataset consisting of four typical federated use cases. Our findings suggest that FedBEVT outperforms the baseline approaches in all four use cases, demonstrating the potential of our approach for improving BEV perception in autonomous driving. © 2023, CC BY.

关键词： Birds

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Modeling Flux of Acetic Acid in Membrane Distillation with the Effect of Ph and Concentration

SSRN

引用

SSRN 2023年

作者： Shin, Bora Shin, Jaewon Wirasembada, Yanuar Chandra Park, Ki Young Cho, Jinwoo Department of Environment and Energy Sejong University 209 Neungdong-ro Gwangjin-gu Seoul05006 Korea Republic of Department of Civil and Environmental Systems Engineering Konkuk University 120 Neungdong-ro Gwangjin-gu Seoul05029 Korea Republic of

Acetic acid, a compound belonging to the group of volatile fatty acids (VFAs), needs to be treated and discharged due to its toxicity and foul odor. However, it is also highly evaluated as a recyclable resource that can be converted into bioenergy. VFAs, including acetic acid, can be produced from waste sources through anaerobic digestion and fermentation processes, and the control of VFAs can be achieved through the membrane distillation (MD) process. This study focuses on acetic acid, which has the highest proportion among VFAs produced in hydrogen fermentation, was selected. The goal was to experimentally determine the parameters influencing the mass transfer mechanism and flux of acetic acid in the MD as well as to propose a flux model. Even for acetic acid solutions with the same concentration, the permeability of acetic acid varied depending on the ionization fraction influenced by the pH. The permeability of acetic acid was proportional to the ionization fraction ([[EQUATION]]) of the feed solution. A lower pH resulted in a higher [[EQUATION]] value and increased vapor pressure of acetic acid. Accordingly, a new flux model reflecting the ionization fraction was proposed to calculate the flux of acetic acid, and it was confirmed that the observed values and the predicted values using the new model were highly consistent. The proposed model can be used to predict the initial flux of the MD process for treating wastewater containing acetic acid. Additionally, modeling works can provide more insights into the relationship between flux, pH, and concentration. © 2023, The Authors. All rights reserved.

关键词： Volatile fatty acids

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