Advances Toward Sustainable Lignin-based Gel for Energy Storage and Smart Sensing

Polymers obtained from biomass are promising alternatives to petrobased polymers owing to their low cost,biocompatibility,and biodegradability.Lignin,a complex aromatic polymer containing several functional hydrophilic and active groups including hydroxyls,carbonyls,and methoxyls,is the second most abundant biopolymer in plants.In particular,sustainable ligninbased gels are emerging as an appealing material platform for developing energy-and sensing-related applications owing to their attractive and tailorable physiochemical properties.This study describes the preparation strategies of lignin-based gels according to previously reported methods,with significant attention on the diverse performance of lignin-derived gel materials.Additionally,a detailed review of lignin-based gels utilized as an important resource in diverse fields is provided.Finally,a future vision on challenges and their possible solutions is presented.

Energy-efficient digital and wireless IC design for wireless smart sensing

Wireless smart sensing is now widely used in various applications such as health monitoring and structural monitoring.In conventional wireless sensor nodes,significant power is consumed in wirelessly transmitting the raw data.Smart sensing adds local intelligence to the sensor node and reduces the amount of wireless data transmission via on-node digital signal processing.While the total power consumption is reduced compared to conventional wireless sensing,the power consumption of the digital processing becomes as dominant as wireless data transmission.This paper reviews the state-of-the-art energy-efficient digital and wireless IC design techniques for reducing the power consumption of the wireless smart sensor node to prolong battery life and enable self-powered applications.

Advanced industrial informatics towards smart,safe and sustainable roads:A state of the art

The road is one of the most important civil infrastructures for serving society,where its service quality and life have direct impacts on the safety and comfort of users.Therefore,road construction,condition detection and monitoring,and timely maintenance are particularly important for engineers.Many engineering applications of industrial informatics approaches,like image processing technology,widely used computer-based algorithms,and advanced sensors,have been initially and gradually applied to roads.This state-of-the-art review first summarized the research on industrial applications of advanced information technologies in recent years,while analyzing and comparing the advantages and disadvantages of each technology.Especially,five topics were focused on road construction,road maintenance with decision strategy,road structure evaluation,smart sensing in the road,and cooperative vehicle infrastructure system.It is expected that advanced industrial informatics can help engineers promote the development of smart,safe,and sustainable roads.

Robust image processing algorithm for computational resource limited smart apple sunburn sensing system

Heat and light stress causes sunburn to the maturing apple fruits and results in crop production and quality losses.Typically,when the fruit surface temperature(FST)rises above critical limits for a prolonged duration,the fruit may suffer several physiological disorders including sunburn.To manage apple sunburn,monitoring FST is critical and our group at Washington State University is developing a noncontact smart sensing system that integrates thermal infrared and visible imaging sensors for real time FST monitoring.Pertinent system needs to perform in-field imagery data analysis onboard a single board computer with processing unit that has limited computational resources.Therefore,key objective of this study was to develop a novel image processing algorithm optimized to use available resources of a single board computer.Algorithm logic flow includes color space transformation,k-means++classification and morphological operators prior to fruit segmentation and FST estimation.The developed algorithm demonstrated the segmentation accuracy of 57.78%(missing error=12.09%and segmentation error=0.13%).This aided successful apple FST estimation that was 10–18C warmer than ambient air temperature.Moreover,algorithm reduced the imagery data processing time cost of the smart sensing systemfrom 87 s to 44 s using image compression approach.

Conformable,programmable and step-linear sensor array for large-range wind pressure measurement on curved surface

The wind pressure measurement,especially on curved surfaces is imperative in revealing flow characteristics.The flexible sensor with high linear sensitivity over large pressure range is still a significant challenge,especially for commutatively positive and negative pressure measurement.Here,we propose a conformable,range-programmable capacitive sensor that can extremely extend the measuring range but with high linear sensitivity.The key point is to precisely control the reference pressure of the flexible capacitive sensor array through microchannel network.The proposed sensor with reference pressure 0 kPa keeps stable at a highly-linear sensitivity of 0.28 kPa-1 in an initial measurement regime from 0 to 3 kPa,beyond which the linearity changes significantly.Via the tunable reference pressure,the linear ranges can be customized arbitrarily according to different flight conditions and measured positions,but without any deterioration of sensitivity.The theoretical model is built for the flexible capacitive sensor with tunable reference pressure,agreeing well with the experimental and finite element method results.Additionally,the bending effect is discovered when the flexible sensor is conformed on curved surfaces.This surface-mounted sensor skin is tested on a plate and is integrated with acquisition circuits on a standard airfoil NACA0012 in a wind tunnel and compares with the standard destructive method of pressure taps.It shows great potential applications in measuring wind pressure on curved surfaces,such as for"Fly-by-Feel"of unmanned aerial vehicles and wind tunnel test.

Mechanoluminescent hybrids from a natural resource for energy-related applications

Mechanoluminescent(ML)materials that directly convert mechanical energy into photon emission have emerged as promising candidates for various applications.Despite the recent advances in the development of both novel and conventional ML materials,the limited access to ML materials that simultaneously have the attributes of high brightness,low cost,self-recovery,and stability,and the lack of appropriate designs for constructing ML devices represent significant challenges that remain to be addressed to boost the practical application of ML materials.Herein,ML hybrids derived from a natural source,waste eggshell,with the aforementioned attributes are demonstrated.The introduction of the eggshell not only enables the preparation of the hybrid in a simple and cost-effective manner but also contributes to the homochromatism(red,green,or blue emission),high brightness,and robustness of the resultant ML hybrids.The significant properties of the ML hybrids,together with the proposed structural design,such as porosity or core–shell structure,could expedite a series of mechanic-optical applications,including the self-luminous shoes for the conversion of human motions into light and light generators that efficiently harvest water wave energy.The fascinating properties,versatile designs,and the efficient protocol of“turning waste into treasure”of the ML hybrids represent significant advances in ML materials,promising a leap to the practical applications of this flouring material family.