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2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Yunpeng Jia ◽  
Yamin Pan ◽  
Chunfeng Wang ◽  
Chuntai Liu ◽  
Changyu Shen ◽  
...  

AbstractUltra-thin flexible films have attracted wide attention because of their excellent ductility and potential versatility. In particular, the energy-harvesting films (EHFs) have become a research hotspot because of the indispensability of power source in various devices. However, the design and fabrication of such films that can capture or transform different types of energy from environments for multiple usages remains a challenge. Herein, the multifunctional flexible EHFs with effective electro-/photo-thermal abilities are proposed by successive spraying Ag microparticles and MXene suspension between on waterborne polyurethane films, supplemented by a hot-pressing. The optimal coherent film exhibits a high electrical conductivity (1.17×104 S m−1), excellent Joule heating performance (121.3 °C) at 2 V, and outstanding photo-thermal performance (66.2 °C within 70 s under 100 mW cm−1). In addition, the EHFs-based single-electrode triboelectric nanogenerators (TENG) give short-circuit transferred charge of 38.9 nC, open circuit voltage of 114.7 V, and short circuit current of 0.82 μA. More interestingly, the output voltage of TENG can be further increased via constructing the double triboelectrification layers. The comprehensive ability for harvesting various energies of the EHFs promises their potential to satisfy the corresponding requirements.


Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 6005
Author(s):  
Armando Castillejo-Cuberos ◽  
John Boland ◽  
Rodrigo Escobar

Solar energy is an economic and clean power source subject to natural variability, while energy storage might attenuate it, ultimately, effective and operationally feasible forecasting techniques for energy management are needed for better grid integration. This work presents a novel deterministic forecast method considering: irradiance pattern classification, Markov chains, fuzzy logic and an operational approach. The method developed was applied in a rolling manner for six years to a target location with no prior data to assess performance and its changes as new local data becomes available. Clearness index, diffuse fraction and irradiance hourly forecasts are analyzed on a yearly basis but also for 20 day types, and compared against smart persistence. Results show the proposed method outperforms smart persistence by ~10% for clearness index and diffuse fraction on the base case, but there are significant differences across the 20 day types analyzed, reaching up to +60% for clear days. Forecast lead time has the greatest impact in forecasting performance, which is important for any practical implementation. Seasonality in data gaps or rejected data can have a definite effect in performance assessment. A novel, comprehensive and detailed analysis framework was shown to present a better assessment of forecasters’ performance.


2021 ◽  
Vol 20 (5s) ◽  
pp. 1-23
Author(s):  
Keni Qiu ◽  
Nicholas Jao ◽  
Kunyu Zhou ◽  
Yongpan Liu ◽  
Jack Sampson ◽  
...  

There is an ongoing trend to increasingly offload inference tasks, such as CNNs, to edge devices in many IoT scenarios. As energy harvesting is an attractive IoT power source, recent ReRAM-based CNN accelerators have been designed for operation on harvested energy. When addressing the instability problems of harvested energy, prior optimization techniques often assume that the load is fixed, overlooking the close interactions among input power, computational load, and circuit efficiency, or adapt the dynamic load to match the just-in-time incoming power under a simple harvesting architecture with no intermediate energy storage. Targeting a more efficient harvesting architecture equipped with both energy storage and energy delivery modules, this paper is the first effort to target whole system, end-to-end efficiency for an energy harvesting ReRAM-based accelerator. First, we model the relationships among ReRAM load power, DC-DC converter efficiency, and power failure overhead. Then, a maximum computation progress tracking scheme ( MaxTracker ) is proposed to achieve a joint optimization of the whole system by tuning the load power of the ReRAM-based accelerator. Specifically, MaxTracker accommodates both continuous and intermittent computing schemes and provides dynamic ReRAM load according to harvesting scenarios. We evaluate MaxTracker over four input power scenarios, and the experimental results show average speedups of 38.4%/40.3% (up to 51.3%/84.4%), over a full activation scheme (with energy storage) and order-of-magnitude speedups over the recently proposed (energy storage-less) ResiRCA technique. Furthermore, we also explore MaxTracker in combination with the Capybara reconfigurable capacitor approach to offer more flexible tuners and thus further boost the system performance.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yang Liu ◽  
Sang-Bing Tsai

In this paper, a hierarchical neural network power source model is used to conduct an in-depth analysis and research on human capital technology innovation and revenue distribution. A hierarchical neural network analysis method was chosen to evaluate the human capital value of professional degree master students, and the applicability of the index system was confirmed through errors; moreover, the significance of the output results was analyzed according to the weight assignments of the input, implicit, and output layers. The analysis found that there was a large disagreement in the assessment of their human capital value, which led to the lack of practical utility of human capital. Knowledge-skilled talents have a wealth of theoretical knowledge and can use theories to guide related work. Compared with technically skilled high-skilled talents, their educational level is higher, and they can summarize past intuitive experience into theoretical guidance. Therefore, the hierarchical neural network method we constructed is theoretically effective in assessing the value of the human capital of professional master’s students and the role of the main constituents. Based on the assessment results, we can provide policy-informed suggestions for improving the quality of school education. To quickly verify whether the model can converge during the training process, a simple dataset with only two sequences and the elements in the sequences being real numbers rather than vectors are constructed to speed up the computation; meanwhile, the length of the sequences in this dataset is adjustable to initially verify the model’s ability to alleviate the long-time dependence problem.


Biosensors ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 342
Author(s):  
Meng Wang ◽  
Guangting Zi ◽  
Jiajun Liu ◽  
Yutong Song ◽  
Xishan Zhao ◽  
...  

Creatinine has become an important indicator for the early detection of uremia. However, due to the disadvantages of external power supply and large volume, some commercial devices for detecting creatinine concentration have lost a lot of popularity in everyday life. This paper describes the development of a self-powered biosensor for detecting creatinine in sweat. The biosensor can detect human creatinine levels in real time without the need for an external power source, providing information about the body’s overall health. The piezoelectric output voltage of creatininase/creatinase/sarcosine oxidase-modified ZnO nanowires (NWs) is significantly dependent on the creatinine concentration due to the coupling effect of the piezoelectric effect and enzymatic reaction (piezo-enzymatic-reaction effect), which can be regarded as both electrical energy and biosensing signal. Our results can be used for the detection of creatinine levels in the human body and have great potential in the prediction of related diseases.


2021 ◽  
Author(s):  
Vinay Kommagoni ◽  
Sai Mahesh Devarakonda ◽  
Jemima Bai Bhukya ◽  
Manoj Kumar Vistarakula ◽  
Shilpa Mishra

Abstract Many municipalities across the world confront a major problem with waste water treatment. However, Tier-1 and Tier-2 cities have good infrastructure to treat the wastewater, but most of the villages are still facing the problem, because of less resources, the untreated waste water is left to flow on the ground, while travelling it merges with the fresh water bodies, and results in surface and ground water pollution in nearby villages. The devlopment of a pilot size waste water treatment system that efficiently produces water by evaporation and condensation in conjunction with a Fresnel lens solar concentrator is discussed and analysed in this experimental investigation.. Solar radiation setup for waste water treatment consists of Fresnel lens which help in achieving the temperature up to 400oC and then wastewater is being converted into vapour form due to this solar radiation. The evaporated vapour condenses on the surface of the glass and collects in a collecting tank. When compared to a typical wastewater treatment plant, this environmental friendly and sustainable procedure removes organic and bacteriological contaminants from wastewater and, moreover, this chemical-free treatment converts wastewater into reusable form of water with less sludge. The main advantage of this treatment method is, simple to construct and no skilled manpower is required to operate it. Since solar radiation is used as a power source to achieve high temperature therefore, no external power source is required to operate this unit. Results indicate that strength of waste water is reduced by 87%, TDS reduced by 82% as compared to sewage water and Ca, Mg, N, P, Chlorides and Sulphates are reduced by 87%, 91%, 66%, 42%, 92% and 80% respectively. However, the main challenge of this method is low output, but can be improved by various techniques mentioned in the study.


Author(s):  
P. Ramesh

This paper focuses on the design of multi-structure controllers (MSCs) for KY negative output boost converter (KYNOBC) functioned in continuous current mode (CCM) for low-power source applications. KYNOBC is one of the topologies of DC–DC converter that performs the positive DC input supply voltage into a negative output voltage. Dynamic behavior of KYNOBC is nonlinear in nature because of its time-changing operation. The single loop control does not regulate the multi-parameters of KYNOBC during the line and load variations owing to that it produces poor transient and dynamic analyses. With the aim of controlling the multi-parameters of KYNOBC such as inductor current and output voltage, enriching the transient and dynamic analysis, the MSCs are recommended in this paper. In our study, MSCs for KYNOBC consist of two loops such as inner proportional (P) controller inductor current loop for modulating the converter current and outer fuzzy logic controller (FLC)/proportional integral (PI) controller voltage loop for regulating the output voltage. The P and PI values are determined from the mathematical modeling of KYNOBC and the fuzzy rules are framed based on its performance without modeling equations. The behaviors of the KYNOBC with MSCs are validated at various zones by making the MATLAB/Simulink simulations and prototype model. The controller parameters are realized in prototype field programmable gate array (FPGA). The responses are recorded to indicate the dexterous of the MSCs for it.


2021 ◽  
Author(s):  
Young-Chai Ko ◽  
Kug-Jin Jung ◽  
Ki Hong Park ◽  
Mohamed-Slim Alouini

<div> <div> <div> <p>Renewable energy (RE)-powered base stations (BSs) have been considered as an attractive solution to address the exponential increasing energy demand in cellular networks while decreasing carbon dioxide (CO2) emissions. For the regions where reliable power grids are insufficient and infeasible to deploy, such as aerial platforms and harsh environments, RE has been an alternative power source for BSs. In this survey paper, we provide an overview of RE-enabled cellular networks, detailing their analysis, classification, and related works. First, we introduce the key components of RE-powered BSs along with their frequently adopted models. Second, we analyze the proposed strategies and design issues for RE-powered BSs that can be incorporated into cellular networks and categorize them into several groups to provide a good grasp. Third, we introduce feasibility studies on RE-powered BSs based on the recent literature. Fourth, we investigate RE-powered network components other than terrestrial BSs to address potential issues regarding RE-enabled networks. Finally, we suggest future research directions and conclusions. </p><p><br></p> </div> </div> </div>


2021 ◽  
Author(s):  
Young-Chai Ko ◽  
Kug-Jin Jung ◽  
Ki Hong Park ◽  
Mohamed-Slim Alouini

<div> <div> <div> <p>Renewable energy (RE)-powered base stations (BSs) have been considered as an attractive solution to address the exponential increasing energy demand in cellular networks while decreasing carbon dioxide (CO2) emissions. For the regions where reliable power grids are insufficient and infeasible to deploy, such as aerial platforms and harsh environments, RE has been an alternative power source for BSs. In this survey paper, we provide an overview of RE-enabled cellular networks, detailing their analysis, classification, and related works. First, we introduce the key components of RE-powered BSs along with their frequently adopted models. Second, we analyze the proposed strategies and design issues for RE-powered BSs that can be incorporated into cellular networks and categorize them into several groups to provide a good grasp. Third, we introduce feasibility studies on RE-powered BSs based on the recent literature. Fourth, we investigate RE-powered network components other than terrestrial BSs to address potential issues regarding RE-enabled networks. Finally, we suggest future research directions and conclusions. </p><p><br></p> </div> </div> </div>


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