Economic benefit analysis of lithium battery recycling based on machine learning algorithm.

Lithium batteries, as an important energy storage device, are widely used in the fields of renewable vehicles and renewable energy. The related lithium battery recycling industry has also ushered in a golden period of development. However, the high cost of lithium battery recycling makes it difficult to accurately evaluate its recycling value, which seriously restricts the development of the industry. To address the above issues, machine learning will be applied in the field of economic benefit analysis for lithium battery recycling, and backpropagation neural networks will be combined with stepwise regression. On the basis of considering social and commercial values, a lithium battery recycling and utilization economic benefit analysis model based on stepwise regression backpropagation neural network was designed. The experimental results show that the mean square error of the model converges between 10-6 and 10-7, and the convergence speed is improved by 33%. In addition, in practical experiments, the model predicted the actual economic benefits of recycling a batch of lithium batteries. The results show that the predictions are basically in line with the true values. Therefore, the economic benefit analysis and prediction model for lithium battery recycling proposed in the study has the advantages of high accuracy and fast operation speed, providing new ideas and tools for promoting innovation in the field of economic benefit analysis. It has certain application potential in the evaluation of the benefits of lithium battery recycling.

Health Benefits of Strategies for Carbon Mitigation in US Transportation, 2017‒2050.

Objectives. To quantify health benefits and carbon emissions of 2 transportation scenarios that contrast optimum levels of physical activity from active travel and minimal air pollution from electric cars. Methods. We used data on burden of disease, travel, and vehicle emissions in the US population and a health impact model to assess health benefits and harms of physical activity from transportation-related walking and cycling, fine particulate pollution from car emissions, and road traffic injuries. We compared baseline travel with walking and cycling a median of 150 weekly minutes for physical activity, and with electric cars that minimized carbon pollution and fine particulates. Results. In 2050, the target year for carbon neutrality, the active travel scenario avoided 167 000 deaths and gained 2.5 million disability-adjusted life years, monetized at $1.6 trillion using the value of a statistical life. Carbon emissions were reduced by 24% from baseline. Electric cars avoided 1400 deaths and gained 16 400 disability-adjusted life years, monetized at $13 billion. Conclusions. To achieve carbon neutrality in transportation and maximize health benefits, active travel should have a prominent role along with electric vehicles in national blueprints. (Am J Public Health. 2022; 112(3):426-433. https://doi.org/10.2105/AJPH.2021.306600).

Triboelectric Nanogenerator from Used Surgical Face Mask and Waste Mylar Materials Aiding the Circular Economy.

Apart from claiming the lives of more than 3.2 million people, the COVID-19 pandemic is worsening the global plastic pollution every day, mainly with the overflux of single-use polypropylene (PP) face masks. In this scenario, as an innovative solution to mitigate plastic pollution as well as to meet the rising electrical energy demand, we are introducing an all-flexible and facile waste material-based triboelectric nanogenerator (WM-TENG), aiding toward the circular economy. The WM-TENG operating in contact separation mode is fabricated using the PP from a used face mask in combination with recovered Mylar sheets from solid wastes as triboelectric contact layers and a flexible supporting structure. After detailed investigation and trials to study the effect of various disinfection mechanisms of PP materials on the energy output of WM-TENG, UV-C radiation is selected for disinfecting the used masks owing to the retention of electrical energy output. Under a tapping force of 3 N, the WM-TENG having an active area of 6 cm2 delivers an open-circuit voltage of 200 V and a short-circuit current density of 0.29 mA/m2, respectively. The WM-TENG also delivered a maximum power density of 71.16 mW/m2 under 108 Ω load. Additionally, the WM-TENG is demonstrated for powering electronic gadgets such as a calculator, digital thermometer, and LCD clock. This flexible and low-cost nanogenerator without any complex fabrication steps is a sustainable solution for the alarming plastic pollution as well as the rising energy demands.

Battery-Powered Portable Rotary Real-Time Fluorescent qPCR with Low Energy Consumption, Low Cost, and High Throughput.

The traditional qPCR instrument is bulky, expensive, and inconvenient to carry, so we report a portable rotary real-time fluorescent PCR (polymerase chain reaction) that completes the PCR amplification of DNA in the field, and the reaction can be observed in real-time. Through the analysis of a target gene, namely pGEM-3Zf (+), the gradient amplification and melting curves are compared to commercial devices. The results confirm the stability of our device. This is the first use of a mechanical rotary structure to achieve gradient amplification curves and melting curves comparable to commercial instruments. The average power consumption of our system is about 7.6 W, which is the lowest energy consumption for real-time fluorescence quantification in shunting PCR and enables the use of our device in the field thanks to its self-contained power supply based on a lithium battery. In addition, all of the equipment costs only about 710 dollars, which is far lower than the cost of a commercial PCR instrument because the control system through mechanical displacement replaces the traditional TEC (thermoelectric cooler) temperature control. Moreover, the equipment has a low technical barrier, which can suit the needs of non-professional settings, with strong repeatability.

Energy self-sufficient households with photovoltaics and electric vehicles are feasible in temperate climate.

The idea that households produce and consume their own energy, that is, energy self-sufficiency at a very local level, captures the popular imagination and commands political support across parts of Europe. This paper investigates the technical and economic feasibility of household energy self-sufficiency in Switzerland, which can be seen as representative for other regions with a temperate climate, by 2050. We compare sixteen cases that vary across four dimensions: household type, building type, electricity demand reduction, and passenger vehicle use patterns. We assume that photovoltaic (PV) electricity supplies all energy, which implies a complete shift away from fossil fuel based heating and internal combustion engine vehicles. Two energy storage technologies are considered: short-term storage in lithium-ion batteries and long-term storage with hydrogen, requiring an electrolyzer, storage tank, and a fuel cell for electricity conversion. We examine technological feasibility and total system costs for self-sufficient households compared to base cases that rely on fossil fuels and the existing power grid. PV efficiency and available rooftop/facade area are most critical with respect to the overall energy balance. Single-family dwellings with profound electricity demand reduction and urban mobility patterns achieve self-sufficiency most easily. Multi-family buildings with conventional electricity demand and rural mobility patterns can only be self-sufficient if PV efficiency increases, and all of the roof plus most of the facade can be covered with PV. All self-sufficient cases are technically feasible but more expensive than fully electrified grid-connected cases. Self-sufficiency may even become cost-competitive in some cases depending on storage and fossil fuel prices. Thus, if political measures improve their financial attractiveness or individuals decide to shoulder the necessary investments, self-sufficient buildings may start to become increasingly prevalent.

Environmental and economical assessment for a sustainable Zn/air battery.

Metal/Air batteries are being developed and soon could become competitive with other battery technologies already in the market, such as Li-ion battery. The main problem to be addressed is the cyclability, although some progress has been recently achieved. A Life Cycle Assessment (LCA) of the manufacturing process of a Zn/Air battery is presented in this article, including raw extraction and process of materials and battery assembly at laboratory scale (cradle to gate approach). The results indicate that Zn/Air battery can be fabricated with low environmental impacts in most categories and only four deserve attention (still being low impacts), such as Human Toxicity (cancer and non-cancer), Freshwater Ecotoxicity and Resource Depletion (the later one depending mainly on Zn use, which is not a critical material, but has a strong impact on this category). Cathode fabrication arises as the subassembly with higher impacts, followed by membrane, then anode and finally electrolyte. An economic cost calculation indicates that if cyclability of Zn/Air batteries is achieved, they can become competitive with other technologies already in the market.

Economic Aspects of a Concrete Floating Offshore Wind Platform in the Atlantic Arc of Europe.

The objective of this paper is to examine the economic aspects of a concrete offshore wind floating platform in the Atlantic Arc of Europe (Portugal and Spain). The life-cycle cost of a concrete floating offshore wind platform is considered to calculate the main economic parameters that will define the economic feasibility of the offshore wind farm. The case of study is the concrete floating offshore wind platform Telwind®, a spar platform with a revolutionary way of installing using a self-erecting telescopic tower of the wind turbine. In addition, the study analyses thirteen locations in Spain and twenty in Portugal, including the Atlantic islands of both countries. Results indicate that the economically feasible location to install a concrete offshore wind farm composed of concrete platforms is the Canary Islands (Spain) and Flores (Portugal).

Pulse generator battery life in deep brain stimulation: out with the old in with the less durable?

BACKGROUND: Battery life of the most commonly used implantable pulse generators in deep brain stimulation is limited. Device replacement is costly and may expose patients to additional risks. Driven by the observation that in our experience newer generation devices seemed to need earlier replacement than the older generation, we aimed to retrospectively analyze the battery life of two generations of non-rechargeable devices, manufactured by a single company (Medtronic, USA). METHODS: Battery life of 281 devices in 165 patients was taken into account for data analysis. This represented 243 older generation devices (Kinetra and Soletra) and 38 newer generation devices (Activa). RESULTS: The battery life of older generation stimulators was 2-fold longer than the newer generation. CONCLUSIONS: Newer devices are more versatile than the older generation. Their battery life is however significantly shorter. Development of next-generation devices needs to address this issue in order to limit health risks and reduce financial costs.

Technoeconomic modelling and environmental assessment of a modern PEMFC CHP system: a case study of an eco-house at University of Nottingham.

This simulation study is aimed to model a contemporary Proton Exchange Membrane fuel cell (PEMFC) CHP system having a 'heat and power' autonomy as well as a provision of demand-driven electrical supply to the grid. A novel nanowire-electrode PEMFC stack is adopted within this PEMFC CHP system so to effectively replace the existing natural gas fuelled durable solid oxide fuel cell (SOFC) CHP system installed at David Wilson Millennium Eco-house at University of Nottingham. The energy savings, environmental, and economic performances of the proposed PEMFC system are determined and compared to the base case (SOFC) which is operated continuously to maintain a 1.5 kWe. While to meetup the highly fluctuating and seasonal demands of heating and power like in the UK, a PEMFC is more productive and advantageous over a SOFC. The proposed PEMFC unlike to the SOFC will be able to operate and adjust its output and turn down instantly as per changing conditions of ambient temperatures and loads in terms of electricity and heat. The results of the modelling predicted that as compared to the base case scenario, this PEMFC CHP system will efficiently reduce an annual CO2 emission by 65.99% and fiscal costs by 66.74% with a viable internal rate of return as 8.93% and benefit to cost ratio as 1.02.

Optimal Operation of the Hybrid Electricity Generation System Using Multiverse Optimization Algorithm.

The ongoing load-shedding and energy crises due to mismanagement of energy produced by different sources in Pakistan and increasing dependency on those sources which produce energy using expensive fuels have contributed to rise in load shedding and price of energy per kilo watt hour. In this paper, we have presented the linear programming model of 95 energy production systems in Pakistan. An improved multiverse optimizer is implemented to generate a dataset of 100000 different solutions, which are suggesting to fulfill the overall demand of energy in the country ranging from 9587 MW to 27208 MW. We found that, if some of the power-generating systems are down due to some technical problems, still we can get our demand by following another solution from the dataset, which is partially utilizing the particular faulty power system. According to different case studies, taken in the present study, based on the reports about the electricity short falls been published in news from time to time, we have presented our solutions, respectively, for each case. It is interesting to note that it is easy to reduce the load shedding in the country, by following the solutions presented in our dataset. Graphical analysis is presented to further elaborate our findings. By comparing our results with state-of-the-art algorithms, it is interesting to note that an improved multiverse optimizer is better in getting solutions with lower power generation costs.

Optimal sizing and energy scheduling of isolated microgrid considering the battery lifetime degradation.

The incessantly growing demand for electricity in today's world claims an efficient and reliable system of energy supply. Distributed energy resources such as diesel generators, wind energy and solar energy can be combined within a microgrid to provide energy to the consumers in a sustainable manner. In order to ensure more reliable and economical energy supply, battery storage system is integrated within the microgrid. In this article, operating cost of isolated microgrid is reduced by economic scheduling considering the optimal size of the battery. However, deep discharge shortens the lifetime of battery operation. Therefore, the real time battery operation cost is modeled considering the depth of discharge at each time interval. Moreover, the proposed economic scheduling with battery sizing is optimized using firefly algorithm (FA). The efficacy of FA is compared with other metaheuristic techniques in terms of performance measurement indices, which are cost of electricity and loss of power supply probability. The results show that the proposed technique reduces the cost of microgrid and attain optimal size of the battery.

Activity-Aware Wearable System for Power-Efficient Prediction of Physiological Responses.

Wearable health monitoring has emerged as a promising solution to the growing need for remote health assessment and growing demand for personalized preventative care and wellness management. Vital signs can be monitored and alerts can be made when anomalies are detected, potentially improving patient outcomes. One major challenge for the use of wearable health devices is their energy efficiency and battery-lifetime, which motivates the recent efforts towards the development of self-powered wearable devices. This article proposes a method for context aware dynamic sensor selection for power optimized physiological prediction using multi-modal wearable data streams. We first cluster the data by physical activity using the accelerometer data, and then fit a group lasso model to each activity cluster. We find the optimal reduced set of groups of sensor features, in turn reducing power usage by duty cycling these and optimizing prediction accuracy. We show that using activity state-based contextual information increases accuracy while decreasing power usage. We also show that the reduced feature set can be used in other regression models increasing accuracy and decreasing energy burden. We demonstrate the potential reduction in power usage using a custom-designed multi-modal wearable system prototype.

STATCOM Estimation Using Back-Propagation, PSO, Shuffled Frog Leap Algorithm, and Genetic Algorithm Based Neural Networks.

Different optimization techniques are used for the training and fine-tuning of feed forward neural networks, for the estimation of STATCOM voltages and reactive powers. In the first part, the paper presents the voltage regulation in IEEE buses using the Static Compensator (STATIC) and discusses efficient ways to solve the power systems featuring STATCOM by load flow equations. The load flow equations are solved using iterative algorithms such as Newton-Raphson method. In the second part, the paper focuses on the use of estimation techniques based on Artificial Neural Networks as an alternative to the iterative methods. Different training algorithms have been used for training the weights of Artificial Neural Networks; these methods include Back-Propagation, Particle Swarm Optimization, Shuffled Frog Leap Algorithm, and Genetic Algorithm. A performance analysis of each of these methods is done on the IEEE bus data to examine the efficiency of each algorithm. The results show that SFLA outperforms other techniques in training of ANN, seconded by PSO.

Battery longevity of implantable cardioverter-defibrillators and cardiac resynchronization therapy defibrillators: technical, clinical and economic aspects. An expert review paper from EHRA.

In recent years an extension of devices longevity has been obtained for implantable cardioverter-defibrillators (ICDs), including ICDs for cardiac resynchronization therapy (CRT-D) through improved battery chemistry and device technology and this implies important clinical benefits (reduced need for device replacements and associated complications, particularly infections), as well as economic benefits, in line with patient preferences and needs. From a clinical point of view, the availability of this improvement in technology allows to better tune the choice of the device to be implanted, taking into account that the reasons supporting the value of an extended device longevity as a clinical priority may differ according to the clinical setting (purely electrical diseases or left ventricular dysfunction/heart failure, respectively). From an economic point of view, extension of device longevity may have an important impact in reducing long-term costs of device therapy, with substantial daily savings in favour of devices with extended longevity, up to 30%, depending on clinical scenarios. In studies based on projections, an extension of device longevity allowed to calculate that the cost per day of ICDs may be substantially reduced, and this allows to overcome the frequent perception of ICD and CRT-D devices as treatments with unaffordable costs and to overturn the misconception that up-front costs are the only metric with which to value device treatments. In view of its clinical and economic value, device longevity should be a determining factor in device choice by physicians and healthcare commissioners and should be appropriately considered and valued in comparative tenders.

Decoupling emissions of greenhouse gas, urbanization, energy and income: analysis from the economy of China.

The adoption and ratification of relevant policies, particularly the household enrolment system metamorphosis in China, led to rising urbanization growth. As the leading developing economy, China has experienced a drastic and rapid increase in the rate of urbanization, energy use, economic growth and greenhouse gas (GHG) pollution for the past 30 years. The knowledge of the dynamic interrelationships among these trends has a plethora of implications ranging from demographic, energy, and environmental and sustainable development policies. This study analyzes the role of urbanization in decoupling GHG emissions, energy, and income in China while considering the critical contribution of energy use. As a contribution to the extant body of literature, the present research introduces a new phenomenon called "the environmental urbanization Kuznets curve" (EUKC), which shows that at the early stage of urbanization, the environment degrades however, after a threshold point the technique effects surface and environmental degradation reduces with rise in urbanization. Applying the autoregressive distributed lag model and the vector error correction model, the paper finds the presence of inverted U-shaped curve between urbanization and GHG emission of CO2, while the same hypothesis cannot be found between income and GHG emission of CO2. Energy use in all the models contributes to GHG emission of CO2. In decoupling greenhouse gas emissions, urbanization, energy, and income, articulated and well-implemented energy and urbanization policies should be considered.

Cost-Minimization Analysis of Deep-Brain Stimulation Using National Database of Japanese Health Insurance Claims.

OBJECTIVES: A new rechargeable dual-channel deep brain stimulation (DBS) system has been introduced for the treatment of Parkinson's disease and other movement disorders. However, the clinical value of the device, which has a high cost, remains unclear. MATERIALS AND METHODS: We conducted a cost-minimization analysis using a national database of health insurance claims in Japan. DBS-related costs were compared between rechargeable and non-rechargeable devices and estimated across a 20-year period. RESULTS: Although the price of rechargeable DBS was higher than that of non-rechargeable DBS, we observed total cost-savings of 8.4 million yen across 20 years by considering costs related to implantation surgery, frequency of replacement, and risk of complications. CONCLUSIONS: In this study, real-world evidence indicated that rechargeable dual-channel DBS is a reasonable choice for saving total medical costs. Price revisions should consider cost-effectiveness findings for medical devices.

Cost-effectiveness of a risk-stratified approach to cardiac resynchronisation therapy defibrillators (high versus low) at the time of generator change.

OBJECTIVE: Responders to cardiac resynchronisation therapy whose device has a defibrillator component and who do not receive a therapy in the lifetime of the first generator have a very low incidence of appropriate therapy after box change. We investigated the cost implications of using a risk stratification tool at the time of generator change resulting in these patients being reimplanted with a resynchronisation pacemaker. METHODS: A decision tree was created using previously published data which had demonstrated an annualised appropriate defibrillator therapy risk of 2.33%. Costs were calculated at National Health Service (NHS) national tariff rates (2016-2017). EQ-5D utility values were applied to device reimplantations, admissions and mortality data, which were then used to estimate quality-adjusted life-years (QALYs) over 5 years. RESULTS: At 5 years, the incremental cost of replacing a resynchronisation defibrillator device with a second resynchronisation defibrillator versus resynchronisation pacemaker was £5045 per patient. Incremental QALY gained was 0.0165 (defibrillator vs pacemaker), resulting in an incremental cost-effectiveness ratio (ICER) of £305 712 per QALYs gained. Probabilistic sensitivity analysis resulted in an ICER of £313 612 (defibrillator vs pacemaker). For reimplantation of all patients with a defibrillator rather than a pacemaker to yield an ICER of less than £30 000 per QALY gained (current NHS cut-off for approval of treatment), the annual arrhythmic event rate would need to be 9.3%. The budget impact of selective replacement was a saving of £2 133 985 per year. CONCLUSIONS: Implanting low-risk patients with a resynchronisation defibrillator with the same device at the time of generator change is not cost-effective by current NHS criteria. Further research is required to understand the impact of these findings on individual patients at the time of generator change.

Nitrogen-Doped Carbon Nanotubes Derived from Metal-Organic Frameworks for Potassium-Ion Battery Anodes.

To tackle the issue of the poor rate capability of graphite anodes for potassium-ion batteries (KIBs), nitrogen-doped carbon nanotubes (NCNTs) with an edge-open layer-alignment structure were synthesized using a simple and scalable approach of pyrolyzing cobalt-containing metal-organic frameworks. The unique structure enables a facile and fast intercalation of K ions. As anodes of KIBs, the NCNTs demonstrated an improved rate capability by a high capacity retention of 102 mA h g-1 at a high current density of 2000 mA g-1 and a good stability without evident capacity loss over 500 cycles at 2000 mA g-1 . Our findings can help to develop highperformance anode materials for potassium-ion batteries as large-scale and low-cost energy-storage systems.