Aggregate Level Research Articles

Tension Lap Splices in Recycled-Aggregate Concrete Strengthened with Steel–Polyolefin Fibers

The bond strength of tension lap splices in recycled-coarse-aggregate-reinforced concrete strengthened with hybrid (steel–polyolefin) fibers was experimentally investigated. This study was conducted with the help of twelve lap-spliced beam specimens. The replacement level of coarse natural aggregates with recycled concrete aggregate (RCA) was 100%. The following variables were investigated: various ranges of steel–polyolefin fibers—100–0%, 75–25%, 50–50%, 25–75%, and 0–100%—in which the total volume fraction of fibers (Vf) remains constant at 1%; and two lengths of lap splices for rebars of 16 mm diameter (db): 10 db and 15 db. The test results showed that the best range of steel–polyolefin fibers that gave the highest bond strength was 50–50%. The ductility of the fiber-reinforced recycled-aggregate (FR-RA) concrete was significantly improved for all the cases of various relative ratios of steel and polyolefin fibers. The bond strength was also predicted using three empirical equations proposed by Orangun et al., Darwin et al., and Harajli. This study showed that the Harajli equation gave a more accurate estimation of the bond strength of reinforcing bars embedded in FR-RA concrete than those proposed by Orangun et al. and Darwin et al.

Short-Term Energy Forecasting to Improve the Estimation of Demand Response Baselines in Residential Neighborhoods: Deep Learning vs. Machine Learning

Promoting flexible energy demand through response programs in residential neighborhoods would play a vital role in addressing the issues associated with increasing the share of distributed solar systems and balancing supply and demand in energy networks. However, accurately identifying baseline-related energy measurements when activating energy demand response events remains challenging. In response, this study presents a deep learning-based, data-driven framework to improve short-term estimates of demand response baselines during the activation of response events. This framework includes bidirectional long-term memory (BiLSTM), long-term memory (LSTM), gated recurrent unit (GRU), convolutional neural networks (CNN), deep neural networks (DNN), and recurrent neural networks (RNN). Their performance is evaluated by considering different aggregation levels of the demand response baseline profile for 337 dwellings in the city of La Rochelle, France, over different time horizons, not exceeding 24 h. It is also compared with fifteen traditional statistical and machine learning methods in terms of forecasting accuracy. The results demonstrated that deep learning-based models, compared to others, significantly succeeded in minimizing the gap between the actual and forecasted values of demand response baselines at all different aggregation levels of dwelling units over the considered time-horizons. BiLSTM models, followed by GRU and LSTM, consistently demonstrated the lowest mean absolute percentage error (MAPE) in most comparison experiments, with values up to 9.08%, 8.71%, and 9.42%, respectively. Compared to traditional statistical and machine learning models, extreme gradient boosting (XGBoost) was among the best, with a value up to 11.56% of MAPE, but could not achieve the same level of forecasting accuracy in all comparison experiments. Such high performance reveals the potential of the proposed deep learning approach and highlights its importance for improving short-term estimates of future baselines when implementing demand response programs in residential neighborhood contexts.

Evaluation of an automated platelet aggregation method for detection of congenital or acquired platelet function defects.

Light transmission aggregometry (LTA) is the most widely used laboratory method for an initial screening of patients with a suspected platelet function defect (PFD), and its use has also been proposed for assessing the efficacy of antiplatelet treatment (APT). An automated LTA method has been developed by Sysmex (Kobe, Japan) on a routine coagulation analyzer (CS-2400), together with a new research parameter called PAL (platelet aggregation level) to evaluate patients on APT. We evaluated the performance of CS-2400 compared to a stand-alone lumi-dual-aggregometer device in the diagnosis of PFD and in assessing the efficacy of APT. For these purposes, the study population was represented by a cohort of 23 patients with a previous diagnosis of PFD and a cohort of 28 patients on APT. Compared to healthy volunteers, patients with PFD showed a statistically significant reduction (p<0.05) in the maximal %light transmission, irrespective of the agonist used, both with the CS-2400 and the lumi-dual-aggregometer. As regards PFD patients, CS-2400 was effective in identifying the more severe defects, with a good sensibility and specificity, but less effective in identifying milder forms of PFD, such as platelet secretion defects. Patients on APT showed a statistically significant (p=0.001) reduced median %light transmission and PAL scores compared to healthy controls. Thanks to this LTA technology, CS-2400, a routine coagulation analyzer widely available in routine laboratories, could prove useful for initial assessment of patients with a suspected PFD. Moreover, the PAL scores were a fairly accurate reflection of the platelet response to APT.

Ribbed floors with optimized thickness distribution for maximized broadband impact sound insulation

Impact sound insulation of floors is one of the main concerns when designing multi-story buildings. While conventional floor systems use flat or regularly ribbed configurations, interesting opportunities to improve performance are given by enhancing the design of the load-bearing slab. In this work, we propose a methodology to maximize broadband impact sound insulation by designing slabs with a non-uniform material thickness distribution, which is numerically optimized. In the design process, efficient and accurate sound insulation predictions are employed through a detailed finite element floor model coupled with a diffuse room model. In particular, we minimize a Single Number Quantity (SNQ) that represents the aggregate broadband sound pressure level in the receiving room under point-load excitation. The design of single slab floors is considered first. Results indicate that, even if the optimization effectively minimizes the sound pressure level in the different third-octave bands, it does not lead to noteworthy decreases in the SNQ. The design of floating floors is then considered. In this case, a better overall performance is obtained, corresponding to significant improvements at low frequencies and a slight degradation at high frequencies, where, nevertheless, floating floors already perform well. This slight high-frequency decline is linked with the resonances of the thin sub-plate regions present between the optimized ribs, akin to what is observed in waffle ribbed floors. Finally, the robustness of the optimized results against changes in the initial guess is assessed by showing that no SNQ improvements are obtained when transitioning from flat to waffle ribbed initial design.

Tau protein profiling in tauopathies: a human brain study

Abnormal accumulation of misfolded and hyperphosphorylated tau protein in brain is the defining feature of several neurodegenerative diseases called tauopathies, including Alzheimer’s disease (AD). In AD, this pathological change is reflected by highly specific cerebrospinal fluid (CSF) tau biomarkers, including both phosphorylated and non-phosphorylated variants. Interestingly, despite tau pathology being at the core of all tauopathies, CSF tau biomarkers remain unchanged in certain tauopathies, e.g., progressive supranuclear palsy (PSP), Pick’s disease (PiD), and corticobasal neurodegeneration (CBD). To better understand commonalities and differences between tauopathies, we report a multiplex assay combining immunoprecipitation and high-resolution mass spectrometry capable of detecting and quantifying peptides from different tau protein isoforms as well as non-phosphorylated and phosphorylated peptides, including those carrying multiple phosphorylations. We investigated the tau proteoforms in soluble and insoluble fractions of brain tissue from subjects with autopsy-confirmed tauopathies, including sporadic AD (n = 10), PSP (n = 11), PiD (n = 10), and CBD (n = 10), and controls (n = 10). Our results demonstrate that non-phosphorylated tau profiles differ across tauopathies, generally showing high abundance of microtubule-binding region (MTBR)-containing peptides in insoluble protein fractions compared with controls; the AD group showed 12–72 times higher levels of MTBR-containing aggregates. Quantification of tau isoforms showed the 3R being more abundant in PiD and the 4R isoform being more abundant in CBD and PSP in the insoluble fraction. Twenty-three different phosphorylated peptides were quantified. Most phosphorylated peptides were measurable in all investigated tauopathies. All phosphorylated peptides were significantly increased in AD insoluble fraction. However, doubly and triply phosphorylated peptides were significantly increased in AD even in the soluble fraction. Results were replicated using a validation cohort comprising AD (n = 10), CBD (n = 10), and controls (n = 10). Our study demonstrates that abnormal levels of phosphorylation and aggregation do indeed occur in non-AD tauopathies, however, both appear pronouncedly increased in AD, becoming a distinctive characteristic of AD pathology.

Desde los estados financierosmicrocontables hacia la macro contabilidad. Un modelo basadoen el measurement approach

The nomenclature in national, public, and financial account-ing, while sharing a common noun, has yet to explore potential synergies. despite accounting’s capacity for powerful analysis at micro and macro levels, the persistent microaccounting-macroaccounting dichotomy limits these synergies. Despite modest reception, scholars have explored con-verging Accounting into a comprehensive discipline, emphasizing inter-connections between macro and micro levels. This study presents a conceptual model spanning micro, meso, and macro fundamental accounting identities. Employing abstract concepts like Di-chev and Tang (2008), Dichev (2008, 2017), and Miller &amp; Bahnson (2010), it organizes economic value stocks and flows from micro to macro levels. Aligned with Scott’s concept of accounting under ideal conditions (2015), it’s grounded in beaver’s measurement approach (1989). The study con-firms, through micro accounting consolidation, that only real assets con-stitute society’s concrete capital. It outlines cyclic dynamics of rental phe-nomena from diverse assets, accruing rental values at each aggregation level. This analytical approach aids understanding accounting’s nature and identifies avenues for future research, including empirical estimation and periodic reassessment of abstract categories.

All aboard: The effects of port development

Seaports facilitate the fast flow of goods across space, but ports also entail local costs borne by host cities. We use the introduction of containerized shipping to explore the effects of port development. At the local level, we find that seaport development increases city population by making a city more attractive, but this market access effect is offset by costs which make the city less attractive. At the aggregate level, we find that the local costs associated with port development are heterogeneous across cities and reduce aggregate welfare gains. Net of the costs, our results suggest that containerization in seaports increased world welfare by 3.4%.

Efficiency and equity: A general equilibrium analysis of rent‐seeking

AbstractWe study the rent‐seeking phenomenon using a simple, static general equilibrium model. The economy consists of two sectors, both employing a constant returns‐to‐scale technology with labor as its sole input. One of the sectors is a monopoly, where a continuum of agents compete for a share of monopoly profits (i.e. rent). Agents are heterogeneous in labor productivity and rent‐seeking ability: they face a choice between engaging in (productive) work or vying for a share of the rent (i.e., a contest against other rent‐seekers). At the aggregate level, rent‐seeking reduces the available amount of labor in the economy and thereby lowers output and welfare (rent‐seeking is inefficient). At the individual level, rent‐seeking shifts income towards rent‐seekers. Consequently, an economy with few rent‐seekers tends to have high income inequality: an effect that is exacerbated by the fact that rent is decreasing in the number of rent‐seekers (low levels of rent‐seeking increase inequity). This tradeoff between efficiency and equity is the primary focus of this paper. We investigate how the distribution of rent‐seeking ability and the correlation between labor productivity and rent‐seeking ability shape this tradeoff.

Within-person increases in job autonomy linked to greater employee strain

ABSTRACT It is commonly believed that job autonomy has a positive impact on employee well-being and protects workers from strain. However, an emerging counter-narrative challenges this assumption and identifies ways in which greater job autonomy has negative impacts, especially for jobs that already have substantial autonomy. Contributing to this debate, our longitudinal study disaggregates stable, between-person variation in job autonomy from dynamic, within-person change in job autonomy over a multi-year period with a sample of Church ministers. We argue that experiencing high and stable job autonomy is conceptually distinct from experiencing an increase in one’s job autonomy; the former being positive for worker well-being while the latter often represents a form of role stress. We develop a two-level model tested by a random-intercept crossed-lagged panel analysis. We find that workers with higher job autonomy than others tend to have lower emotional exhaustion at the between-person level. Also at this level, trait positive affect and, more weakly, trait self-efficacy account for variance in aggregate levels of job autonomy and emotional exhaustion. Our model then evidences the counter-view that within-person increases in job autonomy are followed by greater emotional exhaustion. Implications for extending theory on within-person change in well-being are discussed.

Co-designing sustainable biochar business models with sub-Saharan African communities for inclusive socio-economic transformation

Smallholder farmers in sub-Saharan Africa (SSA) encounter multiple livelihood challenges. Embracing circular bioeconomy principles, particularly considering agricultural and food processing residues, could enable inclusive, locally led, sustainable development pathways within rural communities. Biochar products are one such example of a bio-based material that can be generated using circular principles and deployed for sustainable community development, including among smallholder farmers. This research leverages empirical evidence from four SSA regions to explore the potential of inclusive and sustainable biochar business models, namely: (i) Northern Region, Ghana, (ii) Yamoussoukro, Côte d’Ivoire, (iii) Casamance, Senegal, and (iv) Western Region, Uganda. Co-creation workshops using the Triple-Layered Business Model Canvas framework were carried out in each region with local stakeholders to evaluate the social, ecological, and economic implications of four locally relevant biochar applications: water filtration, biogas purification, soil amendment, and cooking fuel briquettes. Data was analysed at an aggregate level for all regions and applications. The study describes this consolidated biochar business model and examines the implications for SSA communities. The resulting sustainable bio-based business model can guide value chain actors and policymakers in SSA communities towards rural sustainable development with a better understanding of the needs, opportunities, challenges, and impacts of biochar-based value chain development.

Are all cancer survivors included when using electronically administered patient reported outcomes in primary healthcare cancer rehabilitation? A cross-sectional study

BackgroundPatient reported outcomes (PROs) are being used frequently in clinical practice. PROs often serve several purposes, such as increasing patient involvement, assessing health status, and monitoring and improving the quality-of-care at an aggregated level. However, the lack of representative PRO-data may have implications for all these purposes. This study aims to assess the association of non-administration of (not sending an electronic invite to PRO) and non-response to (not responding to PRO) electronically administered PROs with social inequality in a primary healthcare cancer rehabilitation setting. Furthermore, it examines whether the workflows surrounding PRO have an impact on non-administration and non-response.MethodsThis is a cross sectional study using routinely collected data from electronic health records and registers including cancer survivors (CSs) over 18 years booked for an initial consultation in a primary healthcare cancer rehabilitation setting using PROs for systematic health status assessment. During the study period two different PRO platforms were used, each associated with different workflows. Non-administration and non-response rates were calculated for sociodemographic characteristics for each PRO platform. Crude and adjusted odds ratios were calculated using univariate and multivariate logistic regression.ResultsIn total, 1868 (platform 1) and 1446 (platform 2) CSCSs were booked for an initial consultation. Of these, 233 (12.5%) (platform 1) and 283 (19.6%) (platform 2) were not sent a PRO (non-administration). Among those who received a PRO, 157 (9.6%) on platform 1 and 140 (12.0%) on platform 2 did not respond (non-response). Non-administration of and non-response to PROs were significantly associated with lower socioeconomic status. Moreover, the workflows surrounding PROs seem to have an impact on non-inclusion in and non-response to PROs.ConclusionsNon-administration of and non-response to PROs in clinical practice is associated with determinants of social inequality. Clinical workflows and the PRO platforms used may potentially worsen this inequality. It is important to consider these implications when using PROs at both the individual and aggregated levels. A key aspect of implementing PROs in clinical practice is the ongoing focus on representativeness, including a focus on monitoring PRO administration and response.

Early climate mitigation as a social dilemma

We introduce a novel game where a decaying atmospheric quality, modeled as a stock variable determining the payoff externality, can be counteracted through individual mitigation efforts. It encompasses three characteristics of climate change as a social dilemma: (a) the continuous nature of climate degradation, (b) the constant influx of emissions resulting from human economic activities, and (c) the greater efficacy of early mitigation actions. We report findings from an experiment where, across four treatments, we manipulate the starting atmospheric quality and introduce inequality in the endowments employed to mitigate. Results indicate that subjects fail to mitigate in early periods, an individually rational strategy. We do not find differences between treatments at the aggregate level. However, participants treat their groupmates’ past mitigation as a strategic substitute for their own mitigation (i.e., if others’ mitigation increase, participants reduce their mitigation). This substitution is less intense if the initial atmospheric quality is negative.

Evolutionary Characteristics of Urban Public Space Accessibility for Vulnerable Groups from a Perspective of Temporal–Spatial Change: Evidence from Nanjing Old City, China

Social equity/inequity and equal/unequal rights to the city extend beyond the distribution of urban parks and green spaces, necessitating research on equitable accessibility to encompass a broader range of public spaces. However, previous research has predominantly focused on green spaces, neglecting other types of public spaces. To address this gap, the present study takes the public space pattern of Nanjing Old City as the research object, employing the minimum distance method, the gravity potential method, and bivariate local Moran’s I to evaluate the matching relationship between the demand of socially vulnerable groups and the supply of public spaces, as well as its temporal–spatial evolution from 2010 to 2020. The results reveal spatial heterogeneity in the accessibility of public spaces for vulnerable groups at the block level, with 28.1% of the total number of blocks and 22.1% of the total area of blocks experiencing a supply–demand imbalance in 2010. From 2010 to 2020, under the rapid urban development, construction of public spaces, and the general decline in population density and proportion of vulnerable populations, the supply–demand imbalance has exacerbated the distribution of public spaces at both individual and aggregate levels. This imbalance is reflected in the deteriorated accessibility of public spaces for vulnerable groups. This study reveals the mismatches between development, population movement, and public space construction in the old city of Nanjing over the past decade, providing decision-making suggestions and foundations for the future optimization of public spaces, thereby offering an effective tool for assessing and improving the accessibility and equitable distribution of public spaces based on the needs of vulnerable groups.

The relationship between telemedicine tools and physician satisfaction, quality of care, and patient visits during the COVID-19 pandemic

ObjectiveThe objective of our study is to investigate the impacts of telemedicine technology and its specific tools on physicians’ overall satisfaction, quality of care, and percentage of patient visits in ambulatory care settings after the COVID-19 lockdowns. Materials and methodsData for our analysis was sourced from the 2021 annual National Electronic Health Records Survey (NEHRS), which included 1,875 complete questionnaire responses from physicians in the 2021 NEHRS. We used regression models to test the effects of telemedicine on physicians’ overall satisfaction, quality of care, and percentage of patients’ visits. ResultsWe report that telemedicine technology has significant positive effects on physicians’ satisfaction with telemedicine and quality of care evaluation, both at an aggregate level and at the disaggregate levels of individual telemedicine features, and partially significant effects on patients’ telemedicine visits. DiscussionTelemedicine features that contributed significantly to physician satisfaction and quality of care evaluation were telephone, videoconferencing, standalone telemedicine platform, and telemedicine platform integrated with EHR, while only telephone and integrated telemedicine platform contributed significantly to patients’ telemedicine visits. ConclusionFor telemedicine research and practice, this study confirms that telemedicine improves physician satisfaction and quality of care perceptions and will therefore be preferred by physicians. However, telemedicine has a mixed impact on percentage of patient visits, which suggests that providers may have to work harder to regularize telemedicine acceptance among patients in the post-COVID era.

Multi-level analysis of access to drinking water in rural communes in the south of the Kaffrine region, Senegal

In Senegal, there are disparities in access to drinking water at several levels. There are major differences between urban and rural areas. In rural areas, poverty, the abundance or scarcity of water infrastructure, and the distance between the place of residence and the place of supply are, to some extent, factors in the disparity in rates of access to drinking water from one village to another and, within the same village, from one household to another. Determining the sources of variance between villages and households regarding access to drinking water is based on the identification of several explanatory variables, both at the aggregate level (village level) and at the individual level (household level). Multilevel analysis has shown that differences in household access to drinking water are due to several factors that can be grouped into two categories: contextual variables that vary from one village to another, and individual characteristics that differ from one household to another. The aim of this article is to analyze the factors that explain the disparity in access to drinking water in rural communes in the south of the Kaffrine region. The usefulness of multilevel analysis lies in its ability to solidify causal inference in the associations between the infrastructural levels of villages, in terms of water facilities, and their impact on the level of access to drinking water of rural households as reported (Bringe and Golaz in Manuel pratique d’analyse multiniveau, Ined Éditions, Aubervilliers, 2017), as reported (Diane et al., in Analyse multiniveau pour expliquer la prévalence d’impacts sanitaires néfastes autorapportés et l’adaptation lorsqu’il fait très chaud et humide en été dans les secteurs les plus défavorisés des neuf villes les plus populeuses du Québec en 2011, 2015).

Chinese FDI outflows and host country environment

This study provides first evidence on the effects of Chinese FDI (Foreign Direct Investment) outflows on host country environments. The study draws upon a comprehensive dataset covering aggregate Chinese FDI outflows and sector specific data into 65 host nations over the 2007–2019 period. Employing a STIRPAT (Stochastic Regression on Population, Affluence and Technology) model and several different techniques including DID (Difference-in-Difference), pooled OLS (Ordinary Least Squares), quantile regression, IV (Instrumental Variable) estimation, threshold and Tobit regression, the findings suggest that Chinese FDI leads to an increase in host country CO2 (Carbon Dioxide) emissions, aligning with the pollution haven hypothesis at the aggregate level. A closer investigation at the development regime and sectoral levels indicates that in the low development regime, FDI inflows into the financial and real estate sector increase emissions. Conversely in the high-income regime, Chinese FDI into the entertainment sector is associated with an increase in carbon emissions. Chinese FDI is further found to lead to an increase in emissions in countries with a per capita GDP (Gross Domestic Product) of below USD72041.7. However, as per capita income rises above USD72041.7, FDI leads to a fall in carbon emissions.

Improving financial productivity and upgrading in global value chains

This study integrates the financial productivity improvement in a multi–country, multi–sector Ricardian model to examine its impact on China's position within global value chains (GVC). We also differentiate between the trade elasticities of the financial sector concerning intermediate inputs and final consumption. Through counterfactual analysis, our research reveals a consistent upward trajectory in China's GVC positioning at aggregate and sectoral levels that is attributable to financial productivity improvement. This ascent is facilitated by input–output links and cost-saving effects. The findings validate the significance of financial productivity improvement in advancing China's GVC positioning.

Ensemble learning algorithms to elucidate the core microbiome's impact on carbon content and degradation properties at the soil aggregate level

Soil aggregates are crucial for soil organic carbon (OC) accumulation. This study, utilizing a 32-year fertilization experiment, investigates whether the core microbiome can elucidate variations in carbon content and decomposition across different aggregate sizes more effectively than broader bacterial and fungal community analyses. Employing ensemble learning algorithms that integrate machine learning with network inference, we found that the core microbiome accounts for an average increase of 26 % and 20 % in the explained variance of PCoA and Adonis analyses, respectively, in response to fertilization. Compared to the control, inorganic and organic fertilizers decreased the decomposition index (DDI) by 31 % and 38 %, respectively. The fungal core microbiome predominantly influenced OC content and DDI in larger macroaggregates (>2000 μm), explaining over 35 % of the variance, while the bacterial core microbiome had a lesser impact, explaining <30 %. Conversely, in smaller aggregates (<2000 μm), the bacterial core microbiome significantly influenced DDI (R2 > 0.2), and the fungal core microbiome more strongly affected OC content (R2 > 0.3). Mantel tests showed that pH is the most significant environmental factor affecting core microbiome composition across all aggregate sizes (Mantel's r > 0.8, P < 0.01). Linear correlation analysis further confirmed that the core microbiome's community structure could accurately predict OC content and DDI in aggregates (R2 > 0.8, P < 0.05). Overall, our findings suggested that the core microbiome provides deeper insights into the variability of aggregate organic carbon content and decomposition, with the bacterial core microbiome playing a particularly pivotal role within the soil aggregates.

Mechanistic Insight into Intestinal α-Synuclein Aggregation in Parkinson's Disease Using a Laser-Printed Electrochemical Sensor.

Aggregated deposits of the protein α-synuclein and depleting levels of dopamine in the brain correlate with Parkinson's disease development. Treatments often focus on replenishing dopamine in the brain; however, the brain might not be the only site requiring attention. Aggregates of α-synuclein appear to accumulate in the gut years prior to the onset of any motor symptoms. Enteroendocrine cells (specialized gut epithelial cells) may be the source of intestinal α-synuclein, as they natively express this protein. Enteroendocrine cells are constantly exposed to gut bacteria and their metabolites because they border the gut lumen. These cells also express the dopamine metabolic pathway and form synapses with vagal neurons, which innervate the gut and brain. Through this connection, Parkinson's disease pathology may originate in the gut and spread to the brain over time. Effective therapeutics to prevent this disease progression are lacking due to a limited understanding of the mechanisms by which α-synuclein aggregation occurs in the gut. We previously proposed a gut bacterial metabolic pathway responsible for the initiation of α-synuclein aggregation that is dependent on the oxidation of dopamine. Here, we develop a new tool, a laser-induced graphene-based electrochemical sensor chip, to track α-synuclein aggregation and dopamine level over time. Using these sensor chips, we evaluated diet-derived catechols dihydrocaffeic acid and caffeic acid as potential inhibitors of α-synuclein aggregation. Our results suggest that these molecules inhibit dopamine oxidation. We also found that these dietary catechols inhibit α-synuclein aggregation in STC-1 enteroendocrine cells. These findings are critical next steps to reveal new avenues for targeted therapeutics to treat Parkinson's disease, specifically in the context of functional foods that may be used to reshape the gut environment.

CuO/NiO nanocomposite prepared with Saussurea costus extract for super-capacitor energy storage application

This work reports a green synthesis of CuO/NiO nanocomposite with different CuO/NiO ratios. The X-ray diffraction (XRD) confirmed the existence of both CuO and NiO. This was also confirmed by energy dispersive X-ray (EDX). Scanning electron microscopy (SEM) reveals that changing the compositions of the nanocomposites resulted in different surface morphologies with different particle shapes, sizes, and levels of aggregation. Nitrogen adsorption-desorption analysis showed microporous structures with pore size in the range of 1.66-1.75 nm and surface area in the range of 82-513 m2g−1. The supercapacitive activity was examined by cyclic voltammetry (CV) and galvanostatic charge-discharge (GCD). The results display that the 1C3N exhibited the highest capacitive performance of 1072 Fg−1 compared to 760, 716, and 260 Fg−1 for 3C1N, 4 N, and 4 C, respectively. Furthermore, the 1C3N electrode shows a cyclic stability of 72% after 4000 cycles, which makes it a promising candidate for supercapacitive applications.