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In the pursuit of global net-zero emissions targets and cleaner combustion technologies, researchers are increasingly turning to innovative solutions. Ammonia, as a carbon-free fuel, holds promise for achieving low emissions and efficient combustion. This study explores the potential synergies of various ammonia shares (20 %, 40 %, and 60 %) combined with Citronella biofuel in a Low-Temperature Combustion (LTC) Reactivity Controlled Compression Ignition (RCCI) engine. Comparative analysis between a 40 % ammonia blend Citronella biofuel (A40) and a Standard Diesel (SDL) in an RCCI engine demonstrates significant reductions in oxides of nitrogen (by 17 %), carbon dioxide (by 6.6 %), and smoke (by 9.8 %), along with a notable enhancement in Brake Thermal Efficiency (BTE) by 5.4 % for A40. The validation of results using an Artificial Neural Network (ANN) model shows robust coefficients of determination (97 %), high R values (0.9945–0.9995), and low Root Mean Square Error values (ranging from 0.0219 to 0.0483). These findings strongly support the efficacy of the A40 blend, positioning it as a promising and viable alternative fuel for achieving cleaner combustion in LTC-RCCI engines.

In this study, plastic waste was efficiently converted into valuable energy resources using a unique pyrolysis technique. A carbon-metal oxide hybrid nanocomposite was introduced as a catalyst, and analyses of structural and surface morphology were conducted. Pyrolysis process parameters such as temperature (PTemp), process time (PTime), and catalyst concentration (CC) were optimized through response surface methodology for a higher yield of energy resources. Char underwent proximate and ultimate analyses, oil underwent physicochemical and Fourier transform infrared analyses, and syngas composition was determined. Optimal conditions were found: PTemp 300 °C, PTime 60 min, CC 1 % for char; PTemp 465 °C, PTime 150 min, CC 1 % for oil; PTemp 550 °C, PTime 60 min, CC 4 % for syngas. Compared to the ZSM-5 catalyst, char, oil, and syngas yields increased by 7.9 %, 10.8 %, and 7.2 %, respectively, at optimum conditions. These findings suggest that waste plastic pyrolysis can effectively meet energy demands with enhanced energy outputs.

With the increasing demand for sustainable and renewable energy sources, biodiesel has emerged as a promising alternative to conventional fossil fuels. This study presents a novel approach to enhancing Thevetia peruviana biodiesel (TPB) yield from plant waste by optimizing process variables using Zinc sulfide (ZnS) as a catalyst. Co-precipitation was utilized to synthesize the ZnS nanoparticles, followed by comprehensive characterization using SEM, XRD, EDAX, and FTIR. Response surface methodology was employed to determine optimal values for process parameters, specifically catalyst concentration (CC), oil-to-alcohol ratio (OAR), and process temperature (PT). The results demonstrate that the nanoparticle can be effectively reused over five successive cycles without significant loss of catalytic activity. The optimal condition identified was a CC of 107.7 ppm, OAR of 8.9:1, and PT of 94.6 °C, yielding a TPB of 92.5 %, which was validated through confirmation experiments. The yield of TPB using the nanocatalyst exhibited a 3.6 % increase compared to a typical chemical catalyst. ANOVA results revealed that CC had a 43.9 % influence on biodiesel yield, while OAR and PT had influences of 33.2 % and 22.9 %, respectively. Elemental analysis indicated that TPB biodiesel has a 10.9 times higher oxygen concentration compared to diesel fuel, with GC-MS analysis identifying linoleic acid as the predominant component. The elemental, FTIR, GC-MS, and physicochemical analysis of TPB were found to be comparable to the biodiesel standard. This comprehensive assessment suggests that TPB has the potential to serve as a viable alternative to conventional diesel fuel.

This study focuses on optimizing the concentrations of water and 1-pentanol in biodiesel-diesel blends derived from Gossypium hirsutum (cottonseed) oil to enhance engine performance and reduce environmental impact. Biodiesel from cottonseed oil (COB) was produced via transesterification, followed by an analysis of its elemental and chemical composition, and physicochemical properties. Using a Box-Behnken design matrix, the volume concentrations of COB (10–30 %), water (5–15 %), and 1-pentanol (5–20 %) in diesel fuel were varied to optimize engine performance and emission characteristics. ANOVA was employed to evaluate the influence of these parameters on key output responses. The results demonstrated that COB possesses favorable elemental and chemical properties, and the optimal concentrations of COB, water, and 1-pentanol were identified as 14.7 %, 9.9 %, and 11.2 %, respectively. ANOVA findings revealed that COB had the maximum influence on brake specific fuel consumption (93.4 %), nitrogen oxides (55.3 %), carbon monoxide (78.5 %), and carbon dioxide (97.1 %), while 1-pentanol significantly influenced brake thermal efficiency (38.9 %) and hydrocarbon emissions (70 %). Confirmation experiments validated these optimizations, showing substantial improvements in both performance and emissions. The study concludes that integrating water and 1-pentanol into COB blends can reduce fossil fuel consumption by approximately 35 %, while enhancing energy efficiency and minimizing environmental impact.

The increasing concern over environmental pollution and energy security has intensified the search for alternative fuels. This study explores the impact of 1-pentanol blends on the combustion performance and emission characteristics of water-emulsified Gossypium hirsutum (cottonseed) oil biodiesel in a compression ignition engine. Cottonseed oil was converted into biodiesel via transesterification, and its elemental, chemical, and physicochemical properties were thoroughly analyzed. A key contribution of this work is the formulation of a fuel blend comprising 30 % cottonseed oil biodiesel (COB) by volume mixed with diesel fuel, further emulsified with 10 % water by volume. The water-emulsified biodiesel was then enhanced with a 10 % volume concentration of 1-pentanol. The energy and environmental performance of these test fuels were evaluated in a single-cylinder compression ignition engine under various operating conditions. The study's findings reveal that the alcohol-blended, water-emulsified biodiesel significantly improves combustion efficiency and reduces emissions compared to conventional diesel fuel. Notably, the addition of 10 % 1-pentanol to the water-emulsified biodiesel led to a 14.3 % reduction in hydrocarbon emissions and a 12.8 % reduction in carbon monoxide emissions. Furthermore, there was a 3.2 % improvement in brake thermal efficiency and a 1.4 % decrease in specific fuel consumption. This research demonstrates that blending alcohol with water-emulsified biodiesel not only enhances combustion efficiency but also offers a promising strategy for reducing the environmental impact of diesel engines and potentially lowering fossil fuel dependence by 50 %.

The study explores the impact of a zinc oxide (ZnO) induced carbon nanotube (CNT) nanocomposite on ammonia decomposition in aqueous ammonia (AA) emulsified diesel fuel, while evaluating performance and emissions. Functionalized CNTs induced with ZnO underwent structural and surface morphology analysis. Different concentrations of ammonium hydroxide (5 % and 10 %) were mixed with plain diesel fuel (PDF), and 100 ppm of ZnO/CNT was blended with 10 % AA emulsified fuel. Fuel performance was assessed under various brake power conditions compared to PDF. The results demonstrate that the absorption of latent heat by ammonia and its higher decomposition energy result in a longer ignition delay, thereby increasing peak in-cylinder pressure and net heat release rate. The post-combustion reaction of AA emulsified fuels contributes to increased brake specific fuel consumption (BSFC), brake specific energy consumption (BSEC), hydrocarbon (HC), carbon monoxide (CO), and smoke opacity. However, the dispersion of nanocomposite in AA emulsion enhances the catalytic effect and promotes ammonia decomposition, resulting in combustion characteristics similar to PDF. Notably, there is an observed improvement in BSFC by 8.1 % and BSEC by 10.9 %, respectively. Furthermore, emission metrics such as oxides of nitrogen, HC, CO, and smoke opacity decrease by 4.5 %, 18.8 %, 11.4 %, and 5 %, respectively.

Sustainable energy production from plant waste and non-edible seeds offers a promising pathway towards mitigating climate change, reducing environmental impact, promoting economic development, and enhancing energy security. Although several research works have focused on the conversion of Bauhinia seed waste to biooil as a sustainable energy, none of the studies attempted to improve its overall performance through fuel modification and parameter optimization. This study proposes a novel approach by blending water and 2-Ethylhexyl nitrate (2-EHN) into Bauhinia racemose biodiesel (BRD) to minimize emissions and enhance performance. The biodiesel properties were characterized by Fourier-transform infrared and Gas chromatography-mass spectrometry analysis. The optimum levels of fuel modification parameters, such as BRD, water, and 2-EHN in conventional diesel fuel (CD), were obtained using response surface methodology, branding it as a sustainable and greener energy source for engine applications. Box-Behnken design matrix was chosen to categorize input factors, levels, and output responses. Examination of the biodiesel reveals that carbon-based constituents make a significant contribution, and the physicochemical properties align with ASTM standards. The optimization results indicate that the optimum levels of BRD, water, and 2-EHN in CD are 20.33 %, 10.26 %, and 2.05 %, respectively. The performance and emission metrics closely match the projected values. An in-depth examination of combustion, engine vibration, life-cycle assessment, and techno-economic analysis provides further evidence to reinforce the findings and suggests possible avenues for future research.

The accumulation of plastic waste poses a major environmental challenge, while the conversion of waste plastics into oil via pyrolysis holds promise as an alternative energy solution. Despite numerous investigations into this area, none have focused on optimizing pyrolysis process parameters for higher oil yield and enhancing the overall performance of plastic oil through suitable fuel modification. The present study aims to optimize the pyrolysis process parameters, including heating rate (HR), process temperature (PT), and reaction time (RT), to achieve a higher yield of waste plastic oil (WPO) and enhance the overall performance by blending optimal quantities of water. Fuel characterization and properties measurement were conducted using Fourier Transform Infrared and ASTM methods. WPO was blended with conventional diesel fuel (CDF) and different volume concentrations of water (5%, 10%, and 15%). The performance metrices were assessed under various engine conditions. The study findings indicate that the optimum condition of process parameters is an HR of 17.3 °C/min, PT of 403 °C, and RT of 96.30 min, and the fuel quality confirms its suitability as an alternative fuel source. The performance metrics revealed that WPO has a 5.4% lower brake-thermal efficiency than CDF, and the inclusion of 10% water in WPO (WPO10W) enhances the efficiency by 11.5%. The in-cylinder pressure and net-heat release rate of WPO are 1.3% and 12.9% lower than CDF, respectively, and WPO10W emulsion promotes efficient combustion. WPO10W emulsion fuel reduces oxides of nitrogen, hydrocarbon, and carbon monoxide emissions by 21.2%, 9.8%, and 22.2%, respectively, compared to WPO.

In this study, an aqueous ammonia emulsion and a zinc sulfide/copper (ZnS/Cu) nanocomposite were blended with an algae biodiesel-diesel blend, and the optimum levels of parameters were identified for enhanced performance and reduced emissions. The algae were cultivated concurrently with wastewater treatment, and the biodiesel's properties as well as the nanocomposite's structural and surface morphology were analyzed. Response surface methodology was employed for optimization, and confirmation tests were conducted. The results indicate that algae cultivation effectively removes wastewater nutrients, and the optimal values of process parameters were determined to be 10% biodiesel, 14% aqueous ammonia, and 95 ppm of ZnS/Cu.

This work utilized Real-Time Emulsion Fuel Injection (RTEFI) methods to incorporate emulsion fuel, which included citronella oil (20%), ammonia (10%), and water (5%), into diesel fuel without the addition of surfactants. The primary aim of this study was to investigate the influence of hydrogen presence in liquid ammonia on diesel engines. This was accomplished by using a water-emulsified diesel-biodiesel blend and forecasting performance using an artificial neural network (ANN). Citronella oil (20%) was blended with standard fuel (SD), followed by the addition of 10% ammonia and 5% water, labeled as SD20CO, SD20CO10A, and SD20CO10A5W, respectively. The results indicated that the brake thermal efficiency of SD20CO10A5W is comparable to that of diesel. The fuel combination significantly decreased hydrocarbon emissions by 70–75%, smoke by 10–15%, and oxides of nitrogen by 2–5%, while increasing carbon dioxide by 3–8% under all load situations compared to other fuels. The trained ANN models had a coefficient of determination of 97%, with values ranging from 0.9076 to 0.9965. Additionally, the models exhibited low mean absolute percentage error values, ranging from 0.98% to 4.26%. The analytical results provide strong evidence supporting the efficacy of SD20CO10A5W, ultimately indicating that it is a feasible substitute fuel for diesel engines.

Efficiently managing agricultural plant residues is a growing concern, leading to a focus on converting waste materials into valuable resources. The Rutaceae family, especially Citrus maxima peel oil (CMPO), has potential for biofuel production, but research on its use remains limited, especially in terms of fuel modification. This study aims to extract biofuel from Citrus maxima peel and characterize its chemical components. To enhance efficiency and align with environmental goals, the study suggests integrating water and a nanocomposite into CMPO. An eco-friendly method was employed to synthesize a carbon nanotube (CNT)-induced magnesium oxide (MgO) nanocomposite that was extensively characterized. Fuel combinations were derived using a Box-Behnken design matrix, and optimization followed, emphasizing performance and emission parameters. Analysis of the elemental composition and free fatty acid profile of extracted CMPO highlights its potential as an alternative fuel. Optimal concentrations of CMPO, water, and nanocomposite in diesel fuel were found to be 27.6%, 12.2%, and 64.9 ppm, respectively. Confirmation tests validated improved performance and emission outcomes under these optimal conditions. Projected performance and emission parameters closely align with experimental findings. The proposed fuel combination is expected to achieve a significant 40% reduction in the demand for petroleum derivatives.

Background: Because of their regular isolation, patients with COVID-19 had high levels of anxiety and irregular sleep patterns. Certain sleep-enhancing medications may hinder the aerobic system and exacerbate the illness. lengthen the bedside, which could increase the risk of medical infections. Objective: To determine how COVID-19 survivors’ anxiety and sleep quality are affected by progressive muscle relaxation. Methods: A total of 146 Jordanian patients who were admitted to the isolation suite were chosen at random to be placed in the experimental and control groups. For five days in a row, the experimental group used progressive muscle relaxation (PMR) technology for 30 min each day. The control group received only standard medical attention and medication. The Spielberg State-Trait Anxiety Scale (STAI) and Sleep State Self Rating Scale (SRSS) were used to measure patient anxiety and sleep quality before and after the intervention. Ultimately, SPSS 25.0 was used to analyze the data. Results: Prior to intervention, the average anxiety score (STAI) was not statistically significant (P = 0.89); however, following the intervention, it became statistically significant (P < 0.05). Prior to interventions, the two groups’ average sleep quality scores (SRSS) were not statistically significant (P = 0.71), but they were after the interventions (P