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Apple pomace constitutes a major waste stream of the food processing industry that is characterized by high concentrations of free sugars and structural carbohydrates. This study comparatively explored alternative apple pomace valorization strategies. To this regard, the integration of hydrothermal and organic acid pretreatment as a strategy to enhance anaerobic digestion biomethane yield and alternative production of mycoprotein as a valuable secondary product via the use of Aspergillus oryzaeand Neurospora intermediaedible fungi were investigated. In scenario 1, both pretreatment liquors and solid residues underwent anaerobic digestion to produce biomethane. In scenario 2, pretreatment liquors and solid residues underwent fungal cultivation and anaerobic digestion, respectively. Additionally, to optimize bioenergy yield and minimize wastewater generation in scenario 2, the fungal growth effluent was also subjected to anaerobic digestion. In scenario 1, employing methane for transportation showed the potential to decrease GHG by 314.8 kt CO2eq, translating to US$72.4 million in social cost savings. Similarly, in scenario 2, replacing edible fungal biomass in the food market could lead to a substantial reduction in emissions by 824.2 kt CO2eq and a corresponding US$227.0 million in social cost savings.

Hydrogen, valued for its high energy density and environmental friendliness, stands out as a promising energy carrier. Traditional storage methods, such as high-pressure gas cylinders and cryogenic liquid tanks, face challenges related to transportation risks, low energy efficiency, and economic feasibility. In this context, solid-state materials, particularly carbonaceous nanomaterials, have gained prominence as alternatives for hydrogen storage due to their notable capacity, cost-effectiveness, and reliability. However, the identification of efficient carbonaceous adsorbents presents challenges, requiring expensive and time-consuming experimental efforts. This study introduces a machine learning (ML) model designed to predict hydrogen storage capacity in functionalized carbonaceous nanomaterials. Leveraging the ability of ML technology to unravel complex relationships within extensive datasets, the collected comprehensive dataset undergoes rigorous statistical analysis and mechanistic discussions. Feature importance analysis is used to provide insights into the influence of input features on hydrogen storage capacity. The Gaussian process regression model emerges as a standout performer, achieving impressive metrics with an R2 > 0.955, RMSE < 0.121, and MAE < 0.064 for hydrogen adsorption/desorption during the testing phase. The impact of pressure and temperature on hydrogen adsorption, along with pressure and sorbent average crystal size for hydrogen desorption, is elucidated. This ML model has the potential to revolutionize the identification of optimal material properties and processing conditions for hydrogen adsorption in carbonaceous nanomaterials, offering significant time and cost savings.

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Self-powered sensing systems augmented with machine learning (ML) represent a path toward the large-scale deployment of the internet of things (IoT). With autonomous energy-harvesting techniques, intelligent systems can continuously generate data and process them to make informed decisions. The development of self-powered intelligent sensing systems will revolutionize the design and fabrication of sensors and pave the way for intelligent robots, digital health, and sustainable energy. However, challenges remain regarding stable power harvesting, seamless integration of ML, privacy, and ethical implications. In this review, we first present three self-powering principles for sensors and systems, including triboelectric, piezoelectric, and pyroelectric mechanisms. Then, we discuss the recent progress in applied ML techniques on self-powered sensors followed by a new paradigm of self-powered sensing systems with learning capability and their applications in different sectors. Finally, we share our outlook of potential research needs and challenges presented in ML-enabled self-powered sensing systems and conclude with a road map for future directions.

Ammonia, a cost-effective hydrogen carrier, holds the potential for hydrogen production through decomposition, where catalysts play a pivotal role in lowering the decomposition temperature. However, identifying suitable catalysts involves expensive and time-consuming experiments. Machine learning (ML) emerges as a powerful solution to address challenges in catalytic ammonia decomposition. This study focuses on creating an ML model to predict ammonia decomposition. A comprehensive database is compiled and statistically analyzed to discern correlations between descriptors and responses. Employing random forest regression, support vector machine, and gradient boost regression models, the study models the ammonia decomposition process as a function of catalyst properties and reaction conditions. Feature importance analysis evaluates the influence of descriptors on responses. The results unveil a robust positive correlation between ammonia decomposition and reaction temperature. Improved ammonia decomposition and hydrogen formation rates are achievable with a total metal loading below 20 %. The gradient boost regression tree model exhibits satisfactory performance during testing (R2 > 0.85, RMSE <13.24, and MAE < 10.31). Notably, reaction temperature and gas hourly space velocity emerge as the two most influential descriptors impacting ammonia conversion and hydrogen formation rate. This research underscores the efficacy of ML in addressing challenges in catalytic ammonia decomposition, providing valuable insights for the advancement of hydrogen production.

For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section.

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•Exergy-based sustainability assessment of a batch bioreactor for acetate and ethanol fermentation from syngas.•Application of exergy and eco-exergy approaches for decision-making on syngas pressure.•1.8atm syngas initial pressure as the best condition for acetate and ethanol synthesis.•Potential application of exergy-based framework for sustainability and productivity of biofuels production.

A systematic optimization process for simple and eco-friendly extracellular biosynthesis of gold nanoparticles by a native thermophilic Ureibacillus thermosphaericusstrain thermo-BF isolated from geothermal hot springs has been presented. Biosynthesis reactions were conducted using the culture supernatant at different temperatures (60–80 °C) and pH (6–9) with gold ion concentration ranging from 0.001 to 0.1 M. The results obtained showed that pure spherical nanoparticles in the range of 35–75 nm were produced, and the maximum nanoparticle production was achieved using 0.001 M HAuCl4at 80 °C, pH 9. Genome mining and profiling of the genes encoding bioreducing enzymes in U. hermosphaericusstrain thermo-BF revealed evidences indicating sulfur reduction capability of this bacterium. Overall, the findings of this study confirmed the great biocatalyzing potential of the extermophilic U. thermosphaericusstrain thermo-BF supernatant for intensified biosynthesis of gold nanoparticle under extreme conditions.

Organophosphorus (OP) compounds are extensively used in agricultural practice for pest management. However, their residues have a long half-life in the ecosystem as well as in the agro-products, posing a serious threat to human and animal health. Aryldialkylphosphatase (EC 3.1.8.1) is widely used in detoxification procedures. In the present study, aryldialkylphosphatase was immobilised on synthesised cross-linked nano-sized gel particles, also known as nanogels, in order to enhance the enzyme’s physicochemical properties. Accordingly, a new nanogel consisting of chitosan and myristic acid (CMA nanogel) was synthesised and characterised by way of Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The aryldialkylphosphatase-CMA nanogel conjugate was then assayed by FTIR, and its physicochemical characteristics were also investigated. The data obtained from SEM and TEM showed the nanogels to be homogenous spherical particles less than 50 nm in diameter. The proper formation of the nanogel and nanobioconjugate was also confirmed by FTIR spectra. In comparison with the free enzyme, the pH and thermal stability of the aryldialkylphosphatase were enhanced by the covalent immobilisation. Moreover, the immobilised enzyme could maintain approximately half of its activity over more than one month. The kinetic parameters of the aryldialkylphosphatase- CMA nanogel conjugate were also shown to undergo remarkable improvements, hence the synthesised CMA-nanogel could act as a promising support for aryldialkylphosphatase immobilisation. It is suggested that the aryldialkylphosphatase-CMA nanogel could be used for detoxifying paraoxon; a nerve agent. Further clinical experiments are underway.

Organophosphorus (OP) compounds are extensively used in agricultural practice for pest management. However, their residues have a long half-life in the ecosystem as well as in the agro-products, posing a serious threat to human and animal health. Aryldialkylphosphatase (EC 3.1.8.1) is widely used in detoxification procedures. In the present study, aryldialkylphosphatase was immobilised on synthesised cross-linked nano-sized gel particles, also known as nanogels, in order to enhance the enzyme’s physicochemical properties. Accordingly, a new nanogel consisting of chitosan and myristic acid (CMA nanogel) was synthesised and characterised by way of Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The aryldialkylphosphatase-CMA nanogel conjugate was then assayed by FTIR, and its physicochemical characteristics were also investigated. The data obtained from SEM and TEM showed the nanogels to be homogenous spherical particles less than 50 nm in diameter. The proper formation of the nanogel and nanobioconjugate was also confirmed by FTIR spectra. In comparison with the free enzyme, the pH and thermal stability of the aryldialkylphosphatase were enhanced by the covalent immobilisation. Moreover, the immobilised enzyme could maintain approximately half of its activity over more than one month. The kinetic parameters of the aryldialkylphosphatase-CMA nanogel conjugate were also shown to undergo remarkable improvements, hence the synthesised CMA-nanogel could act as a promising support for aryldialkylphosphatase immobilisation. It is suggested that the aryldialkylphosphatase-CMA nanogel could be used for detoxifying paraoxon; a nerve agent. Further clinical experiments are underway.

AbstractThe membrane distillation (MD) process is an emerging and under-developed technique, which is currently investigated for various applications, e.g. desalination and wastewater treatment. As specific membranes for MD are not yet commercially available, most of the applied membranes for MD experiments are those microfiltration membranes made of hydrophobic polymers. Characterization of such kinds of membranes is important in order to achieve a better and clearer understanding of their performance, which helps to fabricate specific membranes for the MD process. In this work, atomic force microscopy, which is a high-resolution technique and newly applied for characterization of MD membranes, has been used for the topographical study of different polytetrafluoroethylene membranes, which are typically recommended for various MD applications. The membranes were characterized for their pore size, pore size distribution, surface roughness, and nodule aggregate. Moreover, the other two important specifications, liquid entry pressure and surface hydrophobicity, were measured and compared. A sweeping gas MD experimental setup was used for solute rejection evaluation of the applied membranes by use of four different feed samples.

The membrane distillation (MD) process is an emerging and under-developed technique, which is currently investigated for various applications, e.g. desalination and wastewater treatment. As specific membranes for MD are not yet commercially available, most of the applied membranes for MD experiments are those microfiltration membranes made of hydrophobic polymers. Characterization of such kinds of membranes is important in order to achieve a better and clearer understanding of their performance, which helps to fabricate specific membranes for the MD process. In this work, atomic force microscopy, which is a high-resolution technique and newly applied for characterization of MD membranes, has been used for the topographical study of different polytetrafluoroethylene membranes, which are typically recommended for various MD applications. The membranes were characterized for their pore size, pore size distribution, surface roughness, and nodule aggregate. Moreover, the other two important specifications, liquid entry pressure and surface hydrophobicity, were measured and compared. A sweeping gas MD experimental setup was used for solute rejection evaluation of the applied membranes by use of four different feed samples.

ABSTRACTElectrospun polymeric membranes are currently being developed for various applications due to their unique specifications in comparison with the conventional membranes. As electrospun membranes comprise nanostructures (with 3D structure and inter-connected pores) with dimensions lying within the lateral resolution of the microscope, the interpretation of electrospun membrane features is challenging. In this study, scanning electron microscopy and atomic force microscopy were used for characterization of an electrospun (N1) and two commercial membranes (N2 and N3). A self-supported electrospun nanofibrous nylon membrane was fabricated and characterized for pore size, pore size distribution, thickness, nodule size, and pure water permeation flux as well as rejection and flux decline during coke removal from a typical petrochemical wastewater stream. The obtained results show that the electrospun membrane had smoother surface. All membranes showed same separation performance, about 99% rejection, but higher permeation flux achieved for the electrospun membrane.

Electrospun polymeric membranes are currently being developed for various applications due to their unique specifications in comparison with the conventional membranes. As electrospun membranes comprise nanostructures (with 3D structure and inter-connected pores) with dimensions lying within the lateral resolution of the microscope, the interpretation of electrospun membrane features is challenging. In this study, scanning electron microscopy and atomic force microscopy were used for characterization of an electrospun (N1) and two commercial membranes (N2 and N3). A self-supported electrospun nanofibrous nylon membrane was fabricated and characterized for pore size, pore size distribution, thickness, nodule size, and pure water permeation flux as well as rejection and flux decline during coke removal from a typical petrochemical wastewater stream. The obtained results show that the electrospun membrane had smoother surface. All membranes showed same separation performance, about 99% rejection, but higher permeation flux achieved for the electrospun membrane.

Each year, millions of tons of halal food wastes are being disposed into the environment through land-filling or illegal dumping activities. Currently, the government has no other cheaper and easier options than landfill. Dumping of organic waste materials into the environment will partly contribute to the global warming phenomenon due to methane gas generation through anaerobic process, occurred inside the landfill or river bed. Methane gas has 21 times higher global warming potential (GWP) than carbon dioxide and can severely affect the environment if not properly managed. Therefore this paper will highlight the concept of biorefinery to enhance the current state of halal food waste handling which include kitchen waste, waste cooking oil, food waste, landscaping and garden waste, wet market waste, night market waste, halal slaughterhouse waste, food processing facility waste and other types of halal waste. Through biorefinery complex these waste materials can be converted into value-added bioproducts such as biodiesel, biogas, bioethanol, animal feed, biofertilizer, bioplastic, biomaterial and others. This will enhance the food halal industry and also support the government aspiration towards achieving high income country.

Recently, application of ionic liquids due to their special solvency properties as a promising method of pretreatment for lignocellulosic biomass has received much attention. Chemical stability, temperature stability, non-flammability, low vapor pressure, wide liquidus range, and non-toxicity are among those unique properties. These solvents are also known as green solvents due to non-toxicity and low vapor pressure. The present study was set to compare the effect of five different ionic liquids namely, 1-ethyl-3-methyl imidazolium acetate, 1-ethyl-3-methyl imidazolium diethyl phosphate, 1-butyl-3-methyl imidazolium chlorides, 1,3-dimethyl imidazolium dimethyl phosphate, and 1-butyl-3-methylimidazolium-trifluoromethane sulfonate on barley straw in bioethanol production process. The performance of ionic liquids was evaluated based on the change observed in chemical structure, crystallinity index, and cellulose digestibility. Overall, 1-ethyl-3-methyl imidazolium acetate was found most effective in pretreating barely straw for bioethanol production. To the best of our knowledge, the present study reports different ionic liquids; some for the first time, for barely straw pretreatment.

ABSTRACTAs membrane distillation (MD) is an under-developed separation process, specific membranes for MD applications are not yet commercially available. Therefore, microporous polymeric membranes made of hydrophobic materials fabricated for microfiltration purposes are usually used for MD applications. Characterization of such kind of membranes is important in order to achieve a better in-depth understanding of their performance and to fabricate specific membranes for MD process. One of the emerging characterization methods is atomic force microscopy (AFM) analysis. AFM is a newly developed high-resolution method that is useful for studying the surface topography of various types of membranes, and 3D images of the membrane surface can be obtained directly without special sample preparation. Consequently, a truer and clearer surface structure of a polymeric membrane can be observed. In this work, AFM method has been used for characterization of three hydrophobic membranes (polytetrafluoroethylene, polypropylene, and polyvinylidene fluoride) which are typically used for various MD applications. The membranes were characterized for their pore size, pore size distribution, surface roughness, and hydrophobicity. A sweeping gas membrane distillation apparatus was used for solute rejection evaluation of the applied membranes.

As membrane distillation (MD) is an under-developed separation process, specific membranes for MD applications are not yet commercially available. Therefore, microporous polymeric membranes made of hydrophobic materials fabricated for microfiltration purposes are usually used for MD applications. Characterization of such kind of membranes is important in order to achieve a better in-depth understanding of their performance and to fabricate specific membranes for MD process. One of the emerging characterization methods is atomic force microscopy (AFM) analysis. AFM is a newly developed high-resolution method that is useful for studying the surface topography of various types of membranes, and 3D images of the membrane surface can be obtained directly without special sample preparation. Consequently, a truer and clearer surface structure of a polymeric membrane can be observed. In this work, AFM method has been used for characterization of three hydrophobic membranes (polytetrafluoroethylene, polypropylene, and polyvinylidene fluoride) which are typically used for various MD applications. The membranes were characterized for their pore size, pore size distribution, surface roughness, and hydrophobicity. A sweeping gas membrane distillation apparatus was used for solute rejection evaluation of the applied membranes.

Nanogenerators have attracted particular attention during the last decade. A nanogenerator harness mechanical or thermal energy to produce electricity without any need for battery. In this paper, general descriptions of different types of nanogenerators, including piezoelectric, triboelectric, and pyroelectric, are presented. Next, bibliometric analysis and unsupervised machine learning–based analysis (principle component analysis) are carried out to determine the trends in this field of science. The current developments and directions for technology commercialization are briefly discussed. Additionally, the output performance and environmental consequences of active materials used in nanogenerators are analyzed by principle component analysis. The analysis reveals China’s sensible investment in the nanogenerator field during the last five years. The number of articles published by Chinese scholars is over 1000 during 2015–2020 with a considerable distance from the USA. It is also deduced that European countries need to pay more attention to this field if they want to compete with the USA, China, and South Korea. Overall, due to the huge amount of waste thermal energy worldwide, more efforts and resources have to be focused and invested in developing pyroelectric nanogenerators. Moreover, there is a need to find low-cost materials having a favorable environmental profile to fabricate nanogenerators.

•Different types of food wastes (homogeneous and heterogeneous) are reviewed.•Processing of food wastes rich in carbohydrates into bioethanol is scrutinized.•Main constraints of the commercial food-waste-to-bioethanol process are highlighted.

•Concerns associated with sustainability of bioenergy product systems are reviewed.•Pros and cons of life cycle assessment in bioenergy product systems are discussed.•Consequential approach reflects environmental impacts of policies in bioenergy sector.•Developing data related to land-use change in bioenergy product systems is necessary.•Uncertainty overshadows results of life cycle assessment of bioenergy product systems.