Environmental Applications Research Articles

Advances in Aerosol Nanostructuring: Functions and Control of Next-Generation Particles.

Nanostructured particles (NSPs), with their remarkable properties at the nanoscale, possess key functions required for unlocking a sustainable future. Fabricating these particles using aerosol methods and spraying processes enables precise control over the particle morphology, structure, composition, and crystallinity during in-flight transformation. In this Perspective, the significant impact of NSPs on technological advancement for energy and environmental applications is discussed. Furthermore, incorporating in situ/operando assessment techniques alongside machine and deep learning is explored. Finally, the future development trends and the perspective on the advancing NSPs synthesis via aerosol process are elaborated for further driving innovations for supersmart and carbon-neutral society.

Hydrogel-based Soft Robotics for Surgical Machinery

Hydrogel-based soft robotics represent a transformative approach in surgical machinery, offering unparalleled adaptability, biocompatibility, and precision for minimally invasive procedures. Hydrogels, with their high water content and tunable mechanical properties, mimic soft biological tissues, making them ideal for applications in delicate surgical environments. This research explores the integration of hydrogel materials into soft robotic systems, focusing on their fabrication, actuation mechanisms, and performance in surgical applications. Key advancements include the development of stimuli-responsive hydrogels that enable precise control of movement and force, enhancing the capability to navigate complex anatomical structures. The study also examines computational models for simulating hydrogel behavior and optimizing robotic designs. While the potential benefits of hydrogel-based soft robotics in improving patient outcomes are significant, challenges remain in ensuring durability, scalability, and reliable control systems. This research aims to address these limitations by integrating advanced materials science with robotic engineering. By doing so, it contributes to the evolution of surgical technologies, paving the way for safer and more effective procedures.

Strain-engineered stretchable substrates for free-form display applications

With the growing potential of the Internet of Things, displays are being utilized to provide various types of information in every aspect of daily life, leading to the expansion of form-factor-free displays. Stretchable displays are considered the ultimate goal in form factor innovation, and they are not limited to rectangular shapes with deformation characteristics suited to target applications. Because reliable stretchable displays should be robust under uniaxial and biaxial strain, there have been efforts to tailor mechanical stress with promising strategies from structural and material perspectives. This review focuses on strain-engineering stretchable substrates for free-form display applications. First, we introduce deformable substrates with structural stretchability, achieved by incorporating buckling and Kirigami structures into plastic films, and we systematically analyze the tensile deformation characteristics based on design elements. In addition, we examined intrinsically stretchable elastomeric substrates, which have gained considerable attention due to recent advances in material and processing technologies. Their spatial modulus patterning is studied by applying optimized design principles, achieved through network alignment and crosslinking control in homogeneous elastomers, as well as by incorporating heterogeneous structures within the elastomer materials. Finally, we discussed state-of-the-art stretchable display applications employing strain-engineered stretchable substrates, focusing on advantageous materials and structures based on the display components, processes, and target deformation characteristics. Building on this foundation, we discuss the development of next-generation free-form displays and aim to contribute to their application in various static and dynamic deformation environments.

Causality-Driven Feature Selection for Calibrating Low-Cost Airborne Particulate Sensors Using Machine Learning

With escalating global environmental challenges and worsening air quality, there is an urgent need for enhanced environmental monitoring capabilities. Low-cost sensor networks are emerging as a vital solution, enabling widespread and affordable deployment at fine spatial resolutions. In this context, machine learning for the calibration of low-cost sensors is particularly valuable. However, traditional machine learning models often lack interpretability and generalizability when applied to complex, dynamic environmental data. To address this, we propose a causal feature selection approach based on convergent cross mapping within the machine learning pipeline to build more robustly calibrated sensor networks. This approach is applied in the calibration of a low-cost optical particle counter OPC-N3, effectively reproducing the measurements of PM1 and PM2.5 as recorded by research-grade spectrometers. We evaluated the predictive performance and generalizability of these causally optimized models, observing improvements in both while reducing the number of input features, thus adhering to the Occam’s razor principle. For the PM1 calibration model, the proposed feature selection reduced the mean squared error on the test set by 43.2% compared to the model with all input features, while the SHAP value-based selection only achieved a reduction of 29.6%. Similarly, for the PM2.5 model, the proposed feature selection led to a 33.2% reduction in the mean squared error, outperforming the 30.2% reduction achieved by the SHAP value-based selection. By integrating sensors with advanced machine learning techniques, this approach advances urban air quality monitoring, fostering a deeper scientific understanding of microenvironments. Beyond the current test cases, this feature selection method holds potential for broader applications in other environmental monitoring applications, contributing to the development of interpretable and robust environmental models.

Wood–Cement Composites: A Sustainable Approach for Mitigating Environmental Impact in Construction

The construction industry’s environmental impact has become a growing concern, largely due to the energy-intensive production of conventional building materials. This paper explores the potential of wood–cement composites as a more sustainable alternative through a comprehensive literature review, including a bibliometric and scientometric analysis of research trends. Our analysis traces the evolution of wood–cement composites from early studies focused on mechanical properties, to recent investigations into their environmental benefits and practical applications. Key findings suggest that optimal performance can be achieved by treating wood with tetraethyl orthosilicate, incorporating additives like cellulose nanocrystals or wollastonite, and using wood from species such as Pinus. While partial cement replacement with wood waste and ash offers significant environmental advantages, precise formulations are needed to maintain structural integrity. This study also acknowledges certain methodological limitations, such as the reliance on keyword-based filtering, which may have excluded some relevant studies. Future research should address long-term durability, economic feasibility, and standardized testing methodologies to facilitate the adoption of wood–cement composites in the construction industry. These materials, particularly suitable for non-structural applications and insulation, hold promise as viable, eco-friendly building solutions capable of reducing the construction industry’s carbon footprint.

Interfacially Assembled Anion Exchange Membranes for Water Electrolysis.

High-performance and durable anion exchange membranes (AEMs) are critical for realizing economical green hydrogen production through alkaline water electrolysis (AWE) or AEM water electrosysis (AEMWE). However, existing AEMs require sophisticated fabrication protocols and exhibit unsatisfactory electrochemical performance and long-term durability. Here we report an AEM fabricated via a one-pot, in situ interfacial Menshutkin reaction, which assembles a highly cross-linked polymer containing high-density quaternary ammoniums and nanovoids inside a reinforcing porous support. This structure endows the membrane with high anion-conducting ability, water uptake (but low swelling), and mechanical and thermochemical robustness. Consequently, the assembled membrane achieves excellent AWE (0.97 A cm-2 at 1.8 V) and AEMWE (5.23 A cm-2 at 1.8 V) performance at 5 wt % KOH and 80 °C, significantly exceeding that of commercial and previously developed membranes, and excellent long-term durability. Our approach provides an effective method for fabricating AEMs for various energy and environmental applications.

2D-to-1D Conversion of a Layered Sodium Titanate via Rational Framework Splitting for Highly Efficient Cation Exchange.

Demand on high-performance ion exchangers is ever-increasing in energy and environment applications. Among many cation exchangers, layered alkali titanates generally show larger cation exchange capacity, but slower cation exchange rate due to their 2D micrometer-size particle morphologies, which limits their practical applications. Here, a rational conversion of a layered sodium titanate, Na2Ti3O7, is reported to the corresponding 1D ultra-narrow nanowires via hydrothermal treatment under basic conditions. The formation of nanowires is thought to involve the partial exfoliation of Na2Ti3O7 to form thin plate-like particles that subsequently split into nanowires along a crystallographically defined, chemically selective weakness in the Na2Ti3O7 crystals. This process is similar to a recently burgeoning materials design using atomic-level weakness in solids, such as zeolites and metal-organic frameworks. The proposed formation scheme is further supported by comparative experiments performed on another layered alkali titanate, K0.8Ti1.73Li0.27O4, which possesses randomly distributed defects at the Ti sites. Thanks to the shortening of diffusion path lengths of the interlayer cations, the resulting Na2Ti3O7 nanowires show an excellent cation exchange performance toward Cd2+ in aqueous solution, exceeding several existing cation exchangers such as zeolites and organic resins.

TiO2 Surface Hybridisation with Ag and CuO for Solar‐Assisted Environmental Remediation and Sustainable Energy Applications

AbstractIndustrialisation has led to unprecedented levels of outdoor air pollution, posing a significant health risk to human beings. Consequently, there is an urgent need to replace fossil fuels with sustainable energy sources, thereby mitigating these risks and providing a safer outdoor and indoor environment. Titanium dioxide is a versatile transition metal oxide with applications ranging from energy conversion to environmental remediation. However, it faces limitations, particularly in its absorption spectrum and charge separation efficiency, and enhancing these properties remains a significant challenge. In this research work, we have decorated the surface of TiO2 hybridising it with noble‐metal and/or noble‐metal oxides (Ag and/or CuO) to improve the photocatalytic performances (monitoring the removal of nitrogen oxides and benzene, and hydrogen generation from water splitting) under simulated solar‐light irradiation. Our results showed that titania modified with an Ag : Cu molar ratio equal to 1 : 1, not only exhibited the most promising performance in terms of nitrogen oxides and benzene removal, it was the optimum amount for the light‐induced generation of hydrogen from water splitting.

Deciphering supramolecular arrangements, micellization patterns, and antimicrobial potential of bacterial rhamnolipids under extreme treatments of temperature and electrolyte

The micellization properties of rhamnolipids (RLs) in extreme electrolyte concentrations and temperatures have gained considerable attention due to their broad industrial applications. In this study, the aggregation behavior, specifically the micellization pattern (critical micelle concentration (CMC)) of RLs produced from a newly isolated thermophilic strain of Pseudomonas aeruginosa from a harsh environment of an oil field, was investigated by a spectrophotometric method at various temperatures (293–393 K) and electrolyte concentrations (NaCl: 2–20%). The result indicated that the CMC values (0.267–0.140 mM⋅dm−3) were both electrolyte- and temperature-dependent exhibiting a U-shaped trend as temperature and NaCl concentration increased. Variations in NaCl concentration and temperature also affected the standard Gibbs free energy (ΔGomic), enthalpy (ΔHomic), and entropy (ΔSomic) of micellization. The molecule also showed stability at a broad range of temperatures, pH, and NaCl concentrations. Thin-layer chromatography (TLC) and Fourier-transform infrared (FTIR) analysis confirmed the similarity in composition between the crude extract and the commercial RL with Rf values of 0.72 for mono-rhamnolipids and 0.28 for di-rhamnolipids. FTIR analysis confirmed the chemical nature particularly key aliphatic functional groups present in the fatty acid tail of RLs and the -COC- bond in the structure of the rhamnose moiety. Additionally, LC-ESI-QTOF analysis confirmed corresponding ionic fragments of mono- and di-rhamnolipids congeners. Furthermore, the antimicrobial potential was determined against different human pathogens in the absence and presence of NaCl by measuring zones of inhibition. The result revealed enhanced inhibitory effects against Gram-positive pathogens (S. aureus, S. epidermidis, and L. monocytogene), with zones of inhibition of 26, 30, and 20 mm in the presence of NaCl. These findings underline the role of NaCl in the micellization of RL molecules and highlight their importance in environmental applications, pharmaceuticals, and various life science sectors.

Effects of Silver Nanoparticles on Ctenopharyngodon idella: Synthesis, Characterization, Antibacterial Activity, and Toxicological Assessment.

Currently, nanotechnology (NT) and nanoparticles (NPs) have gained significant attention in the scientific field due to their diverse application history. Particularly, in environmental applications, their antibacterial efficiency in fisheries due to antibacterial resistance. However, the NPs have been found toxic in the environment. Therefore, the current study aimed to fabricate less toxic NPs using environmentally dried leaves to check their antibacterial efficacy and possible toxicity against grass carp. The findings confirmed the good dispersity of obtained AgNPs, which further showed promising antibacterial activity against several bacterial isolates including Staphylococcus with a zone of inhibition (23.73 ± 0.57 nm). Also, the AgNPs were exposed to the grass carp (Ctenopharyngodon idella) for possible toxicity and toxic effects. First, the bioaccumulation of AgNPs was significantly observed in gills followed by intestines and muscles (p < 0.05). Finally, the AgNPs mainly accumulate in the liver, followed by the intestine, gills, and muscles. Additionally, the deposition of AgNPs in various organs resulted in histological alteration such as necrosis and infiltration of red blood cells in the intestine and the fusion of gill lamella. Hence, the synthesized NPs using dried leaf extract could be a promising approach in applied science. The significant features of the nanoparticles in the present work using green synthesis can help in synthesizing less toxic materials.

Machine Learning-Assisted Surface-Enhanced Raman Spectroscopy Detection for Environmental Applications: A Review.

Surface-enhanced Raman spectroscopy (SERS) has gained significant attention for its ability to detect environmental contaminants with high sensitivity and specificity. The cost-effectiveness and potential portability of the technique further enhance its appeal for widespread application. However, challenges such as the management of voluminous quantities of high-dimensional data, its capacity to detect low-concentration targets in the presence of environmental interferents, and the navigation of the complex relationships arising from overlapping spectral peaks have emerged. In response, there is a growing trend toward the use of machine learning (ML) approaches that encompass multivariate tools for effective SERS data analysis. This comprehensive review delves into the detailed steps needed to be considered when applying ML techniques for SERS analysis. Additionally, we explored a range of environmental applications where different ML tools were integrated with SERS for the detection of pathogens and (in)organic pollutants in environmental samples. We sought to comprehend the intricate considerations and benefits associated with ML in these contexts. Additionally, the review explores the future potential of synergizing SERS with ML for real-world applications.

Biogenic Selenium Synthesis by Extracellular Extracts of Bacterial Isolates from Coastal Soils and Their Environmental Applicability

Biogenic Selenium Synthesis by Extracellular Extracts of Bacterial Isolates from Coastal Soils and Their Environmental Applicability

Enhancing Manganese Peroxidase: Innovations in Genetic Modification, Screening Processes, and Sustainable Agricultural Applications.

Manganese peroxidase (MnP), a vital extracellular enzyme for the degradation of lignin and other organic pollutants, has demonstrated immense potential for agricultural and environmental applications, including straw pretreatment, feed fermentation, mycotoxin degradation, and water treatment. However, current research remains in its exploratory phase, with naturally sourced MnP unable to meet industrial-scale demands and no mature commercial enzyme preparations available on the market. This comprehensive review innovatively constructs a framework for MnP research, probing into its molecular conformation and catalytic principles, while providing an overview of the advancements in high-throughput screening and In silco designing strategies. Specifically, this review focuses on the practical applications of MnP in sustainable agriculture, elaborating on its potential and challenges in straw resource utilization, efficient feed fermentation, mycotoxin control, and water quality improvement. Furthermore, this review summarizes the recent achievements in optimizing MnP activity through enzyme engineering techniques and discuss customized mutation strategies tailored to specific agricultural and environmental requirements, thereby laying a solid theoretical foundation and scientific basis for the industrial production and commercialization of MnP.

Highly Efficient Porous Glass Solar Water Evaporator

AbstractThe global water crisis, exacerbated by excessive use and pollution, has resulted in energy scarcity and threats. Solar desalination provides a sustainable fix, with researchers developing photothermal materials and designs to improve efficiency and sustainability. Glass materials, with their exceptional chemical stability, are suitable for extreme desalination in acidic and alkaline conditions. In this work, we have developed a porous glass evaporator (PGE) with exceptional water evaporation efficiency, achieved through a novel fabrication method that blends glass powders with soluble salts to create structure with continuous pores. The evaporator's microstructure comprises micrometer‐scale pores that form interconnected porous channels, facilitating efficient water transport and preventing salt deposition. Under one sun irradiation, the PGE exhibits superior solar evaporation performance in pure water, achieving a rate of 2.21 kg m−2 h−1, with an evaporation efficiency of 98%. In more complex media, such as seawater and methylene blue solution, the PGE also displays excellent evaporation capabilities, reaching rates of 2.08 and 2.47 kg m−2 h−1, respectively. Even after sustained alternation between acidic and alkaline treatments, the PGE retains an impressive evaporation rate of over 2.0 kg m−2 h−1, coupled with structural robustness, making it a promising candidate for practical applications in extreme environments.

Elaboration and Characterization of Different Zirconium Modified ETS Photocatalysts for the Degradation of Crystal Violet and Methylene Blue.

In this study, Zirconium-modified Engelhard Titanium Silicate 4 (Na-K-ETS-4/xZr) catalysts were synthesized and evaluated for their photocatalytic efficiency in degrading crystal violet (CV) and methylene blue (MB) in aqueous solutions. The catalysts were characterized using XRD, FTIR, SEM, WDXRF, and nitrogen adsorption/desorption isotherms. The results confirmed the successful incorporation of Zr into the ETS-4 framework, with the highest Zr content reaching 9.2 wt %. The photocatalytic performance under visible light irradiation was studied at varying pH levels. The Na-K-ETS-4/6.3Zr catalyst exhibited the highest photodegradation efficiency for CV (76.6 %), while Na-K-ETS-4/8.9Zr achieved 86.6 % efficiency for MB. A combination of Engelhard Titanium Silicate 10, Na-K-ETS-10/6.3Zr and Na-K-ETS-4/8.9Zr significantly enhanced dye degradation, achieving up to 96.5 % efficiency for MB. Kinetic studies indicated that the degradation process follows a non-linear pseudo-first-order model. The catalysts also demonstrated excellent reusability, with minimal efficiency loss after five cycles, and full recovery after an ethanol wash. These findings suggest that Na-K-ETS-4/xZr is a promising candidate for environmental water treatment applications due to its efficient photodegradation performance and stability.

Solid waste-derived carbonaceous catalysts for environmental and energy applications

AbstractUrbanization and industrialization generate vast amounts of solid waste, posing significant threats to the biotic and abiotic components of the environment. Solid wastes-derived carbonaceous catalysts (SW-CCs) represent an effective strategy for resource utilization, and SW-CCs are gradually applied in environmental remediation and energy fields. However, the effects of the properties of SW-CCs on their catalytic activity remain inadequately understood. A comprehensive review of the applications of SW-CCs in environmental remediation and energy fields is yet to be achieved. It is necessary to systematically review the latest research progress of SW-CCs in environmental remediation and energy fields. First of all, this review summarizes the influences of various factors on the properties of SW-CCs and how these properties affect the catalytic activity. Subsequently, it explores the recent research progress and existing issues in the applications of SW-CCs in environmental remediation (persulfate activation, photocatalysis, and Fenton-like oxidation) and the energy sector (H2 production, biodiesel production, and CO2 conversion). Finally, future research prospects and recommendations are provided to facilitate further development and application of SW-CCs. This review offers new insights into the resource utilization of solid waste and the development of efficient and practical carbonaceous catalysts. Graphical Abstract

Retraction Note: Antenna optical communication spectral enhancement with energy analysis of photovoltaic cell microgrid environmental application

Retraction Note: Antenna optical communication spectral enhancement with energy analysis of photovoltaic cell microgrid environmental application

A Systematic Review of Techno-Economic, Environmental and Socioeconomic Assessments for Vibration Induced Energy Harvesting

There is a growing need to ensure the resilience of energy and water systems through digitalization, retrofit these systems for cleaner energy systems, and protect public safety in terms of water quality. This resilience requires a reliable power supply that could be provided by harnessing unexploited energy hidden in the current water infrastructure through the deployment of vortex-induced vibration energy harvesters. Therefore, being able to understand the feasibility of deploying these devices across technical, socioeconomic and environmental scales could further enhance successful deployment and integration of these devices. This paper aims to provide a systematic review investigating the development of energy harvester technologies to understand the key methods used to assess their application feasibility. This study used the PRISMA guidelines, and 139 articles were reviewed and synthesized. The trends were visualized, illustrating the current direction in energy harvesting development and application and methods used to assess the feasibility of these devices and technology. The majority of the reviewed studies focused on technical feasibility, design configuration, limitation, and identification of the most optimal application environment. The results revealed a huge opportunity for energy harvesters, especially as a power supply for monitoring sensors. Nevertheless, the results also identified a knowledge gap when it comes to assessing the overall application feasibility of energy harvesting as most studies currently neglect economic feasibility, environmental impacts, social aspects and energy resilience. Assessment tools will help fill this knowledge gap by identifying the key barriers and benefits gained from integrating this technology into existing energy systems and water systems.

Materials Science and Environmental Applicability

Materials Science and Environmental Applicability

A Case Study Comparing Methods for Coal Thickness Identification in Complex Geological Conditions

This study compares the effectiveness of different methods for coal thickness identification, aiming to identify the most accurate approach and provide a reference for intelligent coalmine development. Focused on the No. 2 coal seam in a mining area in Shanxi, China, the analysis employs well log-constrained impedance inversion and seismic multi-attribute techniques. The results show that the back propagation (BP) neural network model, as part of the seismic multi-attribute approach, delivers prediction accuracy comparable to the well log-constrained inversion method. Specifically, after applying proper static corrections, a four-layer BP neural network was constructed using four optimized sensitive attributes as the input layer, achieving an error range of 0.11% to 1.36%, compared to 0.03% to 6.59% for the logging-based method. The BP neural network demonstrated strong applicability in complex geological environments. Empirical analysis further validated the BP neural network’s geological reliability and practicality in systematic coal thickness determination.