Explore the vast range of titles available.

Rising global carbon dioxide (CO 2 ) levels, driven by industrialization and fossil fuel use, significantly contribute to climate change. CO 2 capture technologies are essential to mitigate greenhouse gas emissions, stabilize global temperatures, and meet international climate goals, ensuring a sustainable future through cleaner energy and reduced environmental impact. Carbon capture and utilization (CCU) technologies are now increasingly in demand with rising atmospheric CO 2 levels. In this respect, Artificial Intelligence (AI) has made a big difference in achieving more efficient and effective solutions for CCU. Therefore, with the objective of examining the role of AI in CCU technologies, the present research offers an in-depth patent analysis focusing on innovation trends, notable contributors, and emerging technical applications. Results from the analysis of the top industrial sectors, regional patent distribution, and impacts of collaborations between the academia and business sectors are also reported. Patent analysis reveals rapid growth in this domain, with China, South Korea, and India leading advancements through academia–industry collaboration. AI techniques such as machine learning, deep learning, and optimization algorithms are being applied to process optimization, performance forecasting, and emissions prediction across physical, chemical, and biological CCU systems. This research points that AI/ML application has increasingly become an important player in the building of sustainable carbon management strategies. We have also enlisted the key challenges faced while using AI such as limited poor scalability and limited training data. Results from the analysis of the top industrial sectors, regional patent distribution, and impacts of collaborations between academia and business sectors have also been reported.

Targeting drug delivery in the intestine is still one of the biggest hurdles in pharmaceutical research because of reasons like low bioavailability, enzymatic degradation, rapid transit time, and absorption plight of conventional oral drugs. Intestinal scaffolds are now a new promising platform for localized, controlled, and sustained drug delivery. Scaffolds mimic the physiological environment of the intestine and are made from biodegradable polymers, hydrogel, and any nanomaterial-based composites. They allow very precise spatial and time-controlled drug release while improving mucosal adhesion and interaction with the epithelium. Current advances include bioengineered scaffolds, microfabrication, and smart responsive systems to increase and expand current use in gastrointestinal diseases such as inflammatory bowel disease, colorectal cancer, and malabsorption disorders. Functional modification has produced scaffolds that are pH-sensitive, enzyme-responsive, and microbiota-targeted scaffolds, which can enable personalized, disease-specific therapeutics. Further enhancement of scaffold stability, drug-loading capacity, and site-specific release mechanisms is achieved by adding nanoparticles, bioadhesive polymers, and bioactive molecules. We have carried out this review from an overview perspective on the latest developments in material design, fabrication techniques, or drug release strategies for the next-generation intestinal scaffolds. The focus now has shifted to comparing the advantages of these innovations over conventional oral drug delivery systems and discussing the accompanying risks of biocompatibility, scalability, regulatory approval, and clinical translation, future research directions to ultimately optimize scaffold-based drug delivery. Thus, from precision medicine and regenerative approaches, intestinal scaffolding may change oral drug administration, improving therapeutic outcomes in patients with gastrointestinal disorders while minimizing systemic side effects.

Global health and ecosystem concerns over mercury pollution require stringent monitoring. Herein, we showcase a novel approach for detecting trace Hg2+ ions in water using cyclic voltammetry (CV). Our approach involves modifying glassy carbon electrode (GCE) and screen printed electrode (SPE) surfaces with a nanocomposite of ascorbic acid-capped silver nanoparticles (AsAgNPs) embedded in nanocrystalline bacterial cellulose (AsAgNP-NBC). Analytical techniques confirmed the nanocomposite’s stability and morphological characteristics, exhibiting high accuracy within a linear range of 10 nM to 1 µM Hg2+ and a low limit of detection (LOD) of 3.531 nM. Additionally, on irradiation with 455 nm light source, AsAgNP-NBC modified SPE displayed a remarkable 9.6 times enhanced photocurrent, achieving an LOD of 3.95 pM, and enhanced photoresponsivity of 55.2 mA W−1, showcasing its potential for ultra-trace level detection. This cost-effective and biocompatible nanocomposite presents a promising alternative to conventional analytical methods for selective detection of trace Hg2+ ions in environmental samples.

Contamination by hexavalent chromium [Cr (VI)] poses a threat to groundwater quality and its detection at point source is essential to provide early mitigating solutions. In this work, we report the fabrication of paper-based sensing system embedded with a novel nano-chromogenic complex having spherical gold nanoparticles modified with 1,5-diphenylcarbazide dye. This A u- D PC F unctionalized paper strip develops pink color in <2 sec upon interaction with Cr (VI). With the developed optical fiber device a limit of detection of 0.02 ppm was achieved within a linear range of 0.01-0.4 ppm. RGB color analysis and data driven predictive modelling (KNN-model) demonstrated highest balanced accuracy score of 0.833 and cross validation accuracy of 0.714. Further, the portable optical fiber-based device offers advantages such as real-time monitoring, remote sensing capabilities, and the ability to integrate with existing optical systems for enhanced detection and analysis.

National Environmental Engineering Research Institute, Jawaharlal Nehru Marg, Nagpur 440020, India; Tel.: +91-712-2249884; Fax: +91-712-2249896; E-Mail: rj_krupadam@neeri.res.inAbstract ... 77 5.1 Introduction ... 78 5.2 Materials and Methods ... 81 5.3 Results and Discussion ... 87 5.4 Conclusions ... 95 Acknowledgments ... 95 Keywords ... 96 References ... 96ABSTRACTThe molecular imprinting technology that has recently demonstrated great potential for producing artificial receptors that challenge their naturalcounterparts. The stability and low cost of molecularly imprinted polymers (MIPs) make them advantageous for application as sensory materials, immunosorbents and adsorbents in environmental and biomedical fields. However, the imprinted polymer properties such as selectivity, capacity and binding kinetics towards the target molecule primarily depends on polymer composition and conditions followed during molecular imprinting. Availability of huge number of functional and cross-linking monomers, it would be time consuming as well as intense quantities of materials/reagents are required to select more appropriate polymer composition based on experiments for a given molecule. To overcome this constraint, the rational design using computer simulations has recently emerged as an efficient and experimental free way of selection of suitable polymer precursors to achieve the optimum molecular recognition properties of imprinted polymers. In this article, a new combinatorial screening method was proposed based on density functional theory (DFT) for selection of polymer precursors for microcystin-LR specific. The study also discusses about on the nature of intermolecular interactions responsible for high selectivity for the microcystin-LR (Scheme 1).