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Preparation and Electrochemical Investigation of NiO Hollow Sphere from Bio Waste (Sugarcane Bagasse) Extract for Energy Storage Applications
This work describes how to easily make NiO hollow sphere composites using waste sugarcane bagasse for use in supercapacitor applications. NiO hollow spheres (NOHSs) nanomaterialis effectively synthesized through the nano carbon sphere (CS) template. A core-shell structure was created on the carbon spheres surface by NiO nanoparticles that were several nanometers in size. The structural and morphological of the synthesized materials were investigated by X-ray diffraction (XRD) and Scanning electron microscope (SEM). The energy-dispersive X-ray spectroscopy (EDS) was used to confirm the presence of the elements in NOHS. The electrochemical behaviour of hierarchical CSs and NOHSs electrode was examined through cyclic voltammetry (CV), Galvanostatic charge/discharge (SC) and electrochemical impedance spectroscopy (EIS). In GCD analysis, NOHSs electrode showed a concentrated specific capacitance (Csp) of 913.79F/g at 5A/g current density. The porous conductive carbon with macro pores that speeds up the transit of electron and electrolyte ions causes noticeably better capacitive behavior. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Scalable synthesis of 2D-layered Ti3C2 MXene by HF etching method; electrochemical investigations and device fabrication to enhancing capacitive nature
The goal of the current effort is aimed to synthesise the uniform exfoliated titanium carbide (Ti3C2) MXene sheets by utilising hydrofluoric (HF) acid to remove/etch aluminium from the parental Ti3AlC2 MAX phase. The Ti3C2 MXene was investigated by structural analysis using X-ray diffraction (XRD), Higher Resolution Transmission Electron Microscope (HRTEM), Scanning electron microscope (SEM), and EDS with mapping for morphological and elemental analysis, Moreover, the Ti3C2 MXene was studied its electrochemical properties to electrochemical energy storage application using cyclic voltammetry (CV), Galvanostatic chargedischarge (GCD) and electrochemical impedance spectroscopy (EIS) techniques. Since the GCD analysis of Ti3C2 MXene, a great specific capacitance (Csp) of 318F/g was attained with current density of 1 A/g and up to 90 % retentivity was attained after 7500 cycles. Besides, fabricated Ti3C2 MXene||Ti3C2-MXene symmetric supercapacitor device (SSD) has described the energy density (ED) of 27.78 Wh/kg at a power density (PD) of 400 W/kg and the capacitive retention existed attained 92.1 % after 7500 cycles with 5 A/g. 2024 Elsevier B.V. -
Exploration of low heat rejection engine characteristics powered with carbon nanotubes-added waste plastic pyrolysis oil
Compression ignition (CI)-powered alternative energy sources are currently the main focus due to the constantly rising worldwide demand for energy and the growing industrialization of the automotive sector. Due to their difficulty of disposal, non-degradable plastics contribute significantly to solid waste and pollution. The waste plastics were simply dropped into the sea, wasting no energy in the process. Attempts have been made to convert plastic waste into usable energy through recycling. Waste plastic oil (WPO) is produced by pyrolyzing waste plastic to produce a fuel that is comparable to diesel. Initially, a standard CI engine was utilized for testing with diesel and WPO20 (20% WPO+80% diesel). When compared to conventional fuel, the brake thermal efficiency (BTE) of WPO20 dropped by 3.2%, although smoke, carbon monoxide (CO), and hydrocarbon (HC) emissions were reasonably reduced. As a result, nitrogen oxide (NOx) emissions decreased while HC and CO emissions marginally increased in subsequent studies utilizing WPO20 with the addition of 5% water. When combined with WPO20 emulsion, nanoadditives have the potential to significantly cut HC and CO emissions without impacting performance. The possibility of incorporating nanoparticles into fuel to improve performance and lower NOx emissions should also be explored. In order to reduce heat loss through the coolant, prevent heat transfer into the cylinder liner, and increase combustion efficiency, the thermal barrier coating (TBC) material is also coated inside the combustion chamber surface. In this work, low heat rejection (LHR) engines powered by emulsion WPO20 containing varying percentages of carbon nanotubes (CNT) are explored. The LHR engine was operated with a combination of 10 ppm, 20 ppm, and 30 ppm CNT mixed with WPO20. It was shown that while using 20 ppm of CNT with WPO20, smoke, hydrocarbons, and carbon monoxide emissions were reduced by 11.9%, 21.8%, and 22.7%, respectively, when compared to diesel operating in normal mode. The LHR engine achieved the greatest BTE of 31.7% as a result of the improved emulsification and vaporization induced by CNT-doped WPO20. According to the study's findings, WPO20 with 20 ppm CNT is the most promising low-polluting fuel for CI engines. 2023 The Institution of Chemical Engineers -
Earlier Stage Identification of Bone Cancer with Regularized ELM
A major focus of current research in the field of image processing is the application of such methods to the field of medical imaging. While dealing with biological issues like fractures, canoers, ulcers, etc., image processing facilitated pinpointing the precise cause and tailoring a remedy. In the field of tumor identification, medical imaging has set a new standard by overcoming a number of challenges. Medical imaging is the practice of generating images of the human body for diagnostic or exploratory purposes. Because of its high image quality, MRI is the method of choice for detecting tumors. This research study proposes the integration of RLM to detect tumors and presents an automatic bone cancer detection system to assist oncologists in making early diagnosis of bone malignancies, which in turn allows patients to receive treatment as soon as possible. This research work also proposes to detect bone tumors by using a combination of the RELM based M3 filtering, Canny Edge segmentation, and the Enhanced Harris corner approach. When compared to other models like CNN, ELM, and RNN, the suggested technique achieves an accuracy of around 97.55%. 2023 IEEE. -
Catalyzing Green Mobility: Consumer Preferences for Green Energy Vehicles
Due to growing urbanization and the increase of vehicles, most Indian cities endure traffic congestion and significant air pollution. As a result, alternate technology in autos, such as electric vehicles, may become necessary (EV). This study aims to identify consumer preferences toward electric vehicles in the Indian market. This research conducted a survey and analyzed the opinions of people regarding their preferences for electric vehicles, demographics, and some of the demotivation which might be stopping them to switch to electric vehicles altogether. This research will help in determining different factors influencing the perception of consumers toward electric vehicles and what they expect when they think about purchasing a new electric vehicle. It is important to understand that electric vehicles are really getting popular now because of the rising fuel prices and environmental concerns. People are thinking about electric vehicles and replacing them with their regular petrol or diesel vehicles. In this research there might be some challenges or roadblocks in switching to electric vehicles. This research found out that despite a favorable attitude toward electric vehicles, individuals are hesitant to transition to electric vehicles due to different hurdles connected with them. This research found out that mostly the preferences of the consumers are good charging infrastructure, a good range of the electric vehicle, pocket-friendly vehicles are the most common preferences of consumers buying an electric vehicle. 2023 EDP Sciences. All rights reserved. -
A study of Artificial Intelligence impacts on Human Resource Digitalization in Industry 4.0
Artificial Intelligence (AI) has opened up tremendous opportunities in the workplace through robotics innovation, which envelops both AI and the Internet of Things (IoT). Precision, Efficiency, and Flexibility are considered the potential benefits of Industry 4.0. The implementation of Industry 4.0 requires a lot of changes, including the Human Resource (HR) function. In Industry 4.0, the HR capability is more critical and gives an upper hand to the organization. The HR capability should be more cautious and adaptable to adjust to the difficulties and requirements. We study the contributions of AI in HR digitalization and practices in Industry 4.0. 271 HR experts working in Information Technology (IT), Manufacturing, and administration are selected to participate in this review focusing on five AI applications in HR capability and three elements of HR readiness. The information collected was examined utilizing the Statistical Package for Social Sciences (SPSS) tool and Analysis of Moment Structures (AMOS). The results uncovered that hierarchical organization examination is a fundamental part of acquiring sustainable development. Adaptability and human asset capability are upheld by each of the five components of AI application areas of HR. Well-being and Safety improvement were viewed as vital components under the AI application in HR. 2023 The Author(s) -
Navigating resource scarcity in a changing climate: AI-powered perspectives on mental health
In the backdrop of the extensive global impact of the COVID-19 pandemic, environmental crises have, to a certain degree, taken a back seat. The pandemic-induced scarcity mindset, emphasizing immediate short-term needs over long-term considerations, has played a role in this shift in priorities. This scarcity mindset, prevalent during the pandemic, poses a risk to pro-environmental behavior and may contribute to environmental degradation, thereby heightening the likelihood of future pandemics. This chapter advocates for a reevaluation of pro-environmental actions, emphasizing their role in addressing various human needs, especially during periods of scarcity. AI-driven chatbots possess the capability to significantly enhance accessibility to affordable and efficient mental health services by complementing the efforts of clinicians. To safeguard pro-environmental behavior, we propose a reconceptualization that positions these actions not merely as value-laden or effortful but as pragmatic measures essential for resource conservation, particularly in times of scarcity. The study explores, the intricate dynamics of resource scarcity, climate change, and mental health, employing AI-powered perspectives to navigate this complex interplay. 2024, IGI Global. All rights reserved. -
Efficient multipath model based cross layer routing techniques for Gauss Markov movable node management in MANET
This research unveils an innovative cross-layer routing methodology tailored for managing Gauss Markov mobile nodes within MANETs. The primary focus deceits cutting-edge inspiring network performance through the efficient utilization of resources and the steadfast maintenance of mobile node connectivity. Central to this model is the implementation of joint optimization, which takes into account both node mobility patterns and resource allocation dynamics to pinpoint the most favorable data transmission pathway. Incorporating multipath routing, the methodology enables the simultaneous exploration of multiple transmission routes, thereby fortifying the network against potential link failures and disruptions. By embracing a cross-layer approach, it seamlessly integrates functionalities across network, and steering layers, thereby amplifying the complete system efficacy. Comprehensive simulations conducted reveal the superior performance of this approach compared to existing techniques, particularly in terms of network throughput, latency reduction, and augmentation of packet delivery ratios. Such findings underscore the immense potential of this methodology across a spectrum of MANET applications that demand streamlined and dependable data transmission mechanisms. 2024 Author(s). -
Attenuation properties of epoxy-Ta2O5 and epoxy-Ta2O5-Bi2O3 composites at ?-ray energies 59.54 and 662 keV
Epoxy resin filled with suitable high Z elements can be a potential shield for X-rays and ?-rays. In this work, we present the ?-ray attenuation properties of epoxy composites filled with (030 wt%) Tantalum pentoxide (Ta2O5) and Ta2O5-Bi2O3, which were prepared by open mold cast technique. X-ray diffraction patterns showed crystalline peaks of Ta2O5 and bismuth oxide (Bi2O3) in the prepared epoxy-Ta2O5 and epoxy-Ta2O5-Bi2O3 composites. Homogeneity of the samples at higher filler wt% was revealed by SEM images. Mechanical characterization showed the enhanced mechanical strength of epoxy-Ta2O5-Bi2O3 composites compared to epoxy-Ta2O5. Higher storage modulus and glass transition temperature of the epoxy-Ta2O5-Bi2O3 composites showed enhanced stiffness and thermal stability when compared to neat and epoxy-Ta2O5. Decrease in the value of tan(?) at higher content of filler loadings indicated the good adhesion between filler and matrix. Mass attenuation coefficients of epoxy-Ta2O5 (30 wt%) composites at ?-ray energies 59.54 and 662 keV were found to be 0.876 cm2 g1 and 0.084 cm2 g1, while that of epoxy-Ta2O5-Bi2O3 (30 wt% Bi2O3) composite were 1.271 cm2 g1 and 0.088 cm2 g1, respectively. The epoxy-5% Ta2O5-30% Bi2O3 composites with higher ?/? value and tensile strength may be a potential ?-ray shield in various radiation environments. 2020 Wiley Periodicals, Inc. -
Poly(vinyl alcohol)bismuth oxide composites for X-ray and ?-ray shielding applications
Polymer composites, which are light in weight, cost effective, and less toxic, have potential applications in X-ray and ?-ray shielding and protection. In this work, we have explored the efficacy of poly(vinyl alcohol)bismuth oxide composites as radiation shielding materials. Poly(vinyl alcohol) composites with different wt % (050) of bismuth were prepared by a simple solution casting technique. Structural and thermal characterization of these samples was carried out using Fourier transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). TGA revealed the enhanced thermal stability of these composites. AC conductivity measurements and optical spectroscopy were used to analyze their electrical behavior. The composites showed low conductivity, and the energy gap obtained also showed their tendency to be insulators. The radiation attenuation properties were investigated using X-ray (5.895 and 6.490 keV) and ?-ray (59.54 and 662 keV) transmission measurements. The shielding efficiency of the composites increased with filler wt %. The 40 wt % composites exhibited mass attenuation coefficients of 122.68 and 93.02 cm2/g at photon energies of 5.895 and 6.490 keV, respectively, while the 50 wt % composites showed 1.57 and 0.092 cm2/g at photon energies of 59.54 and 662 keV, respectively. The effective atomic number quantifies the probability of interaction of radiation with matter. The effective atomic number of the composites calculated by the direct method was in good agreement with the theoretical value obtained from Auto-Zeff software. 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 47949. 2019 Wiley Periodicals, Inc. -
Attenuation parameters of polyvinyl alcohol-tungsten oxide composites at the photon energies 5.895, 6.490, 59.54 and 662 keV
The growing demand for lightweight, non-toxic and effective X-A nd ?-ray shielding materials in various fields has led to the exploration of various polymer composites for shielding applications. In this study, tungsten filled polyvinyl alcohol (PVA) composites of varying WO3 concentrations (0-50 wt%) were prepared by solution cast technique. The structural, morphological, and thermal properties of the prepared composite films were studied using X-ray diffraction technique (XRD), Scanning electron microscopy (SEM) and Thermogravimetric analysis (TGA). The AC conductivity studies showed the low conductivity property of the composites. The X-ray (5.895 and 6.490 keV) and ?-ray (59.54 and 662 keV) attenuation studies performed using CdTe and NaI(Tl) detector spectrometers revealed a noticeable increase in shielding efficiency with increase in filler wt%. The effective atomic number (Zeff) calculated by the direct method agreed with the values obtained using Auto-Zeff software. The % heaviness showed that tungsten filled polyvinyl alcohol composites are lighter than traditional shielding materials. 2020 M V Muthamma et al., published by Sciendo 2020. -
Micro and nano Bi2O3 filled epoxy composites: Thermal, mechanical and ?-ray attenuation properties
Polymer composites have attracted considerable attention as potential light-weight and cost-effective materials for radiation shielding and protection. In view of this, the present work focusses on development of lead-free composites of diglycidyl ether of bisphenol A (DGEBA) epoxy resin with micro (~ 10 ?m) and nano (~ 20 nm) bismuth (III) oxide (Bi2O3) fillers, using solution casting technique. Thermal, mechanical and ?-ray attenuation properties of the composites were studied by varying the filler loading. Inclusion of the fillers into epoxy matrix was confirmed both structurally and morphologically by XRD and SEM, respectively. Thermogravimetric analysis (TGA) showed the thermal stability of composites to be as high as 400 C. The nanocomposites exhibited relatively higher thermal stability than their micro counterparts. Among the composites, 14 wt% nano-Bi2O3/epoxy composites showed highest tensile strength of 326 MPa, which is about 38% higher than 30 wt% micro Bi2O3/epoxy composites. Mass attenuation coefficients (?/?) of the composites were evaluated at ?-ray energies ranging from 0.356 to 1.332 MeV. Nanocomposites showed better ?-ray shielding at all energies (0.356, 0.511, 0.662, 1.173, 1.280 and 1.332 MeV) than micro composites with same filler loading. These studies revealed the significance of nano-sized fillers in enhancing overall performance of the composites. 2021 Elsevier Ltd -
A reconfigurable integrated level shifted carrier based PWM method for modular multilevel converters
This article presents a reconfigurable integrated level shifted carrier-based pulse width modulation (ILSC-PWM) method for modular multilevel converters (MMCs). The principles of basic level shifted carrier-based PWM (LSC-PWM) methods such as phase disposition PWM (PD-PWM), phase opposition disposition PWM (POD-PWM) and alternate phase opposition disposition PWM (APOD-PWM) methods are combined to develop the concept of reconfigurable ILSC-PWM method. The main objectives of the proposed reconfigurable ILSC-PWM method is to develop the pulse width modulated output voltage with both half-wave and quarter-wave symmetries and to reduce the total harmonic distortion (THD). A simplified mathematical approach is developed to formulate reconfigurable single ILSC wave for MMC with N number of submodules (SMs) per arm. The functionality and performance of the reconfigurable ILSC-PWM method are carried out on three-phase five-level MMC in MATLAB/Simulink. A hardware prototype of single-phase five-level MMC is designed for experimental validation. The proposed ILSC-PWM method is implemented on an Altera/Cyclone I series (EP1C12Q240C8N) field programmable gate array (FPGA). Computer Simulations and laboratory experimental results are presented. 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. -
An Efficient Sorting Algorithm for Capacitor Voltage Balance of Modular Multilevel Converter With Space Vector Pulsewidth Modulation
Thisarticle presents an efficient analogue sorting algorithm for balancing the submodule (SM) capacitor voltages of modular multilevel converter (MMC). The proposed analogue sorting algorithm offers the advantage of fast convergence rate without any need of recursive loops for the implementation on embedded devices. It can be easily implemented with combinational logic operations on field programmable gate array (FPGA) and provides less hardware and computational overhead. The functionality and performance of the proposed analogue sorting algorithm is evaluated with the simulation model of three phase five-level MMC in MATLAB/Simulink environment. The real time implementation of the proposed sorting algorithm with the SM capacitor voltage balancing strategy is implemented on Altera/Cylone - I (EP1C12Q240C8N) FPGA. A five-level continuous space vector pulsewidth modulation (CSVPWM) is realized on a PIC microcontroller (PIC18F452). A down-scaled model of single-phase five-level MMC is designed and constructed to investigate the reliable and stable operation of MMC with the proposed analogue sorting algorithm and SVPWM method. Simulation and experimental results are presented for validation. 1986-2012 IEEE. -
Effects of Euphorbia thymifolia and Euphorbia hirta leaf extracts on membrane-bound, mitochondrial enzymes and lipid profile of carbon tetrachloride-induced hepatotoxicity in rats
The present investigation was aimed to identify the potentiality of Euphorbia thymifolia Linn. and Euphorbia hirta Linn. leaf extract on the toxin-induced (carbon tetrachloride- CCl4) Albino Wistar rats. The animals were grouped into 7 categories including control (basal diet, G1), CCl4-induced (1.5 mL/kg, b.w., i.p.) (G2), G1 administrated with 300 mg/kg b.w., extract of E. thymifolia (G3) and E. hirta (G4), G2 administrated with 300 mg/kg b.w., extract of E. thymifolia (G5), E. hirta (G6), and standard drug (silymarin 25 mg/kg b.w.; G7) for 21- days trial period with each group contains 6 rats. The samples were collected and the following parameters including mitochondrial enzymes, different ATPase and lipid profiles were analyzed. The membrane-bound enzymes, the mitochondrial enzymes levels and the lipid profiles were reduced in the toxin-induced rats but the levels of enzymes were restored, significantly increased and lipid profiles are returned to the normal in the treatment of both extracts. 2022 Visagaa Publishing House. -
Unveiling the Emotions: A Sentiment Analysis of Amazon Customer Feedback
This study explores sentiment analysis in the context of diverse regions and contemporary customer feedback, aiming to address research questions related to consolidation based on polarity scores and sentiments. The research utilizes multinomial regression for a comprehensive analysis of customer feedback worldwide. The investigation incorporates confusion matrices, statistics, and class-specific metrics to evaluate the models performance. Results indicate a highly accurate model with perfect sensitivity, specificity, and overall accuracy. The analysis further includes a breakdown of key metrics such as accuracy, confidence intervals, no information rate, p-value, kappa, and prevalence, emphasizing the models robustness. In conclusion, the multinomial logistic regression model demonstrates exceptional performance in predicting sentiment across diverse classes, highlighting its effectiveness in sentiment analysis on a global scale. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
DFT electronic structure calculations, spectroscopic studies, and normal coordinate analysis of 2-[(5-nitro-1,3-thiazol-2-yl)carbamoyl]phenyl acetate
The solid phase FTIR and FT-Raman spectra of 2-[(5-nitro-1,3-thiazol-2-yl)carbamoyl]phenyl acetate (25N2LCPA) have been recorded 450-4000 cm-1 and 100-4000 cm-1 respectively. The normal coordinate analysis was carried out to confirm the precision of the assignments. DFT calculations have been performed giving energies, optimized structures, harmonic vibrational frequencies and IR intensities. The structure of the molecule was optimized and the structural characteristics were determined by density functional theory (DFT) using B3LYP method with 6-31+G(d,p) basis set. The detailed interpretation of the vibrational spectra has been carried out with aid of normal coordinate analysis (NCA) following the scaled quantum mechanical force field methodology. The Vibrational frequencies are calculated in the above method and are compared with experimental frequencies which yield good agreement between observed and calculated frequencies. Stability of the molecule arising from hyper conjugative interactions, charge delocalization has been analyzed using natural bond orbital (NBO) analysis. In addition, Frontiers molecular orbital and molecular electrostatic potential were computed by using Density Functional Theory (DFT) B3LYP/6-31+G(d,p) basis set. The calculated HOMO and LUMO energies show that charge transfer occurs in the molecule. 2014 Elsevier B.V. All rights reserved. -
ML in drug delivery-current scenario and future trends
Machine learning (ML) has enabled transformative applications and emerged as a domain-agnostic decision-making tool as a virtue of its rapid democratization. The authors believe that a systematic assortment of important publications on this issue is indispensable in this context. In terms of data ingestion, data curation, data preprocessing, data handling, and model cross-validation, this review gathers together several studies that have demonstrated a minimum ML framework approach. In general, ML models are described as black-box models, with limited information supplied about their transparency. The authors propose techniques based on the US Food and Drug Administration (FDA)'s current good ML practice (GMLP) in order to improve the ML framework and minimize the aforementioned gap, especially for data. Considering this, the conversation around a model's logic and interpretability are additionally provided. Explicitly, the authors explore the challenges and constraints that ML execution confronts throughout the development of pharmaceuticals. In this context, a structural approach in statistics is presented to allow the scientist to assess the quality of data and incorporate important ideas and techniques that would be implemented in modern ML. The data analytics tetrahedron proposed here can be applied to data of any size. To further contextualize, selected case studies capturing good practices are highlighted to provide pharmaceutical scientists, pharmaceutical ML enthusiasts, readers, reviewers, and regulatory authorities an exposure to fundamental and cuttingedge techniques of ML and data science with respect to chemistry, manufacture, and control (CMC) of drug products. In addition, the authors believe that leveraging ML within CMC procedures can assist in improving decision-making, increasing quality, and enhancing the speed of pharmaceutical product development. IOP Publishing Ltd 2023. All rights reserved. -
Teacher Trainee's Acceptance of Interactive eBooks for Teaching: An Analysis Using the Modified Technology Acceptance Model (TAM)
The current empirical study utilized the Technology Acceptance Model (TAM) to investigate teacher trainees' acceptance of interactive eBooks for teaching. The study investigated the relationships among variables such as attitude toward using interactive eBooks, perceived ease of use, perceived usefulness, enjoyment, perceived self-efficacy, and behavioural intention to use. A sample consisting of 89 teacher trainees studying in diploma and bachelors teacher training programs from two private and public universities in Malaysia participated in the study. The TAM model, which involves seven hypotheses, was tested using the Partial Least Square Structural Equation Modelling approach (PLS-SEM). The key findings of this empirical study confirmed that attitude influences both behaviour intention to use, and perceived self-efficacy of teacher trainees in teaching using interactive eBooks. Besides, the study confirmed a direct effect of ease of use on the level of enjoyment and a direct effect of perceived usefulness on the perception of ease of use. The study findings shed light on preparing teacher trainees for technology-integrated teaching. 2024, The Pacific Association for Computer Assisted Language Learning (PacCALL). All rights reserved. -
Computer modelling of trace SO2 and NO2 removal from flue gases by utilizing Zn(ii) MOF catalysts
SO2 and NO2 capture and conversion have been investigated via density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations using a novel hydrogen-bonded 3D metal-organic framework (MOF) containing a Zn(ii) centre and a partially fluorinated (polar -CF3) long-chain dicarboxylate ligand with a melamine (basic -NH2) co-ligand. Initially, computational single-component isotherms have been determined for SO2 and NO2 gases. These simulations have shown exothermic adsorption enthalpies of ?36.4 and ?28.6 kJ mol?1 for SO2 and NO2, respectively. They have also indicated that SO2 has a high affinity for polar -CF3 and basic -NH2 binding sites of the ligand in the framework pore walls. The lower adsorption capacity of NO2 compared with SO2 is due to weaker electrostatic interactions with the framework. Furthermore, MOF adsorbent selectivity for removing trace amounts of SO2 and NO2 in flue gases has been estimated through the co-adsorption of ternary gas mixtures (SO2/CO2/N2 and NO2/CO2/N2). Together with DFT, the climbing image nudged elastic band (CI-NEB) method has been used for investigating the plausible mechanisms for HbMOF1 catalyzed cycloadditions of SO2 and NO2 with epoxides leading to the formation of cyclic sulphites and nitrates, respectively. 2023 The Royal Society of Chemistry.