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Bifunctional CoPBO/Co-MOF composite electrocatalyst for energy-efficient hydrogen evolution by urea-assisted water splitting
Urea oxidation reaction (UOR) offers a lower energy alternative to generate hydrogen from urea-based wastewater while simultaneously contributing to environmental remediation. However, the commercial viability of this process is hindered by the inability of the electrocatalyst to achieve higher current densities for UOR due to the competition with the OER. In this study, a cobalt-MOF-derived CoPBO/Co-MOF composite electrocatalyst was synthesized over Ni foam using a solvothermal method followed by a simple chemical reduction method for UOR. The CoPBO/Co-MOF@NF demonstrated excellent electrocatalytic bifunctional activity with low potentials of +1.32 V and ?0.095 V for UOR and HER, respectively, at 100 mA/cm2 in 1 M KOH +0.33 M urea solution. Under industrial-level alkaline conditions (6 M KOH), the potential requirement for UOR is further decreased to 1.14 V, also achieving a high current density of 1 A/cm2 at only 1.35 V, which is below the thermoneutral voltage for water splitting. Comprehensive electrochemical kinetic analysis revealed that the CoPBO/Co-MOF composite effectively combines the attributes of CoPBO, for strong OH? adsorption and CoOOH formation, with the affinity of Co-MOF for urea adsorption and CO2 desorption, leading to enhanced UOR performance. Furthermore, in a zero-gap electrolyzer configuration, the CoPBO/Co-MOF@NF catalyst demonstrated remarkable efficiency in actual cow urine (with 1 M KOH), requiring only 1.39 V to achieve a current density of 100 mA/cm2 which is 0.5 V lower than in urea-free water splitting. 2025 -
Mixed CoO/Co3O4 phase nanoparticles encapsulated in a carbon shell derived from Co-MOF as a bifunctional electrocatalyst for scalable hydrogen production
Designing high-performance and long-lasting electrocatalysts is essential to enable large-scale green hydrogen generation through water electrolysis. Herein, we present a bifunctional electrocatalyst, C@CoxOy-B/P-700, obtained by pyrolyzing a Co-MOF under N2 atmosphere, followed by phospho-boronization. Extensive characterization revealed the formation of nanoparticles composed of combined Co3O4 and CoO phases encapsulated by a thin carbon shell. This unique architecture provided electron transport and active site accessibility, while the co-incorporation of boron and phosphorus induced abundant oxygen vacancies, enhancing intrinsic kinetics. In alkaline media, low overpotentials of 220 and 79 mV are required at 10 mA/cm2 for OER and HER, along with excellent durability, maintaining performance over 10,000 cycles and 100 h of continuous operation. When implemented in a symmetric two-electrode configuration, it achieves a current density of 10 mA/cm2 at just ?1.57 V, rivalling noble-metal-based systems. Furthermore, scale-up in a zero-gap alkaline electrolyzer confirms industrial applicability, requiring ?1.72 V to achieve a 500 mA/cm2 at 60 C with a negligible degradation rate. These results emphasize the promise of C@CoxOy-B/P-700 as a sustainable and scalable solution for next-generation hydrogen production. 2025 Elsevier Ltd. -
Maximizing Bifunctionality for Overall Water Splitting by Integrating H2 Spillover and Oxygen Vacancies in CoPBO/Co3O4 Composite Catalyst
In the pursuit of utilizing renewable energy sources for green hydrogen (H2) production, alkaline water electrolysis has emerged as a key technology. To improve the reaction rates of overall water electrolysis and simplify electrode manufacturing, development of bifunctional electrocatalysts is of great relevance. Herein, CoPBO/Co3O4 is reported as a binary composite catalyst comprising amorphous (CoPBO) and crystalline (Co3O4) phases as a high-performing bifunctional electrocatalyst for alkaline water electrolysis. Owing to the peculiar properties of CoPBO and Co3O4, such as complementing Gibbs free energy values for H-adsorption (?GH) and relatively smaller difference in their work functions (??), the composite exhibits H2 spillover (HS) mechanism to facilitate the hydrogen evolution reaction (HER). The outcome is manifested in the form of a low HER overpotential of 65 mV (at 10 mA cm?2). Moreover, an abundant amount of surface oxygen vacancies (Ov) are observed in the same CoPBO/Co3O4 composite that facilitates oxygen evolution reaction (OER) as well, leading to a mere 270 mV OER overpotential (at 10 mA cm?2). The present work showcases the possibilities to strategically design non-noble composite catalysts that combine the advantages of HS phenomenon as well as Ov to achieve new record performances in alkaline water electrolysis. 2024 The Author(s). Small Science published by Wiley-VCH GmbH. -
Using Fog Computing to Accelerate Metagenomic Data Analysis
This article discusses the challenges of processing and analyzing metagenomic data, the volume of which is continuously increasing due to the development of sequencing technologies. Traditional methods such as cloud computing and supercomputing face limitations such as high latency, network dependency, high costs and data security risks. Alternatively, fog computing and hybrid architectures are proposed to distribute the computational load between local devices and cloud systems. This reduces latency, optimizes costs and improves data security. The paper analyzes the advantages of fog computing in metagenomic data analysis, compares it with traditional methods and suggests ways to implement this technology in bioinformatics. The results show that fog computing systems and hybrid systems are promising solutions for applications requiring fast analysis and high data security, such as medical diagnostics and environmental monitoring. The complexity of integrating and managing distributed systems 2025 IEEE. -
Hybrid fruit-fly optimization algorithm with k-means for text document clustering
The fast-growing Internet results in massive amounts of text data. Due to the large volume of the unstructured format of text data, extracting relevant information and its analysis becomes very challenging. Text document clustering is a text-mining process that partitions the set of text-based documents into mutually exclusive clusters in such a way that documents within the same group are similar to each other, while documents from different clusters differ based on the content. One of the biggest challenges in text clustering is partitioning the collection of text data by measuring the relevance of the content in the documents. Addressing this issue, in this work a hybrid swarm intelligence algorithm with a K-means algorithm is proposed for text clustering. First, the hybrid fruit-fly optimization algorithm is tested on ten unconstrained CEC2019 benchmark functions. Next, the proposed method is evaluated on six standard benchmark text datasets. The experimental evaluation on the unconstrained functions, as well as on text-based documents, indicated that the proposed approach is robust and superior to other state-of-the-art methods. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Assessment of mechanical and micro structural analysis of iron ore tailings and red mud sustainable bricks using multiple linear regression
The synergistic utilization of mining and industrial wastes in the construction industry represents a major step forward in the environmental and sustainable constructions. This research has presented an exploration of the feasibility of combined use of iron ore tailings (IOT) and red mud (RM) in sustainable brick manufacture. The IOT and RM have been blended with ground granulated blast furnace slag (GGBS) and lime solution for the production of bricks without high-temperature kiln-firing. Eight different combinations of (IOT + GGBS) and (RM + GGBS) with varying ratios of the principal components have been used in the sustainable bricks. Multiple regression analysis has been employed to estimate the strength of a different compositions of bricks. The bricks with 70% RM and 30% GGBS have attained the highest strength of 9.68 MPa and the bricks with 70% IOT and 30% GGBS attained the highest strength of 6.25 MPa among various combinations. The water absorption results of 18.7% and 19.02% have fulfilled the IS standards too. The research has revealed that the bonding between bricks and mortar has been influenced by the Si-Al matrix at low calcium content. Additionally, the formation of the delicate Ca-Al-Si phase capable of permeating the brick, has contributed to the constructive brick structure. The study also reinforced the view that the combined use of mining and industrial waste in production of environmentally friendly bricks is viable. The Author(s) 2025. -
Mine Waste-Based Next Generation Bricks: A Case Study of Iron Ore Tailings, Red Mudand GGBS Utilization in Bricks
Utilization of mine wastes as a building material in the construction industry surmises to environmental and sustainable concepts in civil engineering.The potential environmental threat posed by mining wastes, as well as a growing societal awareness of the need to effectively treat mining wastes, has elevated the subject importance.The present research proposes a method of producing bricks that is both cost effective and environmentally benign. The research is based on the geopolymerization, known to save energy by obviating high-temperature kiln firing and lowering greenhouse gas emissions. The methodology encompasses the mixing of red mud and iron ore tailings in the range of 90% to 50% with a decrement of 10% with GGBS in the range of 10% to 50% with an increment of 10%. The raw materials and the developed composites have been tested as per Indian and ASTM standards.In addition to tests pertaining to the physical and mechanical properties, XRF, XRD, and SEM tests have been performed for examining various related issues. Based on the result analysis, the compressive strength values showed noticeable differences in case of IOT and red mud bricks with IOT-based bricks showing better compressive strengths. 2021 M. Beulah et al. -
An Empirical Model for Geopolymer Reactions Involving Fly Ash and GGBS
Numerous works are reported in literature regarding the enhancement of compressive strength of fly ash-GGBS geopolymer combinations with addition of alkali activators of varying concentrations. However, a limited study has been chronicled, revealing the specific role of alkali or alkaline earth contributed by the fly ash-GGBS combinations on the compressive strength development. It is well known that the strength of a geopolymer is dependent on gel formation from Al/Si ratio, Ca/Si ratio, and Ca/(Si + Al) ratio but their exact role when cured for various extended periods is unknown as yet. In the present study, alkali concentration in a fly ash-GGBS geopolymer combination was varied from 6 M to 12 M with increments of two mol in six different fly ash-GGBS combinations with a minimum of 20 percent and a maximum of 70 percent GGBS. The correlation coefficients between compressive strength and Al/Si, Ca/Si, and Ca/(Si + Al) ratios exhibited values higher than 0.95 taken individually. Multiple linear regression analysis with compressive strength (as dependent parameter) and individual values of Al/Si, Ca/Si, and Ca/(Si + Al) ratios (as independent parameters) was effectuated. It was observed that, depending on the composition, the compressive strength circumstantiated a changeover from Ca/Si to Ca/(Si + Al) ratio in the intermediate composition range. Such a detailed analysis is considered supportive of developing a suitable composition which will provide the optimum compressive strength of the combination. 2022 Beulah M et al. -
An experimental study on utilisation of red mud and iron ore tailings in production of stabilised blocks
Construction of bricks using waste materials is one among the many ways to address the problems encountered in infrastructure. In the present study, various industrial and mining wastes have been used to manufacture stable bricks. These wastes include red mud (RM) from Hindalco, and iron ore tailings (IOT) from BMM Ispat, Bellary. Both RM and IOT were combined in different proportions with ground-granulated blast furnace slag (GGBS) and waste lime. In first series, IOT was replaced in the range of 45% to 60% with increments of 5%, and RM was replaced in the range of 15% to 30% with increments of 5%. In the second series, RM was replaced in the range of 45% to 60% with increments of 5%, and IOT was replaced in the range of 15% to 30% with increments of 5%. Tests were performed as per the Indian and ASTM standards on both the raw material and the developed composites. These tests include liquid, plastic limit, particle size, XRF, XRD, and SEM on raw materials, while tests performed on composites were compressive strength, water absorption, efflorescence, porosity, apparent specific gravity, and bulk density. Results of the study indicate that addition of IOT up to 55% is acceptable as brick material. Springer Nature Singapore Pte Ltd 2020. -
A Sustainability Approach to Geopolymer Brick Manufacture Using Mine Wastes
India has tons of by-products of industries like fly ash, ground granulated blast furnace slag (GGBS), and mine tailings from different ores. By incorporating these wastes in bricks, the carbon footprint can be minimized. This research pivots around the use of iron ore tailings (IOT) and slag sand as a substitute for clay or shale in the manufacture of stabilized geopolymer blocks. Iron ore tailings and slag sand were used for substitution in the range of 20-40% and 15-40% with increments of 5%. Fly ash, ground granulated blast furnace slag, and sodium silicates (Na2SiO3) were used with a constant value of 15%. The bricks were cast and cured at ambient temperature. The study includes testing of mechanical properties of geopolymer bricks as per IS recommendations. To study the macroanalysis, SEM and XRD analyses were also carried out on raw materials and developed composites. The outcomes of this investigation show that the inclusion of 25% of IOT and 30% of slag sand is acceptable as brick material. Springer Nature Singapore Pte Ltd. 2022. -
A Mathematical Correlation of Compressive Strength Among Silica, Alumina and Calcia Present in Composite Red Mud and Iron Ore Tailingbricks
Waste Red Mud generated from bauxite beneficiation in aluminium industry contains sodium oxide in minor amount along with silica and alumina in significant quantities. Waste iron ore tailings from beneficiation of iron ore in steel industry contain silica and alumina in significant quantities. A combination of both these materials in different amounts along with GGBS and lime addition resulted in complex alkali-activated reaction products consisting of (Si/Al), (Ca/Si) and (Ca/(Si+Al)) complexes which influence compressive strength of the test samples on curing for extended time periods at room temperature. Individual correlation coefficients of these complexes with compressive strength yielded high values with (Si/Al) and (Ca/Si+Al) ratios (0.92 and 0.96, respectively) while showing a poor correlation coefficient with (Ca/Si) ratio (0.88). A direct regression analysis between compressive strength and (Si/Al) ratio and (Ca/Si+Al) ratio indicated negative values with (Si/Al) ratios but positive values with (Ca/ (Si+Al)) ratios. It is therefore concluded that the addition of lime and GGBS (contributed from both GGBS and lime addition) resulted in Ca-Si-Al complex formations which are responsible for improved compressive strength of the samples. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Effect of Replacement of Cement by Metakalion On the Properties Of High Performance Concrete Subjected To Hydrochloric Acid Attack.
Vol. 2, Issue 6, November- December , pp.033-038
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Effect of Replacement of Cement By Metakalion On The Properties Of High Performance Concrete Subjected To Hydrochloric Acid Attack
Vol.2, Issue 6, November-December 2012, pp 033-038
ISSN: 2248-9622 -
Development of Genetic Algorithm based Neural Network Model For Predicting Workability and strength of High Performance Concrete.
Volume-2 Issue-6, May, ISSN 23199598 -
Development of Genetic Algorithm Based Neural Network Model for Predicting Strength of High Performance Concrete
Volume 3, Issue -2, ISSN: 2248-9622 -
Development of Genetic Algorithm based Neural Network Model for Predicting Workability and Strength of High Performance Concrete
International Journal of Inventive Engineering and Sciences (IJIES), Vol.2, Issue 6, ISSN : 2319-9598. -
A new broad-band atmospheric dispersion corrector for HROS-TMT
Atmospheric dispersion causes light from celestial objects with different wavelengths to refract at varying angles as it passes through Earths atmosphere. This effect results in an elongated image at the focal plane of a telescope and diminishes fibre coupling efficiency into spectrographs. We propose an optical design that incorporates a Rotational Atmospheric Dispersion Corrector (RADC) to address the broad-band dispersion for the multi-object mode of the High-Resolution Optical Spectrograph (HROS) on the Thirty Meter Telescope (TMT). The RADC corrects the dispersion across the entire wavelength range (0.311 ?m), using Amici prisms optimized for over 90 per cent transmission efficiency and minimal angular deviation of the beam from the optical axis after dispersion correction. For enhanced accuracy, particularly in the blue region, we have, for the first time, implemented the Filippenko model in Zemax via a custom Dynamic-Link Library (DLL) file. The Author(s) 2025. Published by Oxford University Press on behalf of Royal Astronomical Society. -
Bioconversion of Feather Composts using Proteolytic Bacillus mycoides for their Possible Application as Biofertilizer in Agriculture
Proteolytic Bacillus strains were screened for highest protease production amongst which Bacillus mycoides (G2) was chosen as an assuring protease producer. Enzyme activity was maximum at 37C, pH-7, when the medium was supplemented with 0.5 and 0.75% of sucrose and beef extract respectively. Tapioca flour and soybean meal were capable of replacing commercial carbon and nitrogen sources respectively. Feather degradation studies revealed 62% of degradation with Quail feather (QF), followed by Chicken feather (CF) (58%), Guinea fowl feather (51%) and Pigeon feather (43%). Biodegradation of feather samples in soil evidenced degradation of Quail feather and Chicken feather at the following patternQF Treatment 1 (5%) ? CF Treatment 1 (5%) ? QF Treatment 2 (10%) ? CF Treatment 2 (10%). Maximum degradation of QF and sufficient release of free amino acids into the feather compost was obvious with Field Emission Scanning Electron Microscopic (FE-SEM) and High Performance Thin Layer Chromatographic (HPTLC) analyses respectively. In vitro plant growth studies of tomato and chilly plants were accomplished with feather composts. Maximum growth of 26.44cm (shoot length) was achieved when feather compost prepared with degraded QF (5%) was utilized as plant growth substrate, than other treatment pots (P < 0.05). Plant growth was exemplary in the case of tomato when compared to that of chilly. Sound degradation of QF, followed by CF using Bacillus mycoides could strengthen the efficacy of microbial fermentation processes. This significant attempt could support poultry farms as well as organic agricultural sectors ecologically. Graphic Abstract: [Figure not available: see fulltext.] 2021, The Author(s), under exclusive licence to Springer Nature B.V. -
Hybrid Semantic Evaluation of Student Answers Using Rule Matching and BERT Embeddings
Accurate evaluation of student answers in online and traditional assessments is critical in education. In recent years, various text similarity-based methods have been proposed. However, there are certain challenges, such as the semantic and structural understanding of text. Thus, this paper uses the BERT model to present a hybrid evaluation framework that combines rule-based similarity techniques with deep semantic knowledge. The rule-based component utilizes predefined linguistic and domain-specific rules to ensure interpretability. At the same time, BERT-based similarity captures the semantic similarity and the paraphrased answers. Experimentation has been carried out on benchmark datasets, with the proposed hybrid model and human experts on manual evaluation. The performance comparison demonstrates that the hybrid model has performed significantly better than the traditional machine learning approaches in terms of accuracy and fairness of scoring. The proposed hybrid model is also compatible with deployment in educational platforms as it provides suitable feedback to learners. 2025 IEEE.