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Experimental data-driven machine learning approach for predicting workability in sustainable concrete using green material replacements
Concrete workability is a critical factor governing the placement, compaction, and durability of fresh concrete, yet it remains less explored in data-driven studies compared to hardened properties. This study presents an experimentally validated machine learning framework for predicting fresh concrete workability, namely Compaction Factor Equivalent (CFE) and Vee Bee Time Equivalent (VBTE), using a newly generated laboratory dataset comprising 300 concrete mixes. The dataset was developed through controlled experiments by systematically varying the waterbinder ratio (W/B), aggregatebinder ratio (A/B), type of green material, and replacement percentage, with fly ash and ground granulated blast-furnace slag (GGBS) used as partial cement replacements to promote sustainability, aligning strategies with SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production). To capture the nonlinear relationships between mix design parameters and workability indicators, three ensemble learning modelsRandom Forest (RF), Gradient Boosting (GB), and Extreme Gradient Boosting (XGBoost)were developed and evaluated. Model performance was assessed using standard statistical metrics, including R, RMSE, MAE, and MAPE. The results indicate that boosting-based models outperform baseline approaches, with XGBoost achieving the highest prediction accuracy for both CFE and VBTE. By shifting the focus from hardened properties to fresh-state performance, this study addresses a critical research gap and demonstrates that ensemble machine learning models, when combined with experimentally generated datasets, can significantly reduce experimental workload while supporting intelligent and sustainable concrete mix design for practical engineering applications. 2026 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC license. http://creativecommons.org/licenses/by-nc/4.0/ -
Natural biotic polymer bombyx mori silk fibroin for gold nanoparticles: Fabrication, characterisations and application as colorimetric ammonia detection
Gold nanoparticles (AuNPs) were fabricated using a cost-effective and environmentally benign method, using silk fibroin (SF) as a stabilizing and reducing agent. As a natural, renewable protein polymer, silk fibroin can reduce and stabilize material as well as provide shape-tailoring agent. This resulted bio-polymer with gold nanoparticles was biodegradable, biocompatible, and very stable. Au ions are proficiently reduced to neutral Au atoms by silk fibroin, which governs the size, shape, and distribution of the nanoparticles and, consequently, their optical characteristics. The fabricated nanoparticles are very well characterized using a set of advanced analytical techniques that include UV-Vis Spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Transmission Electron Microscopy (TEM), and Fluorescence Spectroscopy (FL). The sensing performance of ammonia in aqueous ammonia using the SF-AuNPs is presented herein based on an optical sensing approach utilizing surface plasmon resonance (SPR). It is obvious from the results that the materials synthesized have exhibited some unique plasmonic properties due to the interaction between silk fibroin and gold surfaces, hence enhanced sensitivity in colorimetric detection. The AuNPs acted as an ammonia optical sensor with a detected limit of about 1 parts per billion (ppb), very outstanding performance. Ammonia and AuNPs interact to cause a change in their surface plasmon resonance simple rapid and low-cost to realize, eco-friendly, and can find applications towards environmental monitoring and biomedical research fields for ammonia detection. 2026 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/ -
Highly strengthened mechanical, morphological, IR vibrational and optical properties of rationally tailored wheat starchchitosan blends crosslinked with dual UV/acetic acid system for sustainable green packaging
Through this study, wheat starch/chitosan composite (SCB) films were successfully developed via a UV/acetic acid-assisted solution?casting approach with varying chitosan ratios. Tensile testing shows that stress at break remains nearly unchanged at lower chitosan content (1030?wt%) but increases abruptly beyond 30?wt%, reaching an optimum value at 50?wt% due to intensified hydrogen bonding and cross-linking between chitosan NH?? and starch OH? groups. Strain at break follows a similar trend, with markedly elevated elongation and elasticity. Youngs modulus exhibits the highest rigidity at 50?wt%, while stiffness decreases thereafter, consistent with enhanced elastic deformation. Morphological analysis reveals that chitosan incorporation transforms starch films from brittle, cracked surfaces to densely compact structures with fewer pore defects, resulting in superior adhesion and integrity. UVvis results show improved UV shielding, higher transparency, and tunable absorption, while FTIR analysis confirms only physical interactions with no new bonds formed between the components. Overall, chitosan incorporation significantly fortifies the SCB films by improving mechanical strength, structural stability, and optical performance, extending their application as green, multifunctional materials for sustainable packaging, coatings, and wastewater treatment. 2026 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/ -
Sustainable removal of reactive blue 222 dye from aqueous solution using wheat bran
Water pollution is one of the major concerns, and establishing a potential sustainable approach can ensure effective water resource management. Textile dye pollution poses a major environmental challenge due to its toxicity and persistence in water bodies. Conventional dye removal methods are often costly and inefficient, necessitating the exploration of low-cost, sustainable adsorbent materials. This research explores the potential of natural wheat bran (WB), an agro-industrial by-product, as an economical and environmentally beneficial bio-adsorbent for the removal of RB222 dye. Adsorbent concentration (0.56?g/100?mL), Initial dye concentration (501000?mg/L), pH (3?11), and contact time were among the major influencing variables assessed to optimise the adsorption process. The structural and morphological changes in wheat bran before and after adsorption were examined to confirm their active role in the adsorption process. Some of the characterisation techniques, like Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), Energy-Dispersive X-ray Spectroscopy (EDS), X-ray Diffraction (XRD) and Zeta Potential Analysis, were performed to highlight the changes in wheat bran due to Reactive Blue 222 (RB222) adsorption. This study aims to evaluate the feasibility of using wheat bran as a low-cost bio-adsorbent for the efficient removal of Reactive Blue 222 dye from wastewater. The findings showed that wheat bran had a high adsorption capacity of 9.65?mg/g with the best dye removal efficiency of 96% under optimal conditions. Adsorption kinetics studies confirmed that the process follows the Freundlich isotherm and the pseudo-second-order model. The desorption study was also performed to examine its regenerative and reusability potential in the removal of dye. The study proves that wheat bran is a cost-effective and environmentally friendly substitute for dye removal from wastewater and emphasises the extension of value addition to agricultural waste in environmental rehabilitation. These findings highlight the potential of agro-waste valorisation in advancing sustainable wastewater treatment technologies. 2026 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC license. http://creativecommons.org/licenses/by-nc/4.0/ -
Synergistic utilisation of waste coconut fibers, sugarcane bagasse ash, and recycled aggregates in geopolymer paver blocks
The use of industrial and agricultural waste such as ground granulated blast furnace slag (GGBS), recycled coarse aggregates (RCA), sugarcane bagasse ash (SCBA), and waste coconut fibers (WCF) have great potential in development of sustainable construction materials. In this study, geopolymer paver blocks were prepared with GGBS and SCBA as precursors, natural coarse aggregates (NCA) partially replaced with RCA as filler material, and WCF used as an additive. To understand the synergy of these materials, SCBA and WCF was incorporated in a fixed dosage, with varying replacement rates of RCA. GGBS was replaced with 20% SCBA, NCA was replaced with 25% and 50% RCA, and a constant dose of 1% WCF was incorporated in the geopolymer mix. The developed paver blocks were tested for compressive strength, split tensile strength, flexural strength, resistance to abrasion, and water absorption. The results obtained demonstrate that addition of RCA, SCBA, and WCF do not benefit the compressive strength, split tensile strength, and water absorption of the paver blocks. However, the flexural strength and resistance to abrasion have shown significant improvement in the presence of RCA, WCF, and SCBA. This research also develops linear regression models to predict strength properties and water absorption of the paver blocks. The results indicate that linear regression model can be used to predict the compressive strength, split tensile strength, and flexural strength with an accuracy of 85%, 96%, and 71%, respectively. Overall, the developed geopolymer paver blocks with RCA, SCBA, and WCF meet the standard requirements of IS 15658: 2021 for pavement applications, and a significant improvement in the flexural strength and resistance to abrasion will enhance the durability and longevity of the paver blocks in service. 2026 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/ -
Fabrication of LaCoO3/g-C3N5 Z-scheme photo catalyst for Allura Red dye degradation, ascorbic acid sensing and hydrogen evolution studies
Production of hydrogen by water splitting through photocatalytic process under visible light from waste water is one of the potential green energy technologies. In this study, LaCoO3, g-C3N5, LaCoO3/g-C3N5 (1:1), (1:2) and (2:1) weight ratio nanocomposites (NCs) have been successfully synthesized using a solution combustion, hydrothermal and probe sonication method. The X-Ray Diffraction (XRD) confirmed the compound formed with the crystal size range 20 ?30?nm. The studies of Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) verify the morphology of the particles; band gap of the range 1.52?eV identified from Ultraviolet-Visible (UVvis) studies. The findings demonstrate that Z-scheme heterostructures have developed on the interfaces between the layered flake-like g-C3N5 and the perovskite-type oxides LaCoO3, which improve the absorption of visible light, the separation of photogenerated electron-hole pairs, and the transformation of photogenerated electrons. From the different ratio of synthesized nanoparticles (NPs), the LaCoO3/g-C3N5 (2:1) shows enhanced photocatalytic activity of 99.87?% for degradation of Allura red dye in visible light irradiation. For the first time, the produced nanomaterials were tested for ascorbic acid sensing at extremely low concentrations with a 0.12??M detection limit. The prepared nanomaterials were assessed for their electrocatalytic water splitting operation. Especially, the nanomaterial, LaCoO3/g-C3N5 (2:1) reveal exceptional hydrogen evolution reaction (HER) and also oxygen evolution reaction (OER) capabilities with overpotential of 79?mV and 450?mV, respectively. Hence, the prepared nanomaterials are used for multifunctional applications. 2026 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/ -
Sustainable synergies: Performance evaluation of cement mortar with red mud and industrial by- products
This study examines the potential of red mud, a by-product of the alumina industry, as a partial replacement for cement in mortar, aiming to advance sustainable construction in line with UN SDGs 9, 11, and 12. Red mud was incorporated at 1090 % by weight, together with 4 % Ground Granulated Blast Furnace Slag (GGBS) or 4 % fly ash as supplementary cementitious materials. The mixes were tested for compressive strength, flexural strength, water absorption, apparent porosity, and bulk density at 3, 7, and 28 days. The optimum performance was achieved with 3040 % red mud and GGBS, yielding a 28-day compressive strength of 19.29 MPa and flexural strength of 4.55 MPa, outperforming both control and fly-ash-based mixes. Higher red-mud levels increased water absorption (approximately 18 %) and porosity (approximately 15 %). Microstructural analyses (SEM-EDX, XRD, FTIR) confirmed the formation of Calcium Silicate Hydrate (C-S-H), Calcium Aluminate Hydrate (C-A-H), and ettringite phases. The research introduces a novel tri-component binder system (cement-red mud-GGBS/fly ash) that transforms industrial waste into a durable, low-carbon construction material, promoting resource circularity and carbon reduction. 2025 The Authors -
Synthesis of polypyrrole silver graphene ternary nanocomposite and its thermal diffusivity study by thermal lens method
Efficient thermal management materials with tunable thermal diffusivity are increasingly required for advanced electronic, photonic, and energy applications. However, simultaneously achieving both thermal conductivity enhancement and thermal insulation within a single material system remains a significant challenge. In this work, we have synthesized polypyrrole silver graphene (PPy/Ag/Gr) ternary nanocomposites with varying concentrations of graphene by a simple one-pot chemical synthesis method.The photoluminescence spectrum of all the samples of PPy/Ag/Gr showed a quenching in the intensity due to the presence of graphene. Raman spectrum analysis confirmed good coordination of silver and graphene in the ternary composite. Morphological study was done using field emission scanning electron microscopy (FESEM). The thermal diffusivity of the binary composites polypyrrole silver (PPy/Ag) and polypyrrole graphene (PPy/Gr) as well as the ternary composites with varying concentrations of graphene were done using the highly sensitive thermal lens method using two laser sources, one as a pump source and the other as a probe beam. The results of the study show that the thermal diffusivity (D) of PPy/Ag/Gr with 0.2 wt.% of graphene is slightly greater than the binary composites and can be used as a coolant. Another exciting result of this study is that at higher concentrations of graphene the D values of the ternary composites decrease below the D value of the base fluid used. This interesting property of the samples can be exploited by using them as thermal insulators 2025 The Authors -
Machinability and surface integrity for Mg AZ61A alloy composite by employing Taguchi integrated grey relational analysis
The present experimental study seeking to identify the optimal processing parameters in WEDM of Mg AZ61A-ZrB2 composite using Taguchi integrated grey relational analysis (GRA). Wire-cut electric discharge machining (WEDM) is the most effective method of metal removing process which is utilized in a variety of industries, like defence, biomedical, automotive, and aerospace. It is widely used in the machining of conductive and hard materials like composites and super alloys. In this experiment, the Mg AZ61A alloy composite reinforced with 12 wt% ZrB2 particles was fabricated through stir casting method. The scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) mapping ensured the presence of matrix elements and reinforcement in the developed composite. The material removal rate (MRR) and surface roughness (Ra) were examined with relation to the processing factors such as pulse current (Ip), pulse on-time (Ton), and pulse off-time (Toff). The machining was conducted in compliance with Taguchi's L9 array. According to the GRA results, the optimal ranges of factors for achieving the better MRR and Ra were found at 4 amps of Ip, 15 ?s of Ton, and 45 ?s of Toff. The ANOVA results confirm that Ip was the most dominating factor that contributing to 37.58 %, next by Ton (30.96 %) and Toff (12.85 %), respectively. The confirmation test was demonstrated that the actual and predicted GRG values are fairly close to one another with 13.36 % improvement. The morphology of the machined surface was examined and it was shows the formation of a recast layer and the existence of flaws. 2025 The Authors -
Predicting electric vehicle performance metrics using a convolution neural network-gated recurrent unit-attention based deep learning architecture
The indicators of electric vehicle performance such as state of charge (SOC), remaining useful life (RUL), and charge demand need to be accurately forecasted to ensure maximum energy control and battery life. The models used are usually not able to capture the spatial and temporal correlation of battery data and be robust to the presence of noisy measurements. In this study, we model a sequential attention-based deep learning structure with convolutional neural networks, gated recurrent units, and an attention mechanism that can ultimately understand the local features, temporal relationships, and dynamic significance of various features in sequential battery data. The hybrid architecture of this model allows it to extract local spatial features, long-term sequential dependencies and dynamically find the importance of the critical time steps. We also develop a hybrid loss that is an accumulation of Huber loss and Mean Squared Error, which is much more resilient to outliers and at the same time has high prediction accuracy. It is experimentally proven that the proposed model has R2 values of 0.9575, 0.9558, and 0.9199 on SOC, RUL, and charge demand, respectively, which are better than the current single-architecture methods. 2026 The Authors -
Categorizing Mental Stress: A Consistency-Focused Benchmarking of ML and DL Models for Multi-Label, Multi-Class Classification via Taxonomy-Driven NLP Techniques
Mental stress, a critical concern worldwide, necessitates precise and nuanced characterization. This study introduces a novel approach to effectively characterize mental stress through a multi-label, multi-class classification framework through natural language processing techniques. Building on existing literature, discussions with psychologists and other mental health practitioners, we developed a taxonomy of 27 distinctive markers spread across 4 label categories; aiming to create a preliminary screening tool leveraging textual data. The core objective is to identify the most suitable model for this complex task, encompassing comprehensive evaluation of various machine learning and deep learning algorithms. we experimented with support vector machines (SVM), random forest (RF) and long short-term memory (LSTM) algorithms incorporating various feature combinations involving Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA). The best performer of this comparative study was further evaluated against an LLM. The potential of large language models (LLMs), including their language understanding and prediction capabilities, is another key focus. We explore how these models could augment and advance mental health research, offering new perspectives and insights into the characterization of mental stress. Our findings show that the top model, an LSTM with TF-IDF and LDA (class weights assigned) outperformed the PaLM model with a coefficient of variation as low as 0.87% across all labels. Despite the PaLM model's superior average performance, it exhibited higher variability among different labels. 2025 The Author(s) -
Integrating brain-inspired computation with big-data analytics for advanced diagnostics in neuroradiology
Introduction: Neuroradiology encounters considerable difficulties owing to imaging data's intricacy and high-dimensional characteristics. Conventional diagnostic techniques often encounter challenges regarding precision and scalability, resulting in delays and possible misinterpretations. This paper presents the Big-Data Analytics-based Diagnostics (BDA-D) framework, a revolutionary method using computational models derived from neural architectures and sophisticated analytics to tackle these difficulties. Methods: The BDA-D architecture utilizes data mining, pattern recognition, and machine learning to glean useful neuroanatomical characteristics from massive datasets. By simulating human thought processes, this method speeds up clinical decision-making and improves diagnostic accuracy. To evaluate the effectiveness of the framework, it is put to the test in a clinical environment. Results and Discussion: Diagnostic precision, processing speed, and dependability are all enhanced by experimental validation. By detecting even the most minute neuroanatomical changes, BDA-D allows for more accurate diagnosis than traditional approaches. Based on the results, neuroradiologists may improve their practices by using cutting-edge computational methods to close the gap between data-driven analytics and their practical use in the clinic. BDA-D discovers important patterns from high-dimensional neuroimaging data through biologically inspired neural networks, reaching a remarkable diagnosis accuracy of 97.18%. Its 95.42% increase in processing speed allows rapid study of important disorders such as strokes and neurodegenerative diseases. BDA-D reduces inter-observer variability with a dependable value of 94.96%, increasing clinical confidence in AI-assisted diagnosis. Conclusion: A revolutionary change in neurodiagnostics, the BDA-D framework improves efficiency and reliability. This method has the potential to completely transform neuroradiology by combining big-data analytics with sophisticated computer models. It will allow for more rapid and precise diagnosis. 2025 The Authors -
Layered natural oxide based soft actuators for controlling artificial motion by chemical stimulus
The chemical stimuli-based soft-actuators with complex actuation properties are of significant interest in the field of biomechanical and biomedical applications such as prosthetics. Soft actuators can manipulate and precisely control the fluid motion at the microscale and may play an important role in fluid transportation in many biological systems. Here, we have presented a two-dimensional (2D) material-based 3D printed system for the fabrication of porous soft actuators that display different actuations under the organic fluid stimulus. The few atomic layered thin chromite sheets (natural ores) show significant changes in their physical properties due to the strong interaction with organic molecules. The composite film is capable of showing controllable and sophisticated motions such as twisting, bending, rolling, and flipping in response to chemical stimuli. The introduction of porosity in the composite film dramatically increases the dynamic performances, detection range, and sensitivity. As a result, a high actuation (twisting angle) of ?540 5 and response time of ?0.9 s was achieved, which significantly enhanced the device performance. Finally, to offer further flexibility and controlled structural alterations, we designed a snail, leaf, and worm-like soft actuators that expand the practical applications. 2025 Elsevier Ltd -
Synthesis and third-order nonlinear optical properties of PEGylated platinum nanoparticles
PEGylated platinum nanoparticles, which are capped with polyethylene glycol-400, are synthesized through the chemical reduction technique. The sample was comprehensively characterised through UVvisible spectroscopy, X-ray diffraction (XRD) and transmission electron microscopy (TEM). XRD pattern for the sample revealed a face-centered cubic crystalline phase of platinum, with a lattice constant of 3.939 The average particle size, obtained from high-resolution electron microscopy analysis, is 3.73 nm. The third order NLO features were explored through the Z-scan technique, employing a continuous wave regime. The observed phenomena of nonlinear absorption (NLA) and nonlinear refraction (NLR) are attributed to reverse saturable absorption and thermal lens models. NLR index was measured to be in the range of 5.72 10?10 cm2/W, while NLA coefficient was found to be in the range of 1.86 10?5 cm/W, highlighting the potential of PEGylated Pt NPs for NLO applications. 2025 Elsevier B.V. -
Investigation of 1,1?-Binaphthalene-2,2?-diamine as an organic electrode for High-Performance aqueous rechargeable Lithium-Ion batteries
Aqueous rechargeable lithium-ion batteries (ARLIBs) are the most remarkable energy storage devices currently available for various applications with a growing demand for high-performance batteries. The role of electrochemical analysis for lithium-ion batteries, especially electrode reactions, is widely observed in many fields of electrochemical techniques, such as cyclic voltammetry (CV), which is one of the methods that is possible to know the electrochemical factors affecting the reaction voltage and reversibility. This study contributes to the ongoing development of ARLIBs by investigating 1,1?-binaphthalene-2,2?-diamine (BINAM) as a potential organic electrode material. The comprehensive structural and electrochemical characterization is emphasized by the principle of CV and its applications to better understand the electrochemical reactions and the battery performance results, highlighting the viability of BINAM for future ARLIB applications. The cell BINAM | Sat.Li2SO4 | LiMn2O4 delivered its specific 325/155 mAhg?1 capacity and columbic efficiency of ? 9285 %. These findings underscore the importance of considering organic electrode materials and their unique advantages in enhancing the efficiency, sustainability, and cost-effectiveness of lithium-ion battery technology. 2025 Elsevier B.V. -
Facile synthesis of Bi2WO6-NiO nanocomposite for supercapacitor application
In order to prepare for future high-power storage-related applications, a tremendous amount of studies have been conducted on the manufacturing of high-performance supercapacitor electrodes. The hydrothermal technique was used to synthesize Bi2WO6NiO nanocomposite (NC), which was examined using FTIR, XRD, HR-TEM, EDX, FESEM, and XPS techniques. Furthermore, the Bi2WO6-NiO NC performs with an elevated specific capacity of 398.2C/g at 10 mV/s. The charge transfer resistance (Rct) and solution resistance (Rs) of Bi2WO6-NiO NC were determined as 0.81 and 0.23 ? using electrochemical impedance spectra (EIS). Bi2WO6-NiO NC extended the chargedischarge time and rate capacities, as shown by the galvanostatic chargedischarge (GCD) analysis. Even after 2000 cycles, Bi2WO6-NiO NC cyclic stability was superior with a capacitive retention of 89.3 %. A power density of 6750 W/kg resulted from the constructed asymmetric supercapacitor (ASC) device based on Bi2WO6-NiO/AC, exhibiting an energy density of 32.5 Wh/kg. Additionally, the ASC maintains high cyclic stability with 90.8 % of initial capacity, even after 2000 chargedischarge cycles in a row. 2024 Elsevier B.V. -
Development of biocompatible NiTi@?-TCP nanocomposite with improved antibacterial and anticancer activities for bone-related biomedical applications
In the present study, ?-TCP and NiTi@?-TCP nanocomposite were synthesized using a modified solgel method. DLS analysis revealed hydrodynamic particle sizes of ?290 nm for ?-TCP and ?231 nm for NiTi@?-TCP, suggesting improved dispersion after NiTi modification. Optical studies showed a red shift in UVVis absorption from 321 nm (?-TCP) to 396 nm (NiTi@?-TCP) with a reduced band gap from 3.8 eV to 3.1 eV, indicating enhanced electronic interactions. Morphological analysis using SEM and HRTEM revealed nanoscale particles (?1530 nm) with clear lattice fringes and polycrystalline diffraction patterns. The NiTi@?-TCP nanocomposite exhibited enhanced antibacterial activity against S. aureus, S. pneumoniae, K. pneumoniae, and Escherichia coli, producing inhibition zones of 17, 13, 14, and 12 mm, respectively, compared with approximately 10 mm for pure ?-TCP. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values for S. aureus were 0.3 mg mL? and 0.5 mg mL? for NiTi@?-TCP, respectively, which were lower than those of ?-TCP (MIC 0.5 mg mL?; MBC 0.7 mg mL?). Histidine scavenger experiments demonstrated that reactive oxygen species (ROS) play a dominant role in bacterial inhibition. Biocompatibility studies using L929 fibroblast cells showed high cell viability (>87% at 150 ?g mL?), confirming good cytocompatibility. In contrast, the nanocomposite exhibited enhanced anticancer activity against MG-63 osteosarcoma cells, with an IC?? value of 115 ?g mL?, compared with 138 ?g mL? for ?-TCP. These results demonstrate that NiTi@?-TCP nanocomposite possesses improved antibacterial and anticancer properties while maintaining good biocompatibility, making it a promising multifunctional biomaterial for biomedical and bone-related therapeutic applications. 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Green synthesis of biocompatible sodium alginate-coated bismuth oxide nanoparticles using Bougainvillea glabra flower extract with enhanced activity against pathogenic microorganisms and HT-29 colorectal cancer cells
Colorectal cancer is a leading cause of cancer-related deaths, highlighting the urgent need for effective treatments. Similarly, rising antibiotic resistance emphasizes the demand for new antimicrobial drugs. In response, the present study uses Bougainvillea glabra (B. glabra) as a capping agent to synthesis sodium alginate-doped bismuth oxide (SABO) and environmentally friendly bismuth oxide (BO). SABO exhibited smaller particle size (25 nm) and higher crystallinity compared to BO (42 nm). SEM analysis revealed rock-stone-like morphology with average particle sizes of 42 nm for BO and 25 nm for SABO, indicating smaller and better-dispersed particles in SABO. UVVis DRS analysis showed a red shift in absorbance from 387 nm (BO) to 397 nm (SABO) and a band gap decrease from 2.7 eV to 2.3 eV, suggesting enhanced electronic conductivity and increased reactive oxygen species (ROS) generation. Gram-positive bacteria (S. aureus and S. pneumoniae), Gram-negative bacteria (E. coli and K. pneumoniae), and fungi (C. albicans) were all tested for antibacterial activity using BO and SABO. With minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values of 800 and 1000 g/mL, respectively, SABO showed more activity in the zone of inhibition than the other nanoparticles. Furthermore, the anticancer activity of BO and SABO against HT-29 colorectal cancer cells showed greater efficacy for SABO, with a lower IC50 concentration of 8.1 ?g/mL. These findings suggest that SABO could serve as a multifunctional antimicrobial and anticancer agent in the biomedical field. 2026 Elsevier B.V. -
Anticancer potential of Ru(II) Schiff base complexes derived from picolinaldehyde and pyrazolyl amines: structural characterization and selective cytotoxicity toward SiHa cells
Herein, we report the synthesis, complete structural characterization including spectroscopic and computational analyses, and in vitro anticancer efficacy assessment of three Ru(II) complexes against cervical carcinoma (SiHa) cell lines. Various spectroscopic techniques such as FTIR, 1H NMR, 13C NMR, 19F NMR and ESI-LCMS mass spectrometry were used to thoroughly characterize the synthesized ligands and the complexes. Density Functional Theory (DFT) calculations provided insights into their optimized geometry and electronic parameters, which were consistent with experimental observations. The cytotoxicity of three Ru(II) complexes was evaluated against SiHa and normal fibroblast (3T3-L1) cells using MTT assays at concentrations of 10100 g/mL for 2472 h, with 20 g/mL used for detailed temporal evaluation. All complexes showed strong, dose and time dependent cytotoxicity, reducing SiHa cell viability to 24 4%, 23 6%, and 33 5% respectively for complex 1, 2 and 3 after 72 h, while maintaining >90% viability in fibroblasts. The IC?? values for complex 1, 2 and 3 (8.7 2.5, 8.4 2.3, and 7.8 1.5 g/mL) confirmed high potency and selectivity. Acridine orange and ethidium bromide (AO/EB) staining indicated apoptosis as the main cell death pathway, supported by morphological changes such as membrane blebbing and rounding. The DNA binding studies reveal that all the complexes have strong affinity toward DNA and interacted through intercalation mode. These findings highlight the complexes as selective and promising anticancer agents. 2025 Elsevier B.V. -
Green synthesis of NiTiO? and tartaric acid-coated NiTiO? nanoparticles using Tagetes erecta: Characterization and biological applications
This study investigated the environmentally friendly synthesis, structural characterization, and biomedical potential of nickel titanate (NiTiO?) nanoparticles (NPs) prepared using Tagetes erecta (marigold) flower extract, with particular emphasis on their tartaric acid-coated, functionalized derivative (NiTiO?-T NPs). Structural analyses via FTIR spectroscopy revealed functional groups characteristic of the tartaric acid coating on NiTiO?-T NPs, while XRD confirmed the crystalline hexagonal phase for both NiTiO? and NiTiO?-T NPs. FESEM images demonstrated that both types of NPs exhibited uniform, spherical morphologies. Biomedical evaluations highlighted the enhanced efficacy of NiTiO?-T NPs, which achieved 85.2 % DPPH radical scavenging at 100 ?g/mL, significantly outperforming uncoated NiTiO? NPs (72.4 %). Antimicrobial testing against various pathogens showed that NiTiO?-T NPs generated larger inhibition zones compared to their counterparts, effectively targeting Gram-positive bacteria (S. aureus, B. subtilis), Gram-negative bacteria (E. coli, P. aeruginosa), and fungi (C. albicans). Further analysis revealed notably lower minimum inhibitory concentrations (MICs: 1000 ?g/mL) and minimum bactericidal concentrations (MBCs: 1500 ?g/mL) for NiTiO?-T NPs, confirming their potent bactericidal action. These findings position tartaric acid-functionalized NiTiO?-T NPs as promising candidates for dual-functional therapeutic applications. 2025