Open Access

Article

Article ID: 3955

Exploring the effect of graphite-coating on hexanary high entropy metal oxides towards efficient water electrocatalysis

by Shakeel Abbas, Akbar Hussain, Muhammad Asim, Tehmeena Maryum Butt, Banafsha Habib Ur Rehman, Javeria Arshad, Amina Hana, Sadia Kanwal, Muhammad Yasir, Naveed Kausar Janjua

Materials Technology Reports, Vol.4, No.1, 2026;

High-entropy oxides (HEOs) have emerged as promising electrocatalysts due to their high configurational entropy, modular electronic structures, and defect-rich multicationic lattices. However, modifying their electrochemical kinetics through conductive surface modification remains completely unknown. An Al-rich hexanary spinel, Cr, Cd, Fe, Mg, and Mn-based materials were synthesized using a sol-gel method and then modified with graphite (5–20 wt%) via rotary ball milling to improve conductivity and interfacial charge transfer, resulting in a stable spinel phase as validated by Rietveld-refined XRD. The addition of graphite significantly increased anodic activity, with the 10 wt% composite (HEO-10C) achieving a peak current density of 47.09 mA cm⁻² in 1 M KOH + methanol. This was followed by decreased charge-transfer resistance and better electron-transfer kinetics. The graphite-HEO interface allows for faster reaction pathways, as evidenced by a high diffusion coefficient (8.65 × 10⁻⁸ cm² s⁻¹), a heterogeneous electron-transfer rate constant (3.75 × 10⁻⁴ cm s⁻¹), and a low Tafel slope of 97 mV dec⁻¹. To better measure intrinsic activity, we add a new descriptor, Jη = (Jₚ (peak current density)−Jₒₙₛₑₜ (onset current density)), which represents the net operating current above onset. Jη correlates strongly with traditional kinetic measurements, highlighting the conductivity-driven performance gain in HEO-10C (44.59 mA cm⁻²), which is about 1.6× greater than the uncoated HEO. These findings confirm graphite coating as a viable method for modifying multication HEO electrodynamics and introduce a new measure for assessing advanced oxide-based electrocatalysts.

Open Access

Article

Article ID: 3985

Physics-informed surrogate modelling of finite-size scaling and Curie temperature suppression in ferroelectric perovskite nanostructures

by Aswin Karkadakattil

Materials Technology Reports, Vol.4, No.1, 2026;

Finite-size suppression of the Curie temperature (T_c) in ferroelectric perovskite nanostructures remains an important yet insufficiently resolved problem, with reported scaling exponents varying considerably across experimental and theoretical studies. Although density functional theory provides atomistic insight into size-dependent behaviour, its high computational cost limits systematic exploration across broad size ranges. Conversely, purely empirical fitting approaches often lack physical interpretability and formal uncertainty quantification. In this work, a physics-informed surrogate modelling framework is developed to investigate finite-size scaling in BaTiO₃ and KNbO₃ nanostructures using a structured dataset compiled from the literature. The model is based on thermodynamically motivated scaling behaviour, enabling extraction of physically meaningful size-dependent parameters. Bootstrap resampling is employed to quantify statistical robustness, yielding scaling exponents of 1.59 (95% confidence interval: 1.43–1.72) for BaTiO₃ and 1.40 (95% confidence interval: 1.31–1.52) for KNbO₃. Gaussian Process regression is further integrated to provide uncertainty-aware predictions across the nanoscale domain. In addition to forward prediction, the framework enables inverse estimation of the minimum particle size required to preserve ferroelectric stability at a specified operating temperature. For a threshold of 300 K, the predicted critical sizes are approximately 4.96 nm for BaTiO₃ and 2.89 nm for KNbO₃. Extension to a coupled size–strain formulation produces a two-dimensional stability map, demonstrating tunable interactions between confinement and strain. Overall, the proposed methodology provides a transparent, statistically rigorous, and computationally efficient framework for predictive analysis and rational design of nanoscale ferroelectric materials.

Open Access

Article

Article ID: 3988

Density effect on erosion mechanisms in silica-phenolic solid rocket motors insulations

by Jacob Nagler

Materials Technology Reports, Vol.4, No.1, 2026;

The design of lightweight Internal Thermal Protection Systems (ITPS) for solid rocket motors is constrained by the non-linear degradation of erosion resistance at low densities. The primary motivation for this work is the discrepancy often observed between standard design models and flight data, specifically in regions of complex flow such as the aft-dome and submerged nozzle inlets. This study establishes a physics-based constitutive law to predict the transition from thermochemical ablation to mechanical spallation in silica-phenolic composites. Unlike semi-empirical correlations, we derive an Augmented Density-Erosion Model from first principles by coupling the energy conservation equation with Gibson-Ashby cellular solids mechanics. We analytically demonstrate that the mechanical erosion rate scales with density according to a power law (r˙∝ ρ^−β) , where the exponent β ≈ 1.5 corresponds to the fracture toughness scaling of open-cell porous foams. This theoretical framework resolves the "spallation gap", the under-prediction of recession by standard heat-of-ablation models (Q^∗) in low-density felts (ρ < 600 kg·m⁻³). The model is validated against historical firing data, demonstrating that the erosion mechanism shifts from energy-limited to strength-limited regimes as density decreases. Furthermore, we address the practical application of these findings by quantifying "danger zones" in density space for graded insulation architectures. This work provides propulsion designers with a rigorous methodology for determining safety margins in mass-critical motor stages, ensuring structural integrity is not compromised by the pursuit of weight reduction.

Open Access

Review

Article ID: 3805

Basic artificial intelligence for metallurgical design of acicular ferrite in weld metal

by Krishnaswamy Sampath

Materials Technology Reports, Vol.3, No.2, 2025;

Demand-critical applications require high strength steel (HSS) weldments with a significant spread between yield strength (YS) and ultimate tensile strength (UTS). Predominantly acicular ferrite (AF) microstructure in weld metal (WM) of a Fe-C-Mn-Ni based system is suitable for joining HSSs for demand-critical applications. Controlling carbon content in WM below 0.10 wt-%, actual or calculated transformation-start (T_S) temperature between 630 °C and 730 °C and weld cooling rate (CR) is critical in generating a high-performance AF microstructure. The Japan Welding Engineering Society (JWES) offers an artificial neural network (ANN) template at its website which is helpful in manipulating the addition of 16 elements in WM, each within a restricted range. This manipulation allows one to lower the T_28J/°C Charpy V-notch (CVN) test temperature of WM below −80 °C for achieving 28 Joules impact energy. Secondly, a New A_r3 equation obtained using regression analysis through Machine Learning, enables manipulation of 14 elements (except P and S) in WM (all in wt-%) and weld CR (in °C/s) in achieving a predominantly AF microstructure in WM. Dilatometric analysis of selected WMs with Ti-B-Al-N-O content and limited N content below 85 ppm (0.0085 wt-%) showed that these two supplementary approaches can achieve a nearly “balanced” Ti-B-Al-N-O micro-alloying addition in WM. The above two tools allow welding engineers to use basic Artificial Intelligence (AI) system in evaluating or recognizing welding electrodes and related WMs that ensure adequate spread between YS and UTS, and a predictive T_28J/°C test temperature below −80 °C for demand-critical applications.

Open Access

Article

Article ID: 3519

Enhancing the environmental sustainability and performance of drilling fluids through the incorporation of silica nanoparticles and aloe vera powder extracts

by Ahmed Sabri, Anas Elhederi

Materials Technology Reports, Vol.3, No.2, 2025;

This research explores the use of Aloe Vera powder and silica nanoparticles (SNPs) as environmentally friendly additives aimed at enhancing the rheological and filtration performance of water-based drilling muds. The work evaluates how different concentrations of SNPs (0.2 g, 0.3 g, and 0.4 g) combined with Aloe Vera affects key drilling fluid properties, including mud density, plastic viscosity, apparent viscosity, yield point, pH, gel strength, and filtration performance before and after hot rolling. The findings indicate that Aloe Vera alone can improve the drilling mud’s rheology by increasing its viscosity and suspension ability, while also contributing to a noticeable reduction in pH. When paired with SNP, the interactions between the biopolymer and nanoparticles create a synergistic effect, especially at 0.3 g and 0.4 g SNP concentrations. At these levels, mud demonstrated better viscosity behavior, higher yield point values, and more effective control of fluid loss, suggesting a more reinforced internal structure. However, thermal stability declined after hot rolling, implying that high temperatures may weaken or alter the intermolecular forces responsible for the enhanced performance under normal conditions. Overall, the study demonstrates that blending Aloe Vera with SNPs offers a promising, sustainable approach to improve drilling fluid behavior while supporting more environmentally responsible drilling operations.

Open Access

Article

Article ID: 3084

Fluoride-ion batteries: The future of high-energy, safe, and sustainable energy storage

by Shakila Akter, Nur Mohammad Badhon, Dil Mohammad, Md. Abid, Razu Shahazi, Md. Rahim Uddin, Md. Mahmud Alam

Materials Technology Reports, Vol.3, No.2, 2025;

Fluoride-ion batteries (FIBs) are emerging as a potential alternative to lithium-ion batteries, offering higher energy densities, improved safety, and the use of more abundant and sustainable materials. Recent advancements in fluoride-ion technology have focused on addressing key challenges, such as the low ionic conductivity of fluoride and the development of suitable electrode materials. Researchers have made progress in creating electrolytes that stabilize fluoride ions during charging and discharging, leading to prototypes with enhanced cycling stability and energy capacity compared to earlier models. However, issues like corrosion and the need for more efficient energy storage remain significant barriers. Ongoing research is dedicated to finding novel materials that can improve conductivity, as well as to developing corrosion-resistant components that will enhance the longevity and safety of fluoride-ion batteries. Additionally, improving the overall energy efficiency and scalability of production is crucial for future commercialization. If these challenges are successfully overcome, fluoride-ion batteries could offer a transformative solution for high-energy applications, including electric vehicles, portable electronics, and large-scale grid energy storage. As research progresses, fluoride-ion batteries hold the potential to become a key technology in the quest for more sustainable, high-performance energy storage systems.