Journal Articles
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Item Microstructure and corrosion behavior of laser processed NiTi alloy(Elsevier Ltd, 2015) Marattukalam, J.J.; Singh, A.K.; Datta, S.; Das, M.; Balla, V.K.; Bontha, S.; Kalpathy, S.K.Abstract Laser Engineered Net Shaping (LENS™), a commercially available additive manufacturing technology, has been used to fabricate dense equiatomic NiTi alloy components. The primary aim of this work is to study the effect of laser power and scan speed on microstructure, phase constituents, hardness and corrosion behavior of laser processed NiTi alloy. The results showed retention of large amount of high-temperature austenite phase at room temperature due to high cooling rates associated with laser processing. The high amount of austenite in these samples increased the hardness. The grain size and corrosion resistance were found to increase with laser power. The surface energy of NiTi alloy, calculated using contact angles, decreased from 61 mN/m to 56 mN/m with increase in laser energy density from 20 J/mm2 to 80 J/mm2. The decrease in surface energy shifted the corrosion potentials to nobler direction and decreased the corrosion current. Under present experimental conditions the laser power found to have strong influence on microstructure, phase constituents and corrosion resistance of NiTi alloy. © 2015 Elsevier B.V.Item Effect of heat treatment on microstructure, corrosion, and shape memory characteristics of laser deposited NiTi alloy(Elsevier Ltd, 2018) Marattukalam, J.J.; Balla, V.K.; Das, M.; Bontha, S.; Kalpathy, S.K.The aim of this work is to study the effect of heat treatment on the microstructure, phase transformations, shape memory characteristics and corrosion behaviour of laser deposited equiatomic NiTi alloy. Dense samples of NiTi alloy were fabricated using Laser Engineered Net Shaping (LENS™) with two different laser energy densities by varying the scan speed and laser power. These samples were annealed for 30 min at 500 °C and 1000 °C in flowing argon, followed by furnace-cooling to room temperature. The resulting microstructures and properties were compared with the corresponding as-deposited samples. Microstructural analysis after heat treatment showed needle-shape martensite in the samples processed at lower laser energy density of 20 J/mm2, and lenticular or plate-like martensite in the samples processed at 80 J/mm2. The XRD results revealed relatively high concentration of martensite (B19?) in heat-treated NiTi alloy compared to as-processed samples. Furthermore, the heat treatment decreased the forward and reverse transformation temperatures of NiTi alloy from 80 – 95 °C to 20–40 °C, presumably due to annihilation of thermally induced defects. Interestingly, the samples annealed at 500 °C showed a measurable increase of 1–2% in the shape memory recovery, from the net recovery of 8% exhibited by the as-processed NiTi alloy. The corrosion resistance of laser-processed NiTi alloy decreased upon annealing. © 2018 Elsevier B.V.Item Evaluation for the thermokinetics of the autocatalytic reaction of cumene hydroperoxide mixed with phenol through isothermal approaches and simulations(Institution of Chemical Engineers, 2018) Cao, C.-R.; Liu, S.-H.; Das, M.; Shu, C.-M.In the petrochemical industry, estimation methods based on isothermal micro-calorimetry are used to precisely analyze the thermal hazards and risks associated with chemicals and to develop an inherently safer design (ISD). Here, a thermal activity monitor III (TAM III) was used under various isothermal conditions to obtain the thermokinetics parameters of reaction mechanisms. Cumene hydroperoxide (CHP), a typical organic peroxide, is decomposed by the action of sulfuric acid to yield phenol and acetone in equimolar quantities. CHP undergoes multiple complex reactions when an autocatalytic reaction occurs under isothermal decomposition. The following reaction scheme was considered in this study: A + nB ? (n + 1) B, A ? B, B ? C. This type of reaction generally accelerates as the reactant is consumed, and an autocatalytic substance is produced. As a result, an ISD is required for preparation, manufacturing, transportation, storage, and even elimination. The rich behavioral patterns of these autocatalytic reactions were revealed through multiple specific illustrations. © 2018 Institution of Chemical EngineersItem Surface design of Mg-Zn alloy temporary orthopaedic implants: Tailoring wettability and biodegradability using laser surface melting(Elsevier B.V., 2018) Manne, B.; Thiruvayapati, H.; Bontha, S.; Motagondanahalli Rangarasaiah, R.; Das, M.; Balla, V.K.Magnesium-based alloys have attracted significant attention for biomedical applications due to its biodegradability as well as density and elastic modulus which are close to those of human bone. However, the uncontrolled biodegradation and hydrogen evolution are of major concern. In this work, laser surface melting (LSM) has been carried out to tailor initial corrosion rates of Mg-2.2Zn alloy implants. Melt pool dimensions, microstructure and surface topography of the LSM samples were analysed. The wettability and in vitro degradation characteristics of untreated and treated alloy were compared. LSM resulted in much finer cellular microstructural features than as-cast alloy and the melted region depths between 65 and 115 ?m. Higher treatment depths helped to extend the corrosion protection time by suppressing the corrosion front movement. Polished LSM samples resulted in overall corrosion rates of 0.5–0.62 mm/year which was about 40%–50% reduction compared to the as-cast alloy. Accelerated biomineralisation of the surface via enhancements in the surface energy due to microstructural refinement as well as microstructural homogeneity and Zn enrichment in ?-Mg, favoured improvement of the overall corrosion performance of LSM-treated alloy. © 2018 Elsevier B.V.Item Effect of zinc and rare-earth element addition on mechanical, corrosion, and biological properties of magnesium(Cambridge University Press, 2018) Kottuparambil, R.R.; Bontha, S.; Ramesh, M.R.; Arya, S.; Jana, A.; Das, M.; Balla, V.K.; Amrithalingam, S.; Prabhu, T.R.The present work aims to understand the effect of zinc and rare-earth element addition (i.e., 2 wt% Gd, 2 wt% Dy, and 2 wt% of Gd and Nd individually) on the microstructure evolution, mechanical properties, in vitro corrosion behavior, and cytotoxicity of Mg for biomedical application. The microstructure results indicate that the Mg-Zn-Gd alloy consists of the lamellar long period stacking ordered phase. The electrochemical and immersion corrosion behavior were studied in Hanks balanced salt solution. Enhanced corrosion resistance with reduced hydrogen evolution volume and magnesium (Mg2+) ion release were estimated for the Mg-Zn-Gd alloy as compared to the other two alloy systems. At the early stage of corrosion, formation of the oxide film inhibited the corrosion propagation. However, at the later stages, the breaking of the oxide film leads to shallow pitting mode of corrosion. The ultimate tensile strength of Mg-Zn-Gd-Nd is better than the other two alloys due to the uniform distribution of the Mg12Nd precipitate phase. The moderate strength in the Mg-Zn-Gd alloy is due to the low volume fraction of the secondary phase. The MTT (methylthiazoldiphenyl-tetrazolium bromide) assay study was carried out to understand the cell cytotoxicity on the alloy surfaces. Studies revealed that all three alloys had significant cellular adherence and no adverse effect on cells. © 2018 Materials Research Society.Item Laser surface modification of Mg-Zn-Gd alloy: Microstructural, wettability and in vitro degradation aspects(Institute of Physics Publishing helen.craven@iop.org, 2018) Rakesh, K.R.; Bontha, S.; Ramesh, M.R.; Arya, S.; Das, M.; Balla, V.K.; Srinivasan, A.Mg-Zn-Gd have great potential for biomedical applications owing to excellent bioactivity and non-toxicity properties. In the present study, laser surface melting (LSM) was carried out on newly developed Mg-1Zn -2Gd (wt%) alloy. Effects of laser energy on microstructural evolution, corrosion properties, surface energy, and hardness have been investigated. The surface modified sample processed at different energy densities showed fine grain structure in the melt zone compared to the untreated substrate. Grain refinement in the laser melted region improved the hardness by 60%. The surface roughness was found to be increased with increasing laser energy density. At higher energy density, removal of materials from the surface is enhanced, resulting in deeper grooves and higher surface roughness. The wettability studies indicated that the variations in surface geometry, grain size and surface roughness of LSM samples strongly influence the surface energy and hydrophilicity. Improved wetting of LSM sample was achieved owing to grain refinement and low surface roughness. The corrosion resistance determined by immersion and electrochemical methods of laser melted sample in Hank's balanced salt solution improved considerably due to grain refinement, meltpool depth and uniform distribution of secondary phases. © 2018 IOP Publishing Ltd.Item Laser surface melting of Mg-Zn-Dy alloy for better wettability and corrosion resistance for biodegradable implant applications(Elsevier B.V., 2019) K.r, R.; Bontha, S.; M.r, R.; Das, M.; Balla, V.K.In order to improve the performance of magnesium (Mg) for resorbable implant applications, Mg-1Zn-2Dy alloy was developed and the surface of the alloy has been modified by melting using lasers. Laser melted samples, at different laser energy density, were then subjected to microstructural, hardness, wettability and in-vitro degradation assessment. The microstructure of the Mg-Zn-Dy alloy mainly consisted of ?-Mg and eutectic phase (Mg 8 ZnDy). The melted region of the alloy surface evolved with fine grain microstructure at the near surface region and columnar grains near to the liquid solid substrate. The degree of grain size refinement obtained at the melted zone in the order of 1–2 ?m. The cross sectional microhardness of the modified zone was measured by Vickers microhardness tester. Due to these microstructural refinements and solid solution strengthening the surface hardness of laser treated alloy increased by two-fold. It was found that as the energy density increased the surface roughness along with the surface energy also increased. The wetting behaviour of the surface was estimated through measuring the contact angle by dropping the polar and non-polar liquid. Results showed that the surface energy is also found to change with LSM due to changes in the surface morphology, microstructure and chemical composition of the material. The detailed degradation study was carried out by immersing the samples in hanks balances salt solution (HBSS).The improvement in the degradation behaviour followed by laser surface melting is related to the microstructural refinement as a result of rapid heating and cooling of the melted zone. © 2019 Elsevier B.V.Item Degradation, wettability and surface characteristics of laser surface modified Mg–Zn–Gd–Nd alloy(Springer, 2020) K.r, R.; Bontha, S.; M.r, R.; Das, M.; Balla, V.K.This work evaluates the effects of laser surface modification on Mg–Zn–Gd–Nd alloy which is a potential biodegradable material for temporary bone implant applications. The laser surface melted (LSM) samples were investigated for microstructure, wettability, surface hardness and in vitro degradation. The microstructural study was carried out using scanning and transmission electron microscopes (SEM, TEM) and the phases present were analyzed using X-ray diffraction. The in vitro degradation behaviour was assessed in hank’s balanced salt solution (HBSS) by immersion corrosion technique and the effect of LSM process parameters on the wettability was analyzed through contact angle measurements. The microstructural examination showed remarkable grain refinement as well as uniform redistribution of intermetallic phases throughout the matrix after LSM. These microstructural changes increased the hardness of LSM samples with an increase in energy density. The wetting behaviour of processed samples showed hydrophilic nature when processed at lower (12.5 and 17.5 J/mm2) and intermediate energy density (22.5 and 25 J/mm2), which can potentially improve cell-materials interaction. The corrosion rate of as cast Mg–Zn–Gd–Nd alloy decreased by ~83% due to LSM. [Figure not available: see fulltext.]. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.Item Hybrid Bio-Optimized Algorithms for Hyperparameter Tuning in Machine Learning Models: A Software Defect Prediction Case Study(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Das, M.; Mohan, B.R.; Guddeti, R.M.R.; Prasad, N.Addressing real-time optimization problems becomes increasingly challenging as their complexity continues to escalate over time. So bio-optimization algorithms (BoAs) come into the picture to solve such problems due to their global search capability, adaptability, versatility, parallelism, and robustness. This article aims to perform hyperparameter tuning of machine learning (ML) models by integrating them with BoAs. Aiming to maximize the accuracy of the hybrid bio-optimized defect prediction (HBoDP) model, this research paper develops four novel hybrid BoAs named the gravitational force Lévy flight grasshopper optimization algorithm (GFLFGOA), the gravitational force Lévy flight grasshopper optimization algorithm–sparrow search algorithm (GFLFGOA-SSA), the gravitational force grasshopper optimization algorithm–sparrow search algorithm (GFGOA-SSA), and the Lévy flight grasshopper optimization algorithm–sparrow search algorithm (LFGOA-SSA). These aforementioned algorithms are proposed by integrating the good exploration capacity of the SSA with the faster convergence of the LFGOA and GFGOA. The performances of the GFLFGOA, GFLFGOA-SSA, GFGOA-SSA, and LFGOA-SSA are verified by conducting two different experiments. Firstly, the experimentation was conducted on nine benchmark functions (BFs) to assess the mean, standard deviation (SD), and convergence rate. The second experiment focuses on boosting the accuracy of the HBoDP model through the fine-tuning of the hyperparameters in the artificial neural network (ANN) and XGBOOST (XGB) models. To justify the effectiveness and performance of these hybrid novel algorithms, we compared them with four base algorithms, namely the grasshopper optimization algorithm (GOA), the sparrow search algorithm (SSA), the gravitational force grasshopper optimization algorithm (GFGOA), and the Lévy flight grasshopper optimization algorithm (LFGOA). Our findings illuminate the effectiveness of this hybrid approach in enhancing the convergence rate and accuracy. The experimental results show a faster convergence rate for BFs and improvements in software defect prediction accuracy for the NASA defect datasets by comparing them with some baseline methods. © 2024 by the authors.Item HSoMLSDP: A Hybrid Swarm-Optimized Machine Learning Framework for Software Defect Prediction(Institute of Electrical and Electronics Engineers Inc., 2025) Das, M.; Mohan, B.R.; Guddeti, R.M.R.This research aims to design a hybrid swarm-optimized machine learning software defect prediction (HSoMLSDP) framework to predict software defects. We strive to do this by designing a swarm-optimized machine learning defect prediction (SoMLDP) model within the HSoMLSDP framework. In pursuit of enhancing the defect prediction accuracy of the SoMLDP model, this paper designed two novel hybrid swarm-optimization algorithms (SOAs) referred to as gravitational force grasshopper optimization algorithm-artificial bee colony (GFGOA-ABC), and levy flight grasshopper optimization algorithm-artificial bee colony (LFGOA-ABC) algorithms. By combining the enhanced exploration features of LFGOA and GFGOA with the robust exploitation capacity of the artificial bee colony (ABC), the LFGOA-ABC and GFGOA-ABC algorithms are proposed. Prior to validating the HSoMLSDP framework, the LFGOA-ABC and GFGOA-ABC algorithm’s efficacy is first confirmed by experimenting on 19 benchmark functions (BFs) to assess their mean, standard deviation (SD) of optimal values, convergence rate, and convergence rate improvements. Following BFs verification, the second experiment tunes the hyperparameters of the ML models (artificial neural network, XGBOOST) to improve the defect accuracy of the SoMLDP model. The outcomes of the experiments justify a more rapid convergence rate for BFs and notable enhancements of 0.01-0.28 in software defect prediction (SDP) accuracy for NASA defect datasets when compared with state-of-the-art methods. As an enhancement of accuracy justifies the correctness of the SoMLDP model, thus validating the HSoMLSDP framework. © 2013 IEEE.