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  1. Soomro IA, Pedapati SR, Awang M
    Materials (Basel), 2021 Feb 08;14(4).
    PMID: 33567606 DOI: 10.3390/ma14040802
    Resistance spot welding (RSW) of dual phase (DP) steels is a challenging task due to formation of brittle martensitic structure in the fusion zone (FZ), resulting in a low energy capacity of the joint during high-rate loading. In the present study, in situ postweld heat treatment (PWHT) was carried out by employing a double pulse welding scheme with the aim of improving the mechanical performance of DP590 steel resistance spot weld joint. Taguchi method was used to optimize in situ PWHT parameters to obtain maximum peak load and failure energy. Experiments were designed based on orthogonal array (OA) L16. Mechanical performance was evaluated in terms of peak load and failure energy after performing low dynamic tensile shear (TS) test. Microstructural characterization was carried out using a scanning electron microscope (SEM). The results show that improvements of 17 and 86% in peak load and failure energy, respectively, were achieved in double-pulse welding (DPW) at optimum conditions compared to traditional single-pulse welding (SPW). The improvement in mechanical performance resulted from (i) enlargement of the FZ and (ii) improved weld toughness due to tempering of martensite in the FZ and subcritical heat affected zone (SCHAZ). These factors are influenced by heat input, which in turn depends upon in situ PWHT parameters.
  2. Hassan A, Pedapati SR, Awang M, Soomro IA
    Materials (Basel), 2023 Mar 29;16(7).
    PMID: 37049016 DOI: 10.3390/ma16072723
    Additive manufacturing is a key component of the fourth industrial revolution (IR4.0) that has received increased attention over the last three decades. Metal additive manufacturing is broadly classified into two types: melting-based additive manufacturing and solid-state additive manufacturing. Friction stir additive manufacturing (FSAM) is a subset of solid-state additive manufacturing that produces big area multi-layered components through plate addition fashion using the friction stir welding (FSW) concept. Because of the solid-state process in nature, the part produced has equiaxed grain structure, which leads to better mechanical properties with less residual stresses and solidification defects when compared to existing melting-based additive manufacturing processes. The current review article intends to highlight the working principle and previous research conducted by various research groups using FSAM as an emerging material synthesizing technique. The summary of affecting process parameters and defects claimed for different research materials is discussed in detail based on open access experimental data. Mechanical properties such as microhardness and tensile strength, as well as microstructural properties such as grain refinement and morphology, are summarized in comparison to the base material. Furthermore, the viability and potential application of FSAM, as well as its current academic research status with technology readiness level and future recommendations are discussed meticulously.
  3. Hussain I, Amara U, Bibi F, Hanan A, Lakhan MN, Soomro IA, et al.
    Adv Colloid Interface Sci, 2024 Jan 04;324:103077.
    PMID: 38219341 DOI: 10.1016/j.cis.2023.103077
    Ti-MXene allows a range of possibilities to tune their compositional stoichiometry due to their electronic and electrochemical properties. Other than conventionally explored Ti-MXene, there have been ample opportunities for the non-Ti-based MXenes, especially the emerging Mo-based MXenes. Mo-MXenes are established to be remarkable with optoelectronic and electrochemical properties, tuned energy, catalysis, and sensing applications. In this timely review, we systematically discuss the various organized synthesis procedures, associated experimental tunning parameters, physiochemical properties, structural evaluation, stability challenges, key findings, and a wide range of applications of emerging Mo-MXene over Ti-MXenes. We also critically examined the precise control of Mo-MXenes to cater to advanced applications by comprehensively evaluating the summary of recent studies using artificial intelligence and machine learning tools. The critical future perspectives, significant challenges, and possible outlooks for successfully developing and using Mo-MXenes for various practical applications are highlighted.
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