2023

[1]       M. Sahu, A. Paul, S. K. Sinha, and S. Ganguly, “A study on residual stress generation versus recrystallisation in FSW joint of dissimilar alloy pair of the AA5083 and HSLA steel,” Sci. Technol. Weld. Join., vol. 28, no. 5, pp. 388–398, 2023, doi: 10.1080/13621718.2023.2165605.

[2]       M. Sahu, A. Paul, and S. Ganguly, “Formation of mechanical property gradient along the sheet thickness due to the patterned Fe/Al IMC layers in the interface in dissimilar FSW of HSLA steel to AA 5083,” Mater. Charact., vol. 203, no. July, p. 113146, 2023, doi: 10.1016/j.matchar.2023.113146.

[3]       A. K. Gupta, S. Chakroborty, S. K. Ghosh, and S. Ganguly, “A machine learning model for multi-class classification of quenched and partitioned steel microstructure type by the k-nearest neighbor algorithm,” Comput. Mater. Sci., vol. 228, no. May, p. 112321, 2023, doi: 10.1016/j.commatsci.2023.112321.

[4]       K. K. Rahangdale and S. Ganguly, “Magneto-dielectric properties of B-site doped (Fe3+, Zr4+) BiMnO3 perovskite ceramic,” Mater. Sci. Eng. B, vol. 289, p. 116225, Mar. 2023, doi: 10.1016/j.mseb.2022.116225.

[5]       N. Acharjee, S. K. Ganguly, B. Sarangi, and A. K. Srivastava, “A review of various ceramic pigment preparation and characterization methodologies for applications,” J. Aust. Ceram. Soc., vol. 59, no. 2, pp. 303–323, Apr. 2023, doi: 10.1007/s41779-023-00853-3.

[6]       G. Chauhan, M. Sahu, P. Prasad, S. Bhattacharya, and S. Ganguly, “Evolution of Residual Stresses in Friction Stir Welded Joints of AA7039,” J. Inst. Eng. Ser. D, vol. 104, no. 1, pp. 213–223, Jun. 2023, doi: 10.1007/s40033-022-00384-4.

2022

[7]       K. K. Rahangdale and S. Ganguly, “Effect of oxygen vacancies on the dielectricity of Ga doped equimolar BiMnO3–BaTiO3 characterized by XPS analysis,” Phys. B Condens. Matter, vol. 626, p. 413570, Feb. 2022, doi: 10.1016/j.physb.2021.413570.

[8]       K. K. Rahangdale and S. Ganguly, “Synthesis of novel nanostructured 0.6BMO-0.4BT perovskite ceramic and its thermal, structural and mechanical characteristics,” Mater. Today Proc., vol. 66, pp. 602–608, 2022, doi: 10.1016/j.matpr.2022.06.478.

[9]       G. Chauhan, M. Sahu, P. Prasad, A. Paul, and S. Ganguly, “Effect of process parameters on friction stir welded joints of AA 7039,” Mater. Today Proc., vol. 66, pp. 566–572, 2022, doi: 10.1016/j.matpr.2022.06.166.

[10]     J. Sarkar and S. Ganguly, “Investigation of the thermal properties of Cu–Ag core-shell nanowires using molecular dynamics simulation,” Phys. B Condens. Matter, vol. 636, p. 413876, Jul. 2022, doi: 10.1016/j.physb.2022.413876.

[11]     M. Sahu, A. Paul, and S. Ganguly, “Influence of frictional heat spread pattern on the formation of intermetallic layers at the dissimilar FSW joint interface between AA 5083 and HSLA steel,” J. Manuf. Process., vol. 83, pp. 555–570, Nov. 2022, doi: 10.1016/j.jmapro.2022.09.019.

[12]     M. Sahu and S. Ganguly, “Distribution of intermetallic compounds in dissimilar joint interface of AA 5083 and HSLA steel welded by FSW technique,” Intermetallics, vol. 151, p. 107734, Dec. 2022, doi: 10.1016/j.intermet.2022.107734.

2021

[13]     K. K. Rahangdale and S. Ganguly, “Structure, dielectricity and ferroelectricity measurement of new perovskite ceramics (1-x)BaTiO3-xBiMnO3 synthesized by solid-state reaction,” Mater. Chem. Phys., vol. 260, no. October 2020, p. 124114, 2021, doi: 10.1016/j.matchemphys.2020.124114.

[14]     M. Sahu, A. Paul, and S. Ganguly, “Process - Property Correlation of Friction Stir Welding of Marine Grade Aluminium Alloy 5083 Using Finite Element Analysis,” Int. J. Marit. Eng., vol. 163, no. A2, Jul. 2021, doi: 10.5750/ijme.v163iA2.757.

[15]     K. K. Rahangdale and S. Ganguly, “Influence of Ga Doping on Multiferroic Behaviour of Modified BiMnO3-BaTiO3 Ceramics,” J. Inst. Eng. Ser. D, vol. 102, no. 2, pp. 389–396, Dec. 2021, doi: 10.1007/s40033-021-00285-y.

[16]     K. K. Rahangdale and S. Ganguly, “Sintering effect on the structure and multiferroic behavior of nanostructured BiMnO 3 ceramic synthesized by mechanochemical route,” Ferroelectrics, vol. 585, no. 1, pp. 97–110, Dec. 2021, doi: 10.1080/00150193.2021.1991224.

[17]     M. Sahu, A. Paul, and S. Ganguly, “Optimization of process parameters of friction stir welded joints of marine grade AA 5083,” Mater. Today Proc., vol. 44, pp. 2957–2962, 2021, doi: 10.1016/j.matpr.2021.01.938.

2020

[18]     D. Y. Pimenov, A. T. Abbas, M. K. Gupta, I. N. Erdakov, M. S. Soliman, and M. M. El Rayes, “Investigations of surface quality and energy consumption associated with costs and material removal rate during face milling of AISI 1045 steel,” Int. J. Adv. Manuf. Technol., vol. 107, no. 7–8, pp. 3511–3525, 2020, doi: 10.1007/s00170-020-05236-7.

[19]     S. Gupta et al., “Modelling the steel microstructure knowledge for in-silico recognition of phases using machine learning,” Mater. Chem. Phys., vol. 252, p. 123286, Sep. 2020, doi: 10.1016/j.matchemphys.2020.123286.

2019

[20]     S. Gupta, J. Sarkar, A. Banerjee, N. R. Bandyopadhyay, and S. Ganguly, “Grain Boundary Detection and Phase Segmentation of SEM Ferrite–Pearlite Microstructure Using SLIC and Skeletonization,” J. Inst. Eng. Ser. D, vol. 100, no. 2, pp. 203–210, Oct. 2019, doi: 10.1007/s40033-019-00194-1.

[21]     A. Paul, S. Kumar Sinha, P. P. Chattopadhyay, and S. Ganguly, “Anomalous enhancement of strength-ductility combination in FSW joints of AA7039,” Manuf. Lett., vol. 22, pp. 1–5, Oct. 2019, doi: 10.1016/j.mfglet.2019.09.002.

[22]     A. Das, S. Sinha, and S. Ganguly, “Development of a blast-induced vibration prediction model using an artificial neural network,” J. South. African Inst. Min. Metall., vol. 119, no. 2, 2019, doi: 10.17159/2411-9717/2019/v119n2a11.

2017

[23]     M. K. Tripathi, P. P. Chattopadhyay, and S. Ganguly, “Evolutionary intelligence in design and synthesis of bulk metallic glasses by mechanical alloying,” Mater. Manuf. Process., vol. 32, no. 10, pp. 1059–1066, Jul. 2017, doi: 10.1080/10426914.2017.1279305.

[24]     M. K. Tripathi, P. P. Chattopadhyay, and S. Ganguly, “A predictable glass forming ability expression by statistical learning and evolutionary intelligence,” Intermetallics, vol. 90, pp. 9–15, Nov. 2017, doi: 10.1016/j.intermet.2017.06.008.

2016

[25]     M. K. Tripathi, S. Ganguly, P. Dey, and P. P. Chattopadhyay, “Evolution of glass forming ability indicator by genetic programming,” Comput. Mater. Sci., vol. 118, pp. 56–65, Jun. 2016, doi: 10.1016/j.commatsci.2016.02.037.

[26]     S. Ganguly, A. Patra, P. P. Chattopadhyay, and S. Datta, “New training strategies for neural networks with application to quaternary Al–Mg–Sc–Cr alloy design problems,” Appl. Soft Comput., vol. 46, pp. 260–266, Sep. 2016, doi: 10.1016/j.asoc.2016.05.017.

2015

[27]     M. K. Tripathi, P. P. Chattopadhyay, and S. Ganguly, “Multivariate analysis and classification of bulk metallic glasses using principal component analysis,” Comput. Mater. Sci., vol. 107, pp. 79–87, Sep. 2015, doi: 10.1016/j.commatsci.2015.05.010.

[28]     A. Patra, S. Ganguly, P. P. Chattopadhyay, and S. Datta, “Computational design and development of novel Al-Mg-Sc-Cr alloy,” Multidiscip. Model. Mater. Struct., vol. 11, no. 3, pp. 401–412, Oct. 2015, doi: 10.1108/MMMS-12-2014-0061.

2013

[29]     S. Ganguly, C. S. Kong, S. R. Broderick, and K. Rajan, “Informatics-Based Uncertainty Quantification in the Design of Inorganic Scintillators,” Mater. Manuf. Process., vol. 28, no. 7, pp. 726–732, Jul. 2013, doi: 10.1080/10426914.2012.736660.

2012

[30]     S. Ganguly, O. A. Ojo, P. P. Chattopadhyay, and D. Roy, “Nano-Intermetallic Precipitated Al-Based Amorphous Matrix Composite Design by Artificial Neural Network Analysis,” J. Mater. Sci. Res., vol. 1, no. 3, Jun. 2012, doi: 10.5539/jmsr.v1n3p59.

[31]     A. K. Nandi, K. Deb, S. Ganguly, and S. Datta, “Investigating the role of metallic fillers in particulate reinforced flexible mould material composites using evolutionary algorithms,” Appl. Soft Comput., vol. 12, no. 1, pp. 28–39, Jan. 2012, doi: 10.1016/j.asoc.2011.08.059.

2010

[32]     A. Patra, S. Ganguly, M. S. Kaiser, P. P. Chattopadhyay, and S. Datta, “Effect of quaternary zirconium addition on mechanical properties of Al-6Mg-Sc (0.2-0.6%) alloy studied by ANN technique,” Int. J. Mechatronics Manuf. Syst., vol. 3, no. 1/2, p. 144, 2010, doi: 10.1504/IJMMS.2010.029886.

2009

[33]     P. Das, S. Mukherjee, S. Ganguly, B. K. Bhattacharyay, and S. Datta, “Genetic algorithm based optimization for multi-physical properties of HSLA steel through hybridization of neural network and desirability function,” Comput. Mater. Sci., vol. 45, no. 1, pp. 104–110, Mar. 2009, doi: 10.1016/j.commatsci.2008.03.050.

[34]     M. Ray, S. Ganguly, M. Das, S. M. Hossain, and N. R. Bandyopadhyay, “Genetic algorithm based search of parameters for fabrication of uniform porous silicon nanostructure,” Comput. Mater. Sci., vol. 45, no. 1, pp. 60–64, Mar. 2009, doi: 10.1016/j.commatsci.2008.03.052.

[35]     S. Ganguly, S. Datta, and N. Chakraborti, “Genetic algorithm-based search on the role of variables in the work hardening process of multiphase steels,” Comput. Mater. Sci., vol. 45, no. 1, pp. 158–166, Mar. 2009, doi: 10.1016/j.commatsci.2008.01.074.

[36]     S. K. Ghosh, S. Ganguly, P. P. Chattopadhyay, and S. Datta, “Effect of copper and microalloying (Ti, B) addition on tensile properties of HSLA steels predicted by ANN technique,” Ironmak. Steelmak., vol. 36, no. 2, pp. 125–132, Feb. 2009, doi: 10.1179/174328107X254880.

[37]     M. Kundu, S. Ganguly, S. Datta, and P. P. Chattopadhyay, “Simulating Time Temperature Transformation Diagram of Steel Using Artificial Neural Network,” Mater. Manuf. Process., vol. 24, no. 2, pp. 169–173, Jan. 2009, doi: 10.1080/10426910802612239.

2008

[38]     K. P. Das, S. Ganguly, P. P. Chattopadhyay, S. Tarafder, and N. R. Bandyopadhyay, “Exploring the Possibilities of Development of Directly Quenched TRIP-Aided Steel by the Artificial Neural Networks (ANN) Technique,” Mater. Manuf. Process., vol. 24, no. 1, pp. 68–77, Dec. 2008, doi: 10.1080/10426910802543723.

[39]     M. Ray, S. Ganguly, M. Das, S. Datta, N. R. Bandyopadhyay, and S. M. Hossain, “Artificial Neural Network (ANN)-Based Model for In Situ Prediction of Porosity of Nanostructured Porous Silicon,” Mater. Manuf. Process., vol. 24, no. 1, pp. 83–87, Dec. 2008, doi: 10.1080/10426910802543848.

[40]     S. Ganguly, S. Datta, P. P. Chattopadhyay, and N. Chakraborti, “Designing the Multiphase Microstructure of Steel for Optimal TRIP Effect: A Multiobjective Genetic Algorithm Based Approach,” Mater. Manuf. Process., vol. 24, no. 1, pp. 31–37, Dec. 2008, doi: 10.1080/10426910802540398.

[41]     S. K. Ghosh, A. Haldar, S. Ganguly, and P. P. Chattopadhyay, “Development of High-Strength Cu-Ni-Ti-B Multiphase Steel by Direct Air Cooling,” Metall. Mater. Trans. A, vol. 39, no. 11, pp. 2555–2568, Nov. 2008, doi: 10.1007/s11661-008-9610-6.

[42]     S. K. Ghosh, P. P. Chattopadhyay, A. Haldar, S. Ganguly, and S. Datta, “Design of the Directly Air-cooled Pearlite-free Multiphase Steel from CCT Diagrams Developed Using ANN and Dilatometric Methods,” ISIJ Int., vol. 48, no. 5, pp. 649–657, 2008, doi: 10.2355/isijinternational.48.649.

[43]     S. Datta, F. Pettersson, S. Ganguly, H. Saxén, and N. Chakraborti, “Identification of Factors Governing Mechanical Properties of TRIP-Aided Steel Using Genetic Algorithms and Neural Networks,” Mater. Manuf. Process., vol. 23, no. 2, pp. 130–137, Jan. 2008, doi: 10.1080/10426910701774528.

[44]     S. K. GHOSH, S. GANGULY, P. P. CHATTOPADHYAY, and S. DATTA, “DETERMINATION OF MS TEMPERATURE IN COPPER-BEARING MICROALLOYED STEEL BY THE ANN TECHNIQUE,” Can. Metall. Q., vol. 47, no. 1, pp. 91–98, Jan. 2008, doi: 10.1179/cmq.2008.47.1.91.

2007

[45]     S. Ganguly, S. Datta, and N. Chakraborti, “Genetic Algorithms in Optimization of Strength and Ductility of Low-Carbon Steels,” Mater. Manuf. Process., vol. 22, no. 5, pp. 650–658, Jun. 2007, doi: 10.1080/10426910701323607.

[46]     S. Datta, F. Pettersson, S. Ganguly, H. Saxén, and N. Chakraborti, “Designing High Strength Multi-phase Steel for Improved Strength–Ductility Balance Using Neural Networks and Multi-objective Genetic Algorithms,” ISIJ Int., vol. 47, no. 8, pp. 1195–1203, 2007, doi: 10.2355/isijinternational.47.1195.

2005

[47]     S. K. GHOSH, S. GANGULY, P. P. CHATTOPADHYAY, and S. DATTA, “Modeling the Effect of Copper on Hardness of Microalloyed Dual Phase Steel through Neural Network and Neuro-fuzzy Systems,” ISIJ Int., vol. 45, no. 9, pp. 1345–1351, 2005, doi: 10.2355/isijinternational.45.1345.

Book Chapter

[48]     S. K. Sinha, S. Poddar, and S. Ganguly, “Hierarchical Oxide Nanostructures-Based Gas Sensor: Recent Advances,” in Materials Horizons: From Nature to Nanomaterials, 2020, pp. 161–188. doi: 10.1007/978-981-15-4810-9_7.

[49]     K. K. Rahangdale and S. Ganguly, “Microstructural properties of lead free BiMnO 3 ceramic prepared by mechanochemical synthesis,” IOP Conf. Ser. Mater. Sci. Eng., vol. 577, no. 1, p. 012162, Nov. 2019, doi: 10.1088/1757-899X/577/1/012162.

[50]     S. Dey, S. Ganguly, and S. Datta, “In silico Design of High Strength Aluminium Alloy Using Multi-objective GA,” 2015, pp. 316–327. doi: 10.1007/978-3-319-20294-5_28.

Reserch profiles IDs

Web of Science ResearcherID     : L-5397-2016

Orcid Id        : 0000-0003-0878-7904

Google Scholar Id : IsxECvwAAAAJ

Scopus Id        : 8512484600

Awards and Achievement

1. Young Engineers Award 2008 MME Division, Institution of Engineers India.

2. Best paper 2010, MME Division, Institution of Engineeris India

3. Visiting Scientist, Department of Materials Science and Engineering, Iowa  State University Iowa, USA. 2010

4 Visiting post doctoral fellow, University of Manitoba, Manitoba canada. 2009

Sponsored R&D Projects

1. Development of High Throughput Digital Metallography Tool for Analysis Steel MicrostructureUsing Artificial Intelligence (AI). (SERB-CRG, DST- CRG/2021/005256)

2. Development of Low-ppm Ammonia sensors using NiO/CeO2 heterostructured nanofibers, Co-PI, (DST SERB Grant No CRG/2019/003480)

3. Study of metallurgical characteristic of nugget zone in dissimilar alloy joints of AA 5083 andHSLA steel by FSW, PI (IEI, Ref. Project I.D ID: DR2019008)

4. Image processing of SEM microstructures of steel, PI, (NIT Raipur Seed Grant No.NITRR/Seed Grant/2016-17/017).

5. Study of Aging Behavior of Copper-added Austenitic Grade Stainless Steel and Modeling the AgingCharacteristics. PI (IEI, Ref. Project I.D UG2014039).

PhD Awarded

2023: A Study on Dissimilar Friction Stir Welding of AA5083 to HSLA Steel and Evaluation of Joint Interface, Dr. Mrinal Sahu, NIT Raipur