Pravat Ranjan Pati

Dr. Pravat Ranjan Pati


Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 July 2024 in Interactions
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Journal Article
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GBG. Hima Bindu
G. Hima Bindu
MGM. Ganesh
M. Ganesh
SKSathees Kumar
Sathees Kumar
PPPravat Ranjan Pati
Pravat Ranjan Pati
JGJayant Giri
Jayant Giri
Emad MakkiEmad Makki
Emad Makki

15 May 2024 in Journal of Materials Research and Technology
Verified
Journal Article
Open access
SKS. Sathees Kumar
S. Sathees Kumar
PSP. Shyamala
P. Shyamala
PPPravat Ranjan Pati
Pravat Ranjan Pati
JGJayant Giri
Jayant Giri
Emad MakkiEmad Makki
Emad Makki
TST. Sathish
T. Sathish

9 October 2024 in Journal of Materials Research and Technology
Verified
Journal Article
Open access
RMR. Muthalagu
R. Muthalagu
SKS. Sathees Kumar
S. Sathees Kumar
PPPravat Ranjan Pati
Pravat Ranjan Pati
JGJayant Giri
Jayant Giri
TST. Sathish
T. Sathish
AFAmanullah Fatehmulla
Amanullah Fatehmulla

29 September 2025 in Scientific Reports
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Journal Article
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SKSathees Kumar
Sathees Kumar
PSP. Shyamala
P. Shyamala
PPPravat Ranjan Pati
Pravat Ranjan Pati
DMDipesh Kumar Mishra
Dipesh Kumar Mishra
VSVishal Sharma
Vishal Sharma
MKMohammad Kanan
Mohammad Kanan
With the growing emphasis on sustainability and circular economy principles in industrial sectors, the effective utilization of waste-derived and abundantly available natural resources has become imperative. Renewable lignocellulosic fibers such as jute fiber (JF), banana fiber (BaF), coconut coir (CC), and pineapple leaf fiber (PALF) serve as viable reinforcements for developing eco-friendly polymer composites. In this study, hybrid natural fiber (NF) composites were fabricated using the hand lay-up method with varying weight percentages of alkaline-treated JF, CC, BaF, and PALF. Alkaline treatment improved fiber–matrix interfacial bonding by reducing hydroxyl groups and enhancing surface roughness, which significantly contributed to improved mechanical and thermal performance. Mechanical testing revealed that the composite containing 20% JF, 20% CC, and 10% PALF exhibited superior properties, achieving a tensile strength of 85.8 MPa, flexural strength of 134.5 MPa, impact strength of 23.3 J/m2, and hardness of 72.6 Shore D. Fourier transform infrared spectroscopy (FTIR) confirmed successful alkaline treatment through reduced hydroxyl group intensity and improved fiber–matrix compatibility. Atomic force microscopy (AFM) further revealed increased surface roughness (Ra = 31.43 nm), indicating enhanced interfacial adhesion. To predict mechanical performance, machine learning (ML) regression models including linear regression, multilinear regression, decision tree, and random forest were developed using experimental data. Among these, the random forest model demonstrated the highest predictive capability, achieving R2 values of 0.968 for tensile strength, 0.939 for flexural strength, 0.941 for impact strength, and 0.962 for hardness, along with the lowest error metrics (mean absolute error and root mean squared error). These results highlight its suitability for accurate prediction of mechanical properties in fiber-reinforced composites. Furthermore, dynamic mechanical analysis (DMA) revealed enhanced viscoelastic behaviour in treated fiber composites, while thermogravimetric analysis (TGA) confirmed excellent thermal stability up to 690 °C in JF/CC/PALF-reinforced samples.

4 July 2024 in Interactions
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Journal Article
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APAbhilash Purohit
Abhilash Purohit
PSPartha Sarathi Sahoo
Partha Sarathi Sahoo
PCPankaj Kumar Chauhan
Pankaj Kumar Chauhan
PPPravat Ranjan Pati
Pravat Ranjan Pati
JGJayant Giri
Jayant Giri
TST Sathish
T Sathish

16 August 2024 in Polymer Composites
Verified
Journal Article
Closed access
SDSoumya Dash
Soumya Dash
MSMantra Prasad Satpathy
Mantra Prasad Satpathy
BRBharat Chandra Routara
Bharat Chandra Routara
PPPravat Ranjan Pati
Pravat Ranjan Pati
SGSubhra Gantayat
Subhra Gantayat