Authors: Ramya Sharma | Sathiyaraj Chinnasamy | M Ramachandran | Poonkodi Sathiyamoorthy | T Mahlia | B Taufiq | H Masjuki | W Beele | G Marijnissen | A Van Lieshout | K Reddy | Vijay Mudgal | T Mallick | D Fernandes | F Piti | G Cceres | J Baeyens | Robert Vassen | Xueqiang Cao | Frank Tietz | Debabrata Basu | Detlev Stver | Ioannis Axaopoulos | Petros Axaopoulos | John Gelegenis | Watson Vargas | Joseph Mccarthy | Sachin Karad | Balpreet Chandravadan | Singh | C Krishna | Kanchan Ambhika | Shailendra Yadav | Sikarwar Singh | S Ballamudi | B Amrutha | I Meghana | R Tejas | Hrishikesh Vasant Pilare | D Annapurna | C Murugamani | S Shitharth | S Hemalatha | Pravin Kshirsagar | K Riyazuddin | Saiful Quadri Noorulhasan Naveed | Islam | Syed Parween Mazher | Areda Ali | Batu | Xin Wang | Yinping Zhang | Wei Xiao | Ruolang Zeng | Qunli Zhang | Hongfa Di | G Kalinin | V Barabash | A Cardella | J Dietz | K Ioki | R Matera | R Santoro | R Tivey | Anuj Singh | Ranjith Pratap | Rajat Kumar Anandan | Harsh Rana | P Prakash Dwivedi | Akshat Avinash | Sakharkar Narendra | M Vamsikrishna | Amit Srinivasa Rao Bogireddy | Nilamadhab Gangopadhyay | Ajith Mishra | Priya Sundaram | Sharma | G Suresh | G Manikandan | G Bhuvaneswari | P Shanthakumar | V Ragavan | N Nithya | Anantharamaiah Vengala | Balambigai Subramanian | C Ambhika | Souptik Sen | Ramesh Krishnamaneni | Ashwin Narasimha | Murthy | S Karad | A Chaitanya | O Sujayasree | Saikat Maity | Prasenjit Ranjan | Shankar Chatterjee | Chakraborty | Hassan Nazir | Mariah Batool
Source: Journal on Applied and Chemical Physics (article, 2025-09-02)
Field: Materials Science — Materials Chemistry

Material Selection for Statistically Loaded Thermal Conductors A Comprehensive Study A appropriate material for a proportionally loaded thermal conductor is one that can effectively transport heat while overcoming the mechanical stresses that accompany the application. Under the projected operating conditions, the material should have excellent heat conductivity, excellent mechanical strength, and dependability. In a nutshell, the selection procedure seeks a material that's able to efficiently transmit heat while retaining structural integrity when used in a statistical loaded thermal conductivity application. To endure operational demands, the material should be chosen keeping both thermal insulation and mechanical qualities in mind. Several variables must be considered while selecting a material: thermal conductivity, mechanical strength, thermal expansion coefficient, stability and reliability, cost and availability. A thorough assessment of numerous candidate materials including their attributes is required to find the best appropriate material. This evaluation may include laboratory testing, analysis of information, as well as simulations to determine how various materials would function under the application's unique loading and heat circumstances. Overall, choosing an appropriate material for a statistically loaded thermal conductor requires considering thermal conductivity, mechanical strength, stability, and cost concerns in order to match the application's specific criteria and assure optimal performance and reliability. The practical ramifications and possible breakthroughs in numerous domains make selecting a material appropriate for a randomly loaded thermal conductor a research priority. Here are some major elements showing the importance of the research Material selection research in statistically packed thermal conductors seeks to improve the general efficacy of thermal management platforms. Researchers can improve heat transfer effectiveness and dependability by discovering materials with increased thermal conductivity with mechanical strength, resulting in better system performance as a lower risk of failure. Material selection research promotes the investigation and development of novel substances that are specifically adapted for randomly loaded thermal conductors. The selection of an appropriate material for a statistically laden thermal conductor helps to developments like thermal management technologies, system performance, energy efficiency, and general dependability by addressing these research topics. It provides practical answers and prospective breakthroughs that can assist a wide range of sectors and pave the way for future revolutionary thermal management systems. The WASPAS methodology is often used to identify the optimal material to use as a statistically weighted thermal conductor. Taken as “Alternative parameter is Copper-2-beryllium (cast), Copper–cobalt–beryllium (cast), Electrolytic tough-pitch, h.c. copper, soft (wrought), Electrolytic tough-pitch, h.c. copper, hard (wrought), Wrought aluminum alloy, wrought austenitic stainless steel, Commercial bronze, CuZn10, soft (wrought), Carbon steel (annealed). Taken as Evaluation parameter is CS, UT, SL, SB, BF, D. From the result it is seen that Electrolytic tough-pitch, h.c. copper, soft (wrought) got highest rank whereas Wrought aluminum alloy got lowest rank’. According to the results, Electrolytic tough-pitch, h.c. copper, soft (wrought) was ranked first. Selection (genetic algorithm) ; Electrical conductor ; Thermal ; Materials science ; Environmental science ; Computer science ; Composite material ; Thermodynamics ; Physics ; Artificial intelligence Thermal properties of materials ; Thermodynamic and Structural Properties of Metals and Alloys ; Phase Change Materials Research