Good day, Dr. Dhiman Kumar Das. I'm Arjun. I've had a look through your background and your professional record. I'm interested in hearing more about your work and how you see yourself fitting in here with our faculty. Ready to start?

Please start by introducing your professional journey in academia.

Yeah, good morning. How's uh, I'm Doctor Dhiman Kumar Das, uh, starting from the most recent degree, I just completed my PhD philosophy doctorate in mechanical engineering with materials design specialization from NIT Jamshedpur.

Prior to that, I pursued my M tech in advanced material sense and technology from NIT Durgapur.

And before that I perceived my B.Tech in Mechanical Engineering from the same institute in IT Dugapur.

And before that I completed my 12th UH, that is HSC from West Bengal Council for High Secondary education W Bengal, UH, India. And prior to that I completed my 10th in UH.

And from West Bengal Board of Secondary Education.

And uh, talking about my research work, I have research experience in the premium institute like IIT, ISM, Dhanbad, Indian Institute Dhanbad as JRF for two years.

Currently I am working there also in the same institute as SRF Senior Research Fellow after my doctorate degree.

And I also have a teaching as well as corporate experience. After by Btech I joined Hindustan Analytics Limited, the PSU central government company as in design engineer. I served there for near about 8 months. For the reason of higher study I qualified GATE 2011. So I leave it and continued my master degree. And often and I also worked as.

Principal in the state government institute, government ITA college. I also have work experience as a guest faculty in university, the state government university under W Bengal government and I have published uh near about 22 SCI journal papers and the total number of is 28 including our scoop pass as well as international journals also I have published 8.

Chapters few are also in progress or both the journals and book chapters. I have two. I filed 2 patents of which one is granted just on just near about 15 days ago. So in my CV which I uploaded in vit website only the only the filed or published status is showing. But actually one patent got published. I am on the verge of submission of another.

I also have attended new, new new very 17 to 18 total, about of which 8 to 9 national conferences and 8:00 to 9:00 our international conferences and also presented and published papers there. This is in short, my academic background.

Thank you for sharing that, Dr. Das. It sounds like you've had a comprehensive academic and professional journey, with considerable research accomplishments. Let's proceed.

Yeah, in research, I already mentioned in my academic thing that I, uh, already walked as JRF Junior Research fellow in, uh, Indian Institute of Technology in Dhanbad, uh, from 2019 to 21. I also presently I'm working as senior research fellow there after completion of my doctorate degree. That was before completion of my doctorate degree in engineering.

My when I was faculty in some private institutes, I also continued my research after my master degree. Also and what I mentioned already, I have near about 22 SCI journal publications of which most of our Q1 quarantine 1 total total 28 journal publications including other international as well as Coupas index journals. Eight book chapters, few journals as well as book chapters are ongoing in queue.

Uh and uh, also during.

No, already we granted in just a fortnight ago and our I also attended the near about 8 to 9 international conferences and also 8 to 9 national conferences which I already presented there presented there. This is in short my research research profile.

Accepted I already filed 2 patents of which one or one just got.

Thank you for detailing your research profile, Dr. Das. It provides a clear perspective on your extensive experience in research outcomes and contributions. Let’s now delve deeper into some of the specific competencies aligned with the role. First, could you briefly elaborate on how you've applied computational modeling techniques in your current or previous research? Specifically, describe the methodologies or models you've developed or utilized.

Yeah, thank you very much for this question. The computational methodology, I generally work on MD simulation, molecular dynamics simulation and I use the LAMPS large scale atomic molecular massively parallel simulator, the open source software. And the best part of my technique is I generally used to code myself. That means I am a programmer. I am a programmer also in case of materials design.

So uh we predict the mechanical, electrical, thermal uh and physical properties of materials uh of nanomaterials of composites using MD simulation, both NMD non equilibrium molecular dynamics as well as the equilibrium molecular dynamics technique.

EMD and the best part what I say mentioned that uh you know we can, we are generally the coder, we or I specially may code by myself.

And uh, so it's, uh, so it's very influential, influential as it is, it's the prerequisite. It prerequisite necessates the for computer modeling applications.

And rather than this, in my present research, I am where I am working as SRP in IIT ISM Dhanbad. I'm working to develop the modeling as well as experiential composite for medical applications. That is the electrons what are needed in EEG ECG machines for replacing the bones or cartilages in the human bones for petal for patellar removal. We are also planning to work on the tooth.

For this medical applications beside this previously I worked on my hey in my doctorate research I worked or focused on the electrical, mechanical, thermal properties of plumbing, the two-dimensional material of lead resembling graphene, silicene etcetera. They are the they are their cousins. We can and dignify or address or point them as their cousin. Using our MD simulation so I have proficiency. In MD simulation using lamps, uh, I use the NIST interatomic potential potentials and all the other request things. That is the ensembles, our IBC internal conditions, the PBC periodic boundary conditions.

At the next interactive potential is what I said. I actually work on them as well as I have proficiency on the experimental part also.

It's evident that you possess significant expertise in computational modeling, particularly with molecular dynamics simulations, and you've emphasized not just software utilization but also hands-on coding—which is critical for advancing modeling in material science. Exploring both theoretical simulations and medical applications highlights the interdisciplinary impact of your work. As a follow-up, could you explain a specific challenge or limitation you encountered while using molecular dynamics simulations for these materials, especially in the context of medical applications or plumbene research? How did you address it?

Yeah. Thank you. Uh, it is also very good and valid question. The thing is that, uh, the third party already mentioned in my research as well as my academic profile that hardware patent we are just planning to uh, planning to file.

We are working on the, uh, nanocomposite prepared by uh, nanoposite mixture of ultra high molecular, ultra high molecular weight polyethylene with graphene and niobium. Experimentally, we are uh, going to do this and we already have prepared the nanocomposite already tested, uh, lots of data we have. It's about its electrical properties, mechanical properties, thermal properties, etcetera.

But when we are going to model in our modeling, then we found the potential file for graphene for um, HP, the Adivo potential as well as the linear Jordan's potential or tarsapotential etcetera. But the combination of niobium is missing with any of these two materials, which is really a big challenge. Availability of potential file is really a big challenge as well as also the accuracy of the potential files which we are.

Thing are still to be modified. Material scientists are modifying it using the machine learning process continuously. The material database is getting modified, modified and advanced. In future I will also try to develop these potential files by machine learning process or by experiential and to develop this potential file so that these type of limitations that whenever potential file is not available, you cannot. Perform or go through these.

Uh, go through your modeling process, uh, should be minimized as well as also to carry out or to make out other forms. The other relations, uh, we other relations are technological or endometriological equations with more accuracy to predict, estimate or evaluate or investigate the. Engineering as engineering properties or the medical properties or to create the in vivo, in in vivo and in vitro.

Software Switcher specialist specialized for biomedical applications, that is the M bar, moldy jumper, etcetera. For biomedical applications, particularly for medical applications and whatever engineering applications I mentioned earlier, I will try to modify the modify the potential files or to create new potential files which are not available in the market.

Uh, situations which we are developing in lab, uh, in cell, in cell cultures in, uh, through our modeling also, uh, to modify it as well as the other.

Your response showcases not only a deep understanding of the complexities in computational modeling but also a proactive approach towards addressing critical challenges, such as the development of potential files for unique material combinations. This gap in existing material databases and the importance of machine learning to enhance accuracy and versatility of the predictions underline the direction of innovation in this field. Your approach to integrating computational advancements with experimental validation is commendable. Let’s proceed to another key area of relevance to this role. Given your expertise, how do you see AI and machine learning being applied to material science, specifically in the context of predictive modeling or optimization for manufacturing and research?

Yeah. Uh, I think that artificial intelligence or machine learning, uh, specially the NN system, the neural network system, uh, particularly for our materials design and materials application. I will myself try to develop develop it and whatever I mentioned about our potential files, the accuracy say if we can deep, deep into our MD simulation technique.

We can see the.

Bond order. Suppose the molecular weight of carbon. Molecular weight is generally considered as 12.

In an integer figure it is 12, but the actual molecular is weight is 12.01. Now considering these type of accuracy may differ a little bit. For our Avogadro's number, sometimes it is being considered as 6.023, sometimes it is being considered as 6.022. These minute variations might not affect for our mechanical engineering design aspect. That is, for mechanical design engineering design we considered the factor of.

Of 2.8 is directly 4, not 3 but.

Where these are applicable, very good for or to some extent satisfactory forward bulk, forward bulk materials for macroscopic structures. But if we dip minutely into nanotechnology or the minute structure or material structure, then these point variation could affect a lot. So I'll focus on more accuracy, developing new models and new techniques. Uh, to uh, we by utilizing.

AI as well as the predictive modeling. What I am doing that is the ML machine learning process.

To point out the research problems more sophisticatedly, dedicatedly and with accuracy so that the results are more near to the. Physical world because the main or basic difference between physical or experiential thing and the modeling is that the. The considering the aspects.

Like for, uh, such as I am our citing another example for rule of mixture. It is applicable for our composites, but it doesn't consider the voids and interstitial vacancies, etcetera present in the material system. But if I can introduce by our introduce those factors in our modeling technique, it will be a great achievement because. In practically no material can be so perfect.

Institutional vacancies, all these crystal defects or the material defects will be there. But for MD simulation accurately it predicts accurately. Suppose if we set the temperature at 2273 Kelvin for using nose hover thermostat, it will particularly say yes. It will particularly predict the same as 273 Kelvin but achieving 273 or room temperature 30°C. It is very good but physically. Attaining 2 third exactly at 30°C it is near near to impossible. There will be variations and that's why the.

Tolerances are provided, so to minimize these tolerances, I will utilize molecular machine learning processes using the predictive modeling to modify it and continue my research work in future.

Your insights are thorough and highly relevant. You've highlighted critical nuances, such as inaccuracies in molecular weights and constants, and the challenges posed by idealized conditions in simulations compared to real-world imperfections like crystal defects and voids. Your plan to integrate AI and machine learning to enhance the predictive capabilities and reduce discrepancies between modeling and experimental results demonstrates forward-thinking. It also aligns well with trends in the advancement of computational material science. Let us now discuss another essential skill for this role. Given your academic and research background, how would you structure and deliver a course on computational modeling for new graduate students? Specifically, focus on your approach to balancing theory, practical application, and student engagement.

Yeah. Thank you very much.

I actually I am just planning to start for undergraduate degree the basic MD simulation molecular dynamics courses. First I will start, I will start with the very basic, that is the flow chart which is needed, which is essentially needed, which comprise generally of the four parts, 1st preparation of the sample, putting our boundary conditions at the external conditions etcetera.

Next, the equilibration setting up of temperature, pressure, etcetera, that is stabilizes stabilizing the materials. Third, the computation part, that is whatever the desired proper desider properties, mechanical, electrical, thermal, whatever the desired properties we need to evaluate. And last of all from the obtained files or the log files or the data files, we will calibrate our results. The this is the process I will guide the pupils. Both by competition technique, as is the practical application that is through the different softwares, whatever the lamps I mentioned lamps moldy amber, etcetera. What have you mentioned? Another powerful software to develop for chemical modeling is our material studio. And also I also have knowledge and I will also implement the other few softwares lacking or like origin, the graph plotting software Obito, the visual.

Software VMD a little bit. I know, I know, but I am not expertise. I don't have expertise in VMB, but I am quite expert in using Ovito as well as I will try to develop the computational modeling lab there. Our the premium, most premium institute in India is Bangalore already have one supercomputer lab facility. So if it is possible, I'll try to develop there because in supercomputer we can run. Lots of programs through our through our web in different computers and it's very good in our in my present institute, IIT Dhananwad also have that facility also have that facility. I'll try to set up that lab. Beside this the for practical application in nanotechnology. Currently I am also one of one of the in charge of nanometer metric labs at IIT Dhanbad mechanical engineering department. So I'll try to.

Sorry

Set up those labs that sophisticated machines I I can also perform the mechanical properties using UTM, our compression and tensile both uh, also the few basic things that is the dialatometer for thermal expansion testing the conventional Fourier slow method for. Our thermal conductivity testing etcetera and also for preparation of the preparation of manufacturing of our nano composites by very basic things, the by very basic integrants and at room temperature most most important thing is the cost effectiveness of preparation as well as the stock of the shop floor issues and preparation at room. Room temperature, that is employment of unskilled labor. I will. Try to perform all the you know all this and I can set up the laboratory and for theoretical cross work by using a theoretical coursework using or inserting the Monte Carlo simulation to our MD MD simulation. What I already mentioned equilibrium as well as non equilibrium molecular dynamics followed by these following parts boundary condition ensemble, different types of ensemble setting up a potential file linear Jones potential.

The potential grand canonical ensemble like this to steal the output. I will try to insert all these in my course, theoretical as well as the practical about the laboratories, what I already mentioned.

Thank you for that detailed explanation, Dr. Das. Your structured approach to introducing computational modeling through a foundational flowchart of MD simulations demonstrates pedagogical clarity. The balance between theoretical foundations, practical applications, and hands-on lab work, including software use and experimental setups, will provide students with a robust and holistic learning experience. Additionally, your vision for setting up computational and nanomaterial labs with advanced facilities, while keeping cost-effectiveness in mind, underlines your pragmatic outlook. Incorporating tools like Monte Carlo simulations alongside molecular dynamics demonstrates your intent to provide a comprehensive curriculum. Your focus on real-world applications and developing labs would undoubtedly engage and equip students with the skills to tackle complex problems in computational material science. Let us now transition to another aspect of the role—student evaluation and exam duties. Could you describe your approach to assessing students in a course like computational modeling, ensuring fairness while encouraging critical thinking?

Yeah. Uh, thank you very much, uh, for, for student evaluation, uh, I believe on the, uh, whatever the system is going on, that is our theoretical system, uh, also, but I also believe Mac generally on the practical or hands on experience. So in the lab as well as I will also plan the industry visit because I have few contacts with the premium industry what wherever I already. Already worked in Hindustan Limited like that type of thing. My training was in Bangalore and I was posted in Kanpur. So if possible for the aerospace application For the aerospace application of materials.

Uh, with the practical demonstration to the students, uh, generally and uh, the others, we can organize the others few events like the industry academic conclave, uh, already organized in Jamshedpur like that and international conferences, etcetera, where the meeting knowledge sharing everything will be much better. One can understand, uh, very good, as well as to perform the short term courses and workshops where the hands on training experience will be.

To the student and about the exams also, whatever I said particularly with hands on that is whether our modeling or any type of job which is provided to the student, is he or she able to do that practically this I will assign to them about our projects work, our reports etcetera and I will look about. That there is no plagiarism or copy of 1.

That there must be novelty and you you need and unique. Everyone's research or work must be unique. I'll look over that. And by this way, I want to continue, continue in the students evolution and also the exams. Yes, I also prefer the open book test of IIT Mumbai, IIT Kanpur, etcetera, whatever they perform. About these open books open book test and but.

Main the focuses on the concept for our pen and paper exam, they focus on the concept. The running of calculator is not their main motto. Main motto of this premium institute. Whether the concept of the student is clear or not about a particular problem, I'll try to develop own problem and assign it to the students to evaluate their caliber or their potential.

Your philosophy for student evaluation is comprehensive and well-rounded. Placing a strong emphasis on hands-on experience, industrial exposure through site visits, and interactive opportunities such as conclaves and international conferences reflects your commitment to blending academic learning with real-world applicability. Moreover, encouraging innovation and originality ensures that students not only meet academic standards but also contribute novel insights. Your preference for open-book tests and concept-driven evaluations aligns with modern pedagogical practices in premier institutions. It underscores your focus on critical thinking and deep understanding over rote memorization or purely computational skills, which is especially suitable for a field like computational modeling. Let’s now address another important skill for this role. How would you guide students working on independent research projects, ensuring their work is well-structured, methodologically sound, and aligned with academic integrity?

Yeah. Thank you for this very good question. Uh, I will, uh, first I will try to motivate the student about the research.

Uh, there must be nobility and specially, uh, all, all ones are good established career, uh, jobs, uh, which is, which sounds a little bit, uh, of course, but it is a, it is the fact that everyone, uh, every student or every people have a desire to have, uh, to get ols well established in the society with. Good handsome salary like that and to be placed in reputed institutes et cetera so. To for the sake of doing that also, as well As for the shake the primary. Once thinking must be to contribute to the society for the betterment of it, for the betterment of our human civilization and on this planet.

I will try to encourage the students and for their novelty and for guiding, I will. I will, obviously. Guide Guide them about the recent trends. Going on not only the medical field, but also the very high and demanding field like the non conventional energy systems, that is the power which we are generating our our solar structure, the this type of thing, the battery electric vehicle system, etcetera. The I'll try to encourage, encourage them about this and I'll try to and I'll try or I'll share few of my ideas and also. Well, listen from them Pastor would be a good listen. Then listen from them about any new ideas what they have in the in their mind. Because we know the unique ideas always came, always came from some, always came from some things which earlier people don't think they will sound good, such as if we know the story of Benjamin Franklin.

During thunderstorm, he used to fly the kite with.

Uh, hello, Am I audible?

Hello. Wait. But yeah, yeah, OK. Actually the video was stopped. That's why so. Like that thing during the thunderstorm. So at the end time people said that yes, he's a mad person. But later these type of ideas work. So I'll encourage them like that. Can can the nuclear fusion and fission is creating so much of energy for crores and crores of years in the sun. So can something cannot be designed or planned so that we can run any machine. Using water as a fuel, if we see my idea might be a little bit back back dated but The thing is that in our spiritual text we can see in Surya Vijayana that from water this type of energy is coming. We also know that water have a very high heat of hydration that is 11 CS unit which is the highest among all the available or reported materials. So can that much energy? Is not used as fuel, so these type of new ideas.

Yes, you're audible,