preloader

Responsive Soft Matter

Abdominal Aortic Aneurysm (AAA), machine learning, quantify uncertainty, patient-specificLab-on-a-Chip, stimuli-responsive polymers, actuators, sensors,Thermodynamical Framework, Abdominal Aortic Aneurysm (AAA), Endovascular Aneurysm Repair (EVAR),Smooth Finite Element Method (SFEM), Growth and Remodelling (G&R), Deep Learning.

IRIS Webinar

According to epidemiological studies conducted on the fatal ruptured aneurysms (of all types) during 1999-2016 in the United States, an overwhelming 65% of the deaths occurred due to the rupture of AAA. Further, the mortality risk of a ruptured AAA is at least 80%. Assuming incidence rates of 5% and 1% among Indian men and women, respectively, an estimated 1.5 million men and 0.3 million women may be subject to this condition. Currently, surgical intervention of AAA is recommended (or risk of rupture) if the diameter is greater than 55mm, if it grows at the rate of 10mm/year or if it is symptomatic.

  • This diameter-based criteria has an accuracy of about 1 in 10 patients, implying that there is a tremendous scope for a much-improved prediction for life-saving timely intervention.

  • The challenges with regard to AAA may be presented in two parts, one: to accurately predict patient-specific growth and rupture of AAA by considering various risk factors such as age, gender, tobacco use, family history, and comorbidities such as hypertension, hypercholesterolemia, and coronary artery disease.

  • Second, to provide guidance on choice between EVAR and open surgery, based on growth and remodeling of the arterial vessel post EVAR ( i.e., provide guidance on long-term success or failure of EVAR). Further the need for re-intervention maybe assessed periodically based on surveillance data and model predictions.

Responsive Soft Matter

Krishna Kannan

Principal Investigator

People

Parag Ravindran

Area of Interest

Parag Ravindran

Co-Principal investigator

Mechanical Engineering

paragr@iitm.ac.in
Ratna Kumar Annabattula

Area of Interest

Sundararajan Natarajan

Area of Interest

Sundararajan Natarajan

Co-Principal investigator

Mechanical Engineering

snatarajan@iitm.ac.in

Project

A normal and a ruptured aneurysm

Functional Smart Polymers

The present-day Lab-on-Chip (LoC) devices suffer for want of cheap, simple, and easily integrable onboard fluid flow control and sensing devices, significantly limiting their applications. An advantage of LoC devices is their portability which makes them highly suited for medical diagnostics in remote locations where setting-up of full-scale diagnostic laboratories may not be possible. The development of integrable and portable LoC devices relies on the availability of appropriate technologies for flow control and sensing. This center aims to develop different stimuli-actuated integrable microfluidic flow control components, on-chip sensors. In addition, the center also focuses on biomedical applications of soft-robotic actuators. The prime investigation focuses on using various polymers responsive to stimuli such as light, solvent, and vapor to develop actuators and sensors. The center is envisioned to follow an approach of using synergic combination of computational models and experiments.

Lab-on-a-chip with dependence on external systems making it Chip-in-a-Lab

Fully integrated Lab-on-a-Chip with on-chip pumps, valves and sensors

We approximate AAA as an elastic material. A major challenge in hyperelasticity is to derive the structure of an elastic potential with as few material parameters as possible. Hence, we first focus on an analysis-based construction of a potential function based on Lode invariants of Hencky strain for collagenous soft tissues, e.g., human aorta. To this end, we shall employ the constitutive inequalities (Baker-Ericksen and Hill inequalities) proposed in the literature to systematically derive the elastic potential; a stretch limit function also arises naturally within the process.

The ability of biological soft tissues to ’adapt’ to changes in their chemo-mechanical environment is an important component in normal physiological conditions, responses to injury, disease progression, etc. To that end, we shall endeavour to model the adaptation of the aortic wall by means of a constrained rule-of-mixtures approach. Unlike in the normal aortic tissue, there is a first-order kinetics degradation of elastin in aneurysmal tissues. Likewise, decreased wall shear stresses signals the endothelial cells to synthesise nitric oxide (NO), a promoter of collagen synthesis. Driven by such biochemomechanical evidence published in the literature, specific functional forms for mass rates and associated values of material parameters will be identified. The elasticity model, along with a generic G&R (Growth and Remodeling) model would enable us to computationally study the evolution of the tissue over time.

From the literature, it is evident that the mechanical response varies significantly amongst patients (see Figure 2). This motivates the requirement of appropriate stochastic techniques to consider the various sources of variation, e.g., mechanical properties, geometric & clinical attributes, etc.

Bayes' theorem is used for calibration of the model parameters. As the dimension of the parameter space increases, we rely on numerical techniques, e.g., Markov chain Monte Carlo sampling, nested sampling, etc. Preliminary work on this has given insights on the distribution of mechanical and geometric attributes based on a reasonably large sample size.

Ex-vivo equibiaxial stretch- stress response for different patients (data from Duprey et. al.,2016)

A brief schematic of Bayesian inference in the present context

There is no Indian-patient-specific biaxial data on AAA available in the literature. To improve the accuracy of prediction of growth & rupture, biaxial experiments on aneurysmal tissue are proposed as given below. After aneurysmal tissue is harvested from a repair surgery, a part will be stored in a crysostat for later use and another part for conducting histology studies. The sample will be mounted on the biaxial testing machine and submerged in a saline bath at around 37° C. To exploit the advantages of the Lode invariants, the biaxial tests will be conducted such that one of the invariants is held constant, while the other is varied. This requires the X- and Y-axes arms of the biaxial tester be simultaneously translated in a predefined manner. A suitable number of preconditioning cycles will be performed for each protocol and the force data will be collected from the final cycle. Subsequently, the sample will be subject to histological studies, enabling us to compare the collagen microstructure before and after loading.

A large percentage of patients undergoing EVAR need re-intervention. Many of these are due to endoleaks. Endoleaks are classified into 5 types (Figure A.3) depending on the location/cause of leak. It is proposed to study the problem of post EVAR anuerysmal changes within the framework of G&R. The aneurysm rupture appears to be correlated to the size of the intraluminal thrombus (ILT). ILT growth itself is related to the fluid flow characteristics. A model incorporating ILT, but without the full complexity of fluid flow is proposed to be built. The chemo-mechanical influence of ILT on the arterial wall will be studied.

Classification of endoleaks

An efficient and modular computational framework will be developed based on a fast and accurate numerical solution using Smoothed Finite Element Method (SFEM). In this work, we propose to discretize the domain with 4-noded tetrahedral elements. Further, adaptive analyses can be easily built in within the framework since tetrahedral elements can be automatically generated and refined even for complicated domains. However, the T4 element possesses significant shortcomings, for example: they are well known for overly stiff behaviour and volumetric locking in the nearly incompressible cases. These disadvantages can be overcome by employing the smoothed finite element method (SFEM), introduced by Liu et al. and further extended by Natarajan and his co-workers, to arbitrary polytopes, which shows improved accuracy with reduced computational cost. The essential terms in the tangent stiffness matrix and the residual force vector will be computed within the framework of the SFEM. To improve the computational efficiency and accuracy, in this project, we propose to utilize the user subroutine interface; scripting-based CAE/GUI customization and C++ odb API available in the ABAQUS package to implement the SFEM. The user element UEL will implement the SFEM along with the new invariants developed.

The standard FEM or the smoothed FEM discussed above, requires that the background discretization conforms to the geometry. This poses a problem, if the geometry is continuously changing. One approach to handle this is to remesh every time there is a change in the geometry and update the variables by using suitable Galerkin projections. However, given the large deformation and the material being hyperelastic, the above approach is computationally demanding. To alleviate this, in this project, we will employ the smoothed extended FEM. The salient feature of this is that the geometry is represented implicitly and is independent of the underlying background mesh. The local physics of the problem is captured by augmenting the conventional basis functions with suitable ansatz. This framework, again, will be implemented in the FE software, ABAQUS.

Finally, the physical G&R models will aid in generating in silico data, which will be integrated with the cohort Indian patient data. A Deep Belief Network trained on the database will be constructed for the prediction of individual AAA growth and risk assessment. As more patient data becomes available over time, additional physics-based simulations are necessary to ’fill in’ the missing pieces of information: growth between two CT scans. Consequently, the database continues to grow (dynamic) thereby necessitating deep learning methods to predict AAA growth and eventual rupture.

Working with select hospitals, patients in each of the 7 categories (patients with only one of the risk factors (3 categories), with two at a time (3 categories) and having all the three risk factors (1 category), the risk factors being smoking, Coronary Artery Disease and hyperlipidaemia) with different average blood pressure (BP) will be part of the validation studies. The number of patients to be included in this study will be determined after discussion with hospitals involved. Each patient’s 3D image of AAA reconstructed using CT scans taken 2 years apart is compared with that of the predicted growth based on initial scan and patient’s average BP. The prediction will be accomplished by an AI software that learns continuously, in that if the predictions are off, that patient’s actual growth data together with the intermediate synthetic data will be integrated with the database.

The method and the validated results will be demonstrated at hospitals across the country. The target is to visit a certain number of hospitals. The best course of action has to be arrived at after discussions with the clinicians. Initially, the software will be made available free-of-charge to select hospitals such as Apollo Chennai, Sree Chitra Tirunal Institute for Medical Sciences and Technology (SCTIMST) Thiruvanathapuram and Narayana Hrudayalaya Bangalore, where the greatest number of aneurysm repairs transpire. Based on feedback received, it will be determined if the database needs expansion.

Classification of endoleaks

Expected deliverables of the research

Functional Smart Polymers

  • Stimuli-responsive microfluidic flow control devices namely, micro pump, micro valve and micro mixer and microfluidic sensors.

  • Integration of the microfluidic flow control devices (to be developed) with an existing LoC device.

The output will be a software based on Deep learning guided by data derived from physics-based, stochastic, stress-mediated, continuum level, growth and remodelling solutions together with hardto-quantify risk factors such as tobacco use and family history, to predict the growth and rupture of aneurysms, pre and post EVAR, for an individual.

Current status

  • The procurement of equipment, software and workstations is under progress
  • Published one research article in Journal of Applied Physics
  • One postdoctoral candidate will start working from July 2021 on the synthesis of liquid crystal thin films.

Unitary structural constitutive relation that takes into account the distribution of arterial collagen based on the novel self-annihilating invariants is completed. This work will be communicated to a top journal in mechanics. Some of the known issues present in the existing HGO (most popular) is resolved using our model.

Collaborations

International Collaborations

  • Prof. Seungik Baek, Michigan State University, East Lansing,USA link

  • Prof. Albert P. H. J. Schenning, Stimuli Responsive Functional Devices Lab, Eindhoven University of Technology, The Netherlands link

  • Prof. Patrick Onck, Mechanics of Materials Group, University of Groningen, The Netherlands link

  • Prof. Apala Majumdar, University of Strathclyde, Glasgow, UK link

  • Prof. Stéphane PA Bordas, University of Luxembourg, Luxembourg. link

  • Prof. Timon Rabczuk, Bauhaus University, Weimar, Germany link

Organizing mini-symposia in popular conferences such as Materials Research Society (MRS), Engineering Mechanics Institute, ACS, IUTAM and European Mechanics Society. The center will also organize international workshops/conferences at IIT Madras by inviting top researchers in the field.

The faculty members of the proposed center have active collaborations with the top research groups around world in both the proposed domains. The following activities will be undertaken to enhance the international connect of the center and the institute.

  • All the PhD students working on the topics proposed by the center will have joint PhD guidance with a foreign collaborator.

  • The PhD students and Postdocs will be sent to visit the collaborator’s labs for extended periods of time. They serve as ambassadors for the research excellence at IIT Madras.

  • Center will pro-actively invite the PhDs and Postdocs from the collaborator’s group to spend some time (at least 3 months) at IITM.

  • Organize mini-symposia in popular conferences such as MRS, Engineering Mechanics Institute, ACS, IUTAM and European Mechanics Society.

  • At least 3 to 4 members from the center will attend top conferences in the area.

  • The center will also organize international workshops/conferences at IIT Madras by inviting top researchers in the field.

  • An MoU for joint doctoral program with TU/Eindhoven and University of Groningen will be explored.

  • The existing JDP with Michigan State University will be used to initiate PhD student guidance in the field of AAA.

The center will send research scholars and scientist to visit laboratories of collaborators for extended training on experiments. Further, it will also willingly train their students/staff on modelling and simulation aspects. The faculty and scholars of the center will attend international conferences and exhibitions to showcase the work done at IITM and increase IITM’s visibility in the global arena. Further, the center will also organize one international conference on responsive soft matter by bringing in the top researchers in the field. This would increase the center’s collaboration base and lead to an enhancement of the visibility of publications resulting from the center’s scientific endeavours. We are confident that, atleast some of the PIs of this proposal have the potential to be editors in top international journal. We believe that our efforts will reach levels, where one of the PIs would be invited for a plenary lecture in one of the top-conferences in the area.

Industrial collaborations

Achira Labs: Develops Microfluidic Point of Care diagnostic devices

The computational medical diagnostics used in conjunction with CT and MRI is in nascent state and is likely to gain ground soon. Such diagnostics can be used to plan an intervention or arrive at an informed prognosis by the clinicians. In phase III, there is a good possibility that the hospitals will be interested in a clinically validated AI tool. As of today, there is no such tool capable of predicting the growth of AAA with a reasonable accuracy. If we bring such a tool to the market, it is likely to be pursued by healthcare companies around the world. The research in vertical-2 (Smart Responsive Soft Sensors & Actuators) will be of interest to various microfluidic point of care medical diagnostics companies. We have interacted with the CEO of Achira Labs based out of Bengaluru to request him to be the part of the centre as an advisor and collaborator to which he gladly agreed.

Societal impact

The work proposed by the center under the two verticals can positively impact healthcare in India and abroad. In the short term (phase I), for both the focus areas, only the research community will be positively impacted because of the publications and presenting in conferences. In the medium term, the AI-based software will be undergoing trials in select hospitals, and therefore the medical fraternity will be aware of this tool. For the second vertical, a prototype will be ready and may pique the interest of related industries. In the long term, the AI-based tool is likely to be used by vascular surgeons and cardiologists to get inputs to enable them to make an informed prognosis for both the pre and post-surgical treatment of aneurysms. Such patient-specific computational diagnostic tools will play a greater role in the future and transform medical prognosis, in that greater number of lives will be saved by timely interventions.The research carried out in the second vertical contributes to the development of portable and programmable lab-on-chip devices. This technology has the potential to transform the way medical diagnostics is done today, especially in the remote areas of the country. The outcome of the work is likely to lead to the development of accessible and affordable medical diagnostic tools, where setting up elaborate laboratories is a challenge.

The work proposed by the center under the two verticals can positively impact healthcare in India and abroad. The research carried out in the Functional Smart Polymers domain contributes to the development of portable and programmable lab-on-chip devices. This technology can transform the way medical diagnostics is done today, especially in remote areas of the country. The outcome of this work is likely to lead to the development of accessible and affordable medical diagnostic tools, where setting up large scale laboratories is a challenge.

Sustenance statement

The outcome of both the verticals is focused on the well-being of society. Consequently, one expects to attract significant interest from the industry. The developed systems are likely to play a vital role in medical diagnostics and drug delivery, which has enormous potential to change the healthcare landscape in the world.

An advisory board made up of successful entrepreneurs and industrialists will be set up to advise on the issues related to IP and commercialization. The lab is envisioned to be a fertile ground for startups to emerge from the activities of the center, i.e., startups based on licensing of AI software to predict growth and rupture and licensing/manufacturing of the next generation lab-on-a-chip device.

By working together as a team with cross-contributions in both domains (Living Matter and Functional Smart Polymers), we also envisage a modular and efficient finite element package capable of solving problems that involve large deformations in engineering to emerge.

Nonetheless, the center is confident that it will succeed in attracting funds from various sources such as:

The outcome of the project is focussed on the well-being of the society. Consequently, one expects to attract significant interest from the industry. We already have a support letter from Achiral Laboratories Bengaluru that develop point-of-care diagnostic devices. These systems are likely to play a key role in medical diagnostics and drug delivery, which has enormous potential of changing the landscape of healthcare in the world. In order to guide the center on various activities, an advisory board will be set up to advise on the issues related to IP and commercialization. We understand that there are several issues that must be tackled before one can commercialize a prototype developed in a laboratory. By having advisors who have succeeded in taking the leap from laboratory to commercialization will be part of the advisory board; the contacts they bring will be very valuable in securing funding for commercialization. These actions should provide a fertile ground for startups to emerge from the activities of the center, i.e., startups based on licensing of AI software to predict growth and rupture, and licensing/manufacturing of the next generation lab-on-a-chip device. By working together as a team with cross-contributions in both the domains, we also envisage a modular and efficient finite element package capable of solving problems that involve large deformations in engineering to emerge. Nonetheless, the center is confident that it will succeed in attracting funds from various sources such as:

  • Government and Industry funding
  • Selling IP related to software and device development
  • Revenue generation through training to MSME
  • Revenue generation from startups, which could emerge from this center

Technical/ Scientific Progress

New work done in the project

Vertical#1:

The prediction of the progression of an aneurysm requires the tissues' mechanical characteristics. The tri-layered aortic tissue is reinforced by collagen fibers, which maintain the structural integrity of the tissue wall. It is also known that these collagen fibers cannot sustain compressive loads. Traditionally, this is ensured by switching-off the fibers' response during compression. However, such a switch can lead to discontinuities in the stresses. To address that, we have constructed a novel anisotropic ‘matched invariant’ that automatically vanishes in pure compression. This eliminates the need for an external tension-compression switch. Additionally, the resulting Generalized Structure Tensor (GST) based model is able to predict the mechanical response of various tissues' biaxial test data with significantly higher correlation and with the same number of material parameters as that of the existing constitutive relations [Ref#5]. The capability of the matched invariant in the Angular Integration (AI) approach will be explored in the near future.

Vertical#2:

Soft actuators can produce flexible movements due to the integration of microscopic changes at the molecular level into a macroscopic deformation of actuator materials. Chitosan is a versatile hydrogel widely used in various technologies for its excellent film-forming capability and is well suited for niche applications in bioelectronics, flexible portable electronics and microelectromechanical systems. In spite of being a promising candidate for several applications, investigations on the optical anisotropy of chitosan thin films are few. In a recent work, we used spectroscopic ellipsometry to investigate the optical anisotropy of chitosan thin films for (dry) film thicknesses in the range of 35–350 nm. For all of the films we investigated, the optical anisotropy increased with the decreasing thickness of the dry film and upon exposure to solvent vapour, it decreased exponentially with time [Ref#3]. We also measured the the critical concentration (Pg) which enhances the glass-like transition of substrate supported glassy chitosan thin films in the presence of water vapour [Ref#4]. Based on our study on the overall folding and actuation characteristics of a bilayer system applied for gripping submerged objects, we have demonstrated the application of the chitosan-PMMA bilayer in gripping and lifting an immersed object, approximately 155 times the weight of the bilayer. The solvent (water in this study) in which the object is immersed itself acts a trigger for this bilayer based soft gripper [Ref#1].

Recent and promising integrable microfluidic control systems include a photo-responsive gel based bead as a micro-valve and photo-induced oscillations in artificial cilia as aiders for mixing of fluids. Actuators providing alternative, controlled shape deformations with additional functionalities possible are desirable. Our recent work on controlled deposition of a light-responsive liquid crystal (LC) ink with direct ink writing revealed that passive substrates, such as thermoplastics, can be made responsive without fully covering the surface with active material or affecting their performance, which reduces the fabrication cost as less of the expensive LC material is needed [Ref#2].

Infrastructure developments

S.No.InfrastructureEquipmentUser for Status
1Microfluidic Flow characterization Flow Sensor, Pressure Sensor, Flow BoardTo measure the flow rates and pressure capabilities of micro-fluidic flow control systemProcured
2Microdisplacement characterization Capacitive Displacement Sensor and ReaderTo measure the micron scale displacements of smart actuatorsProcured
33D PrinterSLA 3D Printer and accessoriesTo fabricate microfluidic chips with channels of the order of 100 microns accuratelyProcured
4Magnetic Stirrer + Hot PlatesMagnetic Stirrer + Hot Plates Mixing solutions and heating the samplesProcured
5Thermal Imaging Thermal Imaging CameraTo visualize the temperatures attained by the thin films during heat/light based actuation Procured
6UV/Vis/NIR Illumination Setup UV/Vis LED and Lamp based light sources, NIR Laser Source, Filters, LED Driver, Optical Bread Board, Black BoxPolymerization of the liquid crystal monomer mixture to make thin films and Actuation of thin filmsOrder Placed, Partially funded by the Department and DST Project (Ratna Kumar Annabattula)
7Oven OvenHeating the samples, evaoporation of solventsProcessing PO, Funded by the Department
8Polarizing Microscope Polarizing MicroscopeTo characterise the micro-structure of the liquid crystal mesogensWaiting for Ministry Approval for Global Tendering
9Work stations CPU - 36 Cores x Intel Xeon (R) W-2295 @ 3.00 GHz, 128 GB RAM, Storage - 1 TB NVMe SSD + 2 x 2 TB HDD, Graphic Card - NVIDIA Quadro RTX 400, 8 GB VRAMTo simulate the multi-physics/multi-scale mechanisms involving in the actuation of stimuli-responsive thin filmsProcured
10Work stations CPU - 36 Cores x Intel Xeon (R) W-2295 @ 3.00 GHz, 128 GB RAM, Storage - 1 TB NVMe SSD + 2 x 2 TB HDD, Graphic Card - NVIDIA Quadro RTX 400, 8 GB VRAMImage and video processing/ matlab based simulationsProcured
11Optical Imaging High Speed camera Recording time evolution of ultra-fast actuationTender floated and no bid received from class-I and class-II supplier. Going for global tendering
123D Image Segmentation and Processing Software Simpleware ScanIPPerforming image segmentation and subsequently generate 3D geometry with FE meshes from 3D image data (CT, MRI, etc)Procured
13Work stations CPU - 36 Cores x Intel Xeon (R) W-2295 @ 3.00 GHz, 128 GB RAM, Storage - 1 TB NVMe SSD + 2 x 2 TB HDD, Graphic Card - NVIDIA Quadro RTX 400, 8 GB VRAMGenerating 3D geometry using ScanIP softwareProcured
14Work stations CPU - 36 Cores x Intel Xeon (R) W-2295 @ 3.00 GHz, 128 GB RAM, Storage - 1 TB NVMe SSD + 2 x 2 TB HDD, Graphic Card - NVIDIA Quadro RTX 400, 8 GB VRAMPerforming FE simulations pertaining to Growth & Remodelling of AAAsProcured
15Work stations CPU - 36 Cores x Intel Xeon (R) W-2295 @ 3.00 GHz, 128 GB RAM, Storage - 1 TB NVMe SSD + 2 x 2 TB HDD, Graphic Card - NVIDIA Quadro RTX 400, 8 GB VRAMComputations pertaining to prediction of growth and rupture using Deep LearningProcured

Output

Journal Publications:

  1. Meena RK, Rapaka SD, Pratoori R, Annabattula RK, Ghosh P. “An embedded interface regulates the underwater actuation of solvent-responsive soft grippers”. Soft Matter, 2022 (in press), link- Q1, 78th percentile
  2. Pozo MD, Sol JA, van Uden SH, Peeketi AR, Lugger SJ, Annabattula RK, Schenning AP, Debije MG. “Patterned Actuators via Direct Ink Writing of Liquid Crystals”. ACS Applied Materials & Interfaces. 2021, 13, 49, 59381–59391.- Q1, 93rd percentile
  3. Pradipkanti Devi Lairenjam, Sathish K. Sukumaran, and Dillip K. Satapathy, “Modulation of Optical Anisotropy in Chitosan Thin Films: Role of Swelling”, Macromolecules. 2021, 54, 23, 10931–10942 link, Q1 , 95th percentile
  4. Aathira Murali, Manikandan Ganesan, Dillip K. Satapathy, PB Sunil Kumar, “Penetrant-Induced Glass-like Transition in Thin Chitosan Films”, J. Phys. Chem. B 2021, 125, 45; link Q1, 79th percentile
  5. K.Arvind, K.Kannan, ‘‘Structure-Tensor based Switchless Constitutive Relation for Arterial Tissues that Self-annihilate Contribution from fibers in Compression’’ (To be submitted)

Conferences:

  1. Peeketi AR (Presenter), Ramgopal A, Jayoti D, Swaminathan N, Annabattula RK. “Finite element modelling of light-responsive liquid crystal polymer network thin films”. 28th National Conference on Liquid Crystals (NCLC). 21-23 December 2021.
  2. Ramgopal A, Annabattula RK, “Design and Development of Light-driven motorless miniature cart - A computational analysis”. Indo-Korean Workshop on, “Multi-Functional Materials for Extreme Loading” (MFMEL), 22-24 February, 2021.

Seminars: 1 Prof. Apala Majumdar, University of Strathclyde, UK, 24-09-2021, Modelling Nematic Liquid Crystals for Novel Technologies and Applications

Mobility

Visits planned for PI, co-PIs, international collaborators and students (both inbound and outbound)

 

  1. Student (PhD Scholar)- Akhil R Peeketi- Technical Universitat Eindhoven, The Netherlands, Jan 13 - April 10, 2022, To gain experience in synthesis and characterization of liquid crystal polymer based thin films.
  2. Student (PhD Scholar) K. Arvind- Michigan State University, USA, March, 2022, To gain experience in biaxial testing of soft tissues and modelling the active response.

Relationship

Industrial Engagement

1 Achira Labs, Bangalore, India, Join. Development and commercialization of innovative technologies for point-of-care medical testing.

University Engagement

  1. Prof. A. P. H. J. Schenning, Eindhoven University of Technology, Eindhoven, The Netherlands (a.p.h.j.schenning@tue.nl)
  2. Prof. Patrick Onck, University of Groningen, Groningen, The Netherlands (p.r.onck@rug.nl)
  3. Prof. Apala Majumdar, University of Strathclyde, Glasgow, United Kingdom (apala.majumdar@strath.ac.uk)
  4. Prof. S. Krishna Prasad, Centre for Nano and Soft Matter Sciences, Bangalore, India (skprasad@cens.res.in)
  5. Prof. Sathish K. Sukumaran, Yamagata University, Yonezawa,Yamagata, Japan (sathish@yz.yamagata-u.ac.jp)
  6. Prof. Seungik Baek, Michigan State University, Michigan, USA (sbaek@egr.msu.edu)

Updates

Relevant Updates

Student Training:

Mr. Adithya Ramgopal, MS, Graduated (2021) (Ratna Kumar Annabattula) Mr. Akhil Reddy Peeketi, PhD (Ratna Kumar Annabattula & Narasimhan Swaminathan) Mr. Neeraj CS, PhD (Ratna Kumar Annabattula) Mr. Rajesh Kumar Meena, PhD (Ratna Kumar Annabattula) Mr. Akash Patil, MS (Ratna Kumar Annabattula) Dr. Divya Jayoti, Post-Doc, (Ratna Kumar Annabattula) Mr. Rohit Kumar, MTech, (Ratna Kumar Annabattula) Mr. Nirmal Patel , MTech, (Ratna Kumar Annabattula) Mr. Vipin Kumar, PhD (Dillip Kumar Satapathy) Mr. Sonam Zhangpo Bhutia, PhD (Dillip Kumar Satapathy) Ms. Sarah Ahmed Siraj, PhD (Dillip Kumar Satapathy) Ms. Ankita Pradhan, PhD (Pijush Ghosh & Dillip K. Satapathy) Mr. K. Arvind, PhD (Krishna Kannan)