Department of Electrical Engineering

Indian Institute of Technology Hyderabad (IITH) is a premier institute of science and technology established in 2008. IITH has been consistently ranked in the&nbsp;<a href="https://iith.ac.in/reports/" rel="noopener noreferrer">top 10 institutes</a>&nbsp;in India for Engineering&nbsp;<a href="https://www.nirfindia.org/2021/EngineeringRanking.html" rel="noopener noreferrer" target="_blank">according to NIRF</a>&nbsp;making it one of the most coveted schools for science and technology in the country.

IITH offers&nbsp;<a href="https://iith.ac.in/academics/under-graduate/">undergraduate programs</a>&nbsp;in all the classical engineering disciplines, applied sciences, design, as well as several modern interdisciplinary areas. Students are given a flexibility to explore a broad set of areas, and potentially pursue a minor or double major in a discipline that is not their own. Students who wish to seek a deeper understanding of their own discipline are strongly encouraged to get involved in cutting-edge research with the help of a faculty to mentor them, and earn an Honors in their own field.

The very foundation of IIT Hyderabad is based on&nbsp;<a href="https://iith.ac.in/research/">research and innovation</a>. The vibrant research culture is evident from the number of patents and publications that IITH produces consistently every year. IITH offers&nbsp;<a href="https://iith.ac.in/academics/programmes-offered/">graduate programs</a>&nbsp;at both a masters, and a doctoral level, in several diverse areas. There are separate programs for technology, design, science, and liberal arts. The&nbsp;<a href="https://iith.ac.in/academics/post-graduate/">MTech program</a>&nbsp;is offered in various modes and durations to cater to the ever-growing need of postgraduate level professionals in the country.

IITH encourages and supports&nbsp;<a href="https://iic-iith.netlify.app/index.html" rel="noopener noreferrer" target="_blank">innovation and entrepreneurship</a>&nbsp;at every stage. The minor program in entrepreneurship is open to all students of IITH, and many of the courses are offered by industrialists who are entrepreneurs themselves. There are various&nbsp;<a href="https://iith.ac.in/research/centres-incubators/">innovation centers and incubators</a>&nbsp;that promote entrepreneurship and help mentor young innovators. IITH has been very successful in building tie-ups with leading academic institutions around the globe.

IITH enjoys a very special relationship with Japanese universities and industries that goes beyond academic and research collaborations. In fact, some of the iconic buildings in IITH campus will carry the signature of Japanese architecture.

IITH creates a unique holistic ecosystem for education that offers interactive learning, a very flexible academic structure, cutting-edge research, strong industry collaboration, and entrepreneurship. This is an environment which enables students and faculty to translate their dreams into realities.

IIT Hyderabad

Transient electronics fabricated using low cost, abundant, biodegradable materials is one of the promising solutions to address the issue of e-waste. This work is the first demonstration of an ultra-fast wirelessly destructible non-volatile memory using a novel MgO-PVP-Gr composite material synthesized by a low cost solution processed method. Optimized synthesis conditions result in the composite based memristor device which exhibits bipolar resistive switching with excellent device performances viz., on/off ratio of 8.5 × 103, switching endurance of 500 cycles, data retention of &gt;104 s at lower set and reset voltages of +4 V, -4 V. The mechanism for conduction bridging based resistive switching (RS) is discussed in terms of the formation and rupture of the electrochemically active silver metal clusters. Furthermore, the composite is used to fabricate crossbar memory architecture that finds wide applications in non-volatile memories. Modelling and bending studies on the memristor reveal outstanding mechanical robustness along with stability, primarily attributed to high young's modulus of graphene. Due to the high hydro-dissolution rates of MgO and PVP, the device dissolves completely in water (within 3 s). Finally, wirelessly controlled memory deletion using the mobile application is demonstrated which offers better control for the end user to handle memory devices useful in security applications. © 2019

World University root node

Materials Science in Semiconductor Processing

Wirelessly destructible MgO-PVP-Graphene composite based flexible transient memristor for security applications

Herein, we report cuprous oxide nanocubes decorated reduced graphene oxide (CNC-rGO) immersed in chitosan matrix as a versatile and enhanced electrochemically active electrode material for both supercapacitor and hydrogen peroxide (H 2 O 2 ) sensor applications. The CNC-rGO was synthesized by one-pot scalable chemical precipitation method. The morphology and crystal structure of as-synthesized hybrid material was characterized by field emission scanning electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy. The CNC-rGO hybrid material immersed in the chitosan matrix was used as an enhanced electrochemically active electrode material for supercapacitor and hydrogen peroxide (H 2 O 2 ) sensor. The fabricated CNC-rGO hybrid in chitosan matrix as an electrode showed remarkable charge storage capacity of 772.3 F g −1 (12.87 mA h g −1 ) at a current density of 0.2 A g −1 with high cyclic stability over 2000 charge-discharge cycles. Similarly, H 2 O 2 sensing performance of the same electrode exhibits very high sensitivity of 0.33 A M −1 cm −2 within a linear range of detection of 20–160 μM. Thus, the synthesized CNC-rGO hybrid material composed of numerous cuprous nanocubes on rGO nanosheets with large active sites showed enhanced electrochemical activity beneficial towards the supercapacitor and H 2 O 2 sensor applications. © 2019 Elsevier B.V.

Journal of Electroanalytical Chemistry

Cuprous oxide nanocubes decorated reduced graphene oxide nanosheets embedded in chitosan matrix: A versatile electrode material for stable supercapacitor and sensing applications

This report demonstrates of the direct growth of ternary compound ZnSnO 3 nanocubes on silica cloth for the fabrication of scalable tactile sensors for monitoring physiological signals which even the highly sensitive tactile sensors fail to measure and artificial electronic skin (E-skin) without the use of sophisticated silicon wafer based technologies. The fabricated sensor exhibited a sensitivity and response time of 0.12 KPa −1 and 350 ms respectively. Inspired by the inherent alignment of the ZnSnO 3 nanocubes on silica microfibers, the fabricated sensor was further demonstrated to be able to recognize wrist pulse pressure, finger movement, wrist movement and finger pressing. Furthermore, large area sensors array (4 × 4) were fabricated and integrated onto human hand which can “feel” the touch and spatially map the response paving way for the development of E-skin. Also, the sensor array was able to detect and map the shape and location of unknown objects placed on it and could trace the index finger trajectory made on the sensor array. The fabricated pressure sensor was tested for its reliability by performing bending test studies under harsh deformations and 500 bending cycles which resulted in negligible change in the performance of the sensor. © 2019

Monitoring of physiological body signals and human activity based on ultra-sensitive tactile sensor and artificial electronic skin by direct growth of ZnSnO 3 on silica cloth

Herein we report a simple and selective open-circuit potential-time (OCPT) based preparation of nickel hexacyanoferrate (NiHCF) on nickel and iron impurity containing carbon nanotube (CNT*, * = intrinsic metal impurity) modified glassy carbon electrode (GCE/CNT*NiHCF) using pH 2 ferricyanide solution. Unlike potentiodyanamic cycling, OCPT allowed the selective preparation of NiHCF with a distinct redox features at an equilibrium potential = 0.38 V in pH 7 phosphate buffer solution (PBS). Kinetic parameters such as transfer coefficient and rate constant of GCE/CNT*NiHCF were calculated from cyclic voltammetry (CV) studies of the redox peak. Characterization of CNT* and CNT*NiHCF by XRD, TEM, FTIR and Raman spectroscopy techniques revealed the presence of iron and nickel impurities in CNT* and confirmed the formation of CNT*NiHCF and CNT*Fe-NiHCF (Fe-NiHCF = FeHCF + NiHCF) by OCPT and potentiodynamic cycling, respectively. Furthermore, electrocatalytic activity of CNT*NiHCF modified electrode was explored with a model analyte, hydrazine (Hz) in pH 7 PBS. Likewise, electron number involved during the rate determining step, complete electrocatalytic reaction and its heterogeneous rate constant values were calculated using CV technique. At optimal amperometric i-t conditions, GCE/CNT*NiHCF showed a linear calibration plot with a current linearity on a range of 20–200 μM with current sensitivity and detection limit (signal-to-noise = 3) values of 1217.39 nA μM −1 cm −2 and 0.8 μM respectively. It also displayed zero interference from oxalic acid, uric acid, ascorbic acid, sulphate, nitrite, nitrite, magnesium and sodium displaying feasibility to Hz detection in polluted water bodies. © 2019

Selective in-situ derivatization of intrinsic nickel to nickel hexacyanoferrate on carbon nanotube and its application for electrochemical sensing of hydrazine

While most electrochemical uric acid (UA) sensors are developed on the conventional electrodes and involve either multiple steps based synthesis routes and/or complicated fabrication processes, this paper is the first demonstration of direct growth of pyrite FeS2 on pencil-graphite electrode (PGE) for non-enzymatic UA sensing. FESEM images of the pyrite FeS2-PGE reveal mesoporous microspherical structure of pyrite FeS2 along with graphite flakes of PGE and EDX, Raman spectroscopic data validate growing of pyrite FeS2 on PGE. The pyrite FeS2-PGE sensor exhibited detection limit of 6.7 μM, excellent linearity, reproducibility, selectivity over glucose, urea, ascorbic acid with the sensitivity of 370 μA mM−1 cm−2 in the range of 10–725 μM of UA. These improved analytical performances can be attributed to high conductivity of the pyrite FeS2, larger electro-active surface area of the mesoporous microspherical pyrite FeS2 grown on PGE (than only PGE) and abundance in defect sites originating from both the pyrite FeS2 as well as functional groups of pencil graphite. Furthermore, the sensor was validated against UA in urine sample and the result supports well with the UA concentration achieved from colorimetric technique. Development of this low cost, non-enzymatic, sensitive and highly selective pyrite FeS2-PGE bases UA sensor is a significant step in the development of practically viable sensors for point-of-care applications in clinical and pharmaceutical analyses. © 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

Electroanalysis

FeS2 Grown Pencil Graphite as an In-expensive and Non-enzymatic Sensor for Sensitive Detection of Uric Acid in Non-invasive Samples

An index code is said to be locally decodable if each receiver can decode its demand using its side information and by querying only a subset of the transmitted codeword symbols instead of observing the entire codeword. Local decodability can be a beneficial feature in some communication scenarios, such as when the receivers can afford to listen to only a part of the transmissions because of limited availability of power. The locality of an index code is the ratio of the maximum number of codeword symbols queried by a receiver to the message length. In this paper we analyze the optimum locality of linear codes for the family of index coding problems whose min-rank is one less than the number of receivers in the network. We first derive the optimal trade-off between the index coding rate and locality with vector linear coding when the side information graph is a directed cycle. We then provide the optimal trade-off achieved by scalar linear coding for a larger family of problems, viz. problems where the min-rank is only one less than the number of receivers. While the arguments used for achievability are based on known coding techniques, the converse arguments rely on new results on the structure of locally decodable index codes. © 2019 IEEE.

IEEE International Symposium on Information Theory - Proceedings

Locality in Index Coding for Large Min-Rank

We consider network coding for a noiseless broadcast channel where each receiver demands a subset of messages available at the transmitter and is equipped with noisy side information in the form an erroneous version of the message symbols it demands. We view the message symbols as elements from a finite field and assume that the number of symbol errors in the noisy side information is upper bounded by a known constant. This communication problem, which we refer to as broadcasting with noisy side information (BNSI), has applications in the re-Transmission phase of downlink networks. We derive a necessary and sufficient condition for a linear coding scheme to satisfy the demands of all the receivers in a given BNSI network, and show that syndrome decoding can be used at the receivers to decode the demanded messages from the received codeword and the available noisy side information. We represent BNSI problems as bipartite graphs, and using this representation, classify the family of problems where linear coding provides bandwidth savings compared to uncoded transmission. We also provide a simple algorithm to determine if a given BNSI network belongs to this family of problems, i.e., to identify if linear coding provides an advantage over uncoded transmission for the given BNSI problem. © 2018 IEEE.

2018 24th National Conference on Communications, NCC 2018

On Linear Codes for Broadcasting with Noisy Side Information

An electrochemical dopamine (DA) sensor has been fabricated by modifying a glassy carbon electrode (GCE) with ruthenium disulfide (RuS2) nanoparticles (NPs). FESEM and TEM micrographs show the NPs to have an average size of ~45 nm. XRD, Raman and EDS, in turn, confirm the successful formation of cubic phased RuS2 NPs. The modified GCE displays has attractive features of merit that include (a) an ultra-low detection limit (73.8 nM), (b) fast response time (&lt; 4 s), (c) a low oxidation potential (0.25 V vs. Ag|AgCl), (d) excellent reproducibility and stability, (e) an electrochemical sensitivity of 18.4 μA μM−1 cm−2 and 1.8 μA.μM−1.cm−2 in the linear ranges from 0.1–10 μM of DA (R2 = 0.97) and 10–80 μM of DA (R2 = 0.99), respectively. The sensor exhibits excellent specificity over potential interferents like ascorbic acid, glucose and uric acid. The superior performance of the sensor is attributed to its high electrical conductivity, large electro-active surface, and large numbers of exposed catalytically active sites resulting from the presence of unreacted sulfur atoms. [Figure not available: see fulltext.]. © 2019, Springer-Verlag GmbH Austria, part of Springer Nature.

Microchimica Acta

A ruthenium(IV) disulfide based non-enzymatic sensor for selective and sensitive amperometric determination of dopamine

Building security systems is improving at a mammoth rate since the past decade, to cope with the threats of unauthorized access and fraudulent intentions. In high security public places like airports, embassies, corporate offices etc. only facial recognition for verification does not suffice full proof security. To predict the intention of an individual we must capture the objects around the subject/individual and his interactions with them in real time environment with good accuracy besides recognizing them. In this paper we designed an Enterprise Class Deep Neural Network (EcDNN) architecture built on the base architecture of YOLO network. Our proposed multitask learning network architecture recognizes the faces of registered individual as well as objects in the person's vicinity at one shot which achieves significant improvement in performance in terms of speed and model size without loss of precision, if it would have done separately in a cascaded model architecture. Our proposed single network architecture employing multitask learning is achieving state of the art recognition accuracy of 79 mAP at 40 fps with 33 % reduction in model size and an approximately 4x speedup with respect to the benchmark state of the art architectures, validated on standard dataset of PASCAL VOC 2012, FDDB and custom office dataset. © 2019 IEEE.