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Recent Submissions

  • Inherent Surface Activation of Laser-Scribed Graphene Decorated with Au and Ag Nanoparticles: Simultaneous Electrochemical Behavior toward Uric Acid and Dopamine

    Beduk, Tutku; De Oliveira Filho, José Ilton; Ait Lahcen, Abdellatif; Mani, Veerappan; Salama, Khaled N. (Langmuir, American Chemical Society (ACS), 2021-11-17) [Article]
    Laser-scribed graphene electrodes (LSGEs) have attracted great attention for the development of electrochemical (bio)sensors due to their excellent electronic properties, large surface area, and high porosity, which enhances the electrons’ transfer rate. An increasing active surface area and defect sites are the quickest way to amplify the electrochemical sensing attributes of the electrodes. Here, we have found that the activation procedure coupled to the electrodeposition of metal nanoparticles resulted in a significant amplification of the active area and the analytical performance. This preliminary study is supported by the demonstration of the simultaneous electrochemical sensing of dopamine (DA) and uric acid (UA) by the electrochemically activated LSGEs (LSGE*s). Furthermore, the electrodeposition of two different metal nanoparticles, gold (Au) and silver (Ag), was performed in multiple combinations on working and reference electrodes to investigate the enhancement in the electrochemical response of LSGE*s. Current enhancements of 32, 27, and 35% were observed from LSGE* with WE:Au/RE:LSG/CE:LSGE, WE:Au/RE:Au/CE:LSGE, and WE:Au/RE:Ag/CE:LSGE, compared to the same combinations of LSGEs without any surface activation. A homemade and practical potentiostat, KAUSTat, was used in these electrochemical depositions in this study. Among all of the combinations, the surface area was increased 1.6-, 2.0-, and 1.2-fold for WE:Au/RE:LSG/CE:LSGE, WE:Au/RE:Au/CE:LSGE, and WE:Au/RE:Ag/CE:LSGE prepared from LSGE*s, respectively. To evaluate the analytical performance, DA and UA were detected simultaneously in the presence of ascorbic acid. The LODs of DA and UA are calculated to be ∼0.8 and ∼0.6 μM, respectively. Hence, this study has the potential to open new insights into new surface activation strategies with a combination of one-step nanostructured metal depositions by a custom-made potentiostat. This novel strategy could be an excellent and straightforward method to enhance the electrochemical transducer sensitivity for various electrochemical sensing applications.
  • A Hardware/Software Co-design Methodology for In-memory Processors

    Yantir, Hasan Erdem; Eltawil, Ahmed; Salama, Khaled N. (Journal of Parallel and Distributed Computing, Elsevier BV, 2021-11) [Article]
    The bottleneck between the processor and memory is the most significant barrier to the ongoing development of efficient processing systems. Therefore, a research effort begun to shift from processor-centric architectures to memory-centric architectures. Various in-memory processor architectures have been proposed to break this barrier to pave the way for ever-demanding memory-bound applications. Associative in-memory processing is a successful candidate for truly in-memory computing, in which processor and memory are combined in the same location to eliminate the expensive data access costs. The architecture exhibits an unmatched advantage for data-intensive applications due to its memory-centric design principles. On the other hand, this advantage can be revealed fully by an efficient design methodology. This study puts further progressive effort by proposing a hardware/software design methodology for associative in-memory processors. The methodology aims to decrease energy consumption and area requirement of the processor architecture specifically programmed to perform a given task. According to the evaluation of nine different benchmarks, such as fast Fourier transform and multiply-accumulate, the proposed design flow accomplishes an average 7% reduction in memory area and 18% savings in total energy consumption.
  • Resistive Neural Hardware Accelerators

    Smagulova, Kamilya; Fouda, Mohammed E.; Kurdahi, Fadi; Salama, Khaled N.; Eltawil, Ahmed (arXiv, 2021-09-08) [Preprint]
    Deep Neural Networks (DNNs), as a subset of Machine Learning (ML) techniques, entail that real-world data can be learned and that decisions can be made in real-time. However, their wide adoption is hindered by a number of software and hardware limitations. The existing general-purpose hardware platforms used to accelerate DNNs are facing new challenges associated with the growing amount of data and are exponentially increasing the complexity of computations. An emerging non-volatile memory (NVM) devices and processing-in-memory (PIM) paradigm is creating a new hardware architecture generation with increased computing and storage capabilities. In particular, the shift towards ReRAM-based in-memory computing has great potential in the implementation of area and power efficient inference and in training large-scale neural network architectures. These can accelerate the process of the IoT-enabled AI technologies entering our daily life. In this survey, we review the state-of-the-art ReRAM-based DNN many-core accelerators, and their superiority compared to CMOS counterparts was shown. The review covers different aspects of hardware and software realization of DNN accelerators, their present limitations, and future prospectives. In particular, comparison of the accelerators shows the need for the introduction of new performance metrics and benchmarking standards. In addition, the major concerns regarding the efficient design of accelerators include a lack of accuracy in simulation tools for software and hardware co-design.
  • Laser-scribed graphene sensor based on gold nanostructures and molecularly imprinted polymers: Application for Her-2 cancer biomarker detection

    Lahcen, Abdellatif Ait; Rauf, Sakandar; Aljedaibi, Abdulrahman; De Oliveira Filho, José Ilton; Beduk, Tutku; Mani, Veerappan; Alsharee, Husam N.; Salama, Khaled N. (Sensors and Actuators B: Chemical, Elsevier BV, 2021-08-09) [Article]
    Laser scribed graphene (LSG) has shown great potential as a sensing platform due to its high sensitivity, simplicity, porosity, and flexibility. In this context, we report a novel biosensing platform that utilizes LSG electrodes modified with nanostructured gold and molecularly imprinted polymer (MIP) to enhance its sensitivity and selectivity. This biomimetic sensing platform is used to detect the human epidermal growth factor receptor 2 (Her-2) protein, a significant breast cancer biomarker. Hence, a simple and accurate biomimetic sensor is developed in this study. To the best of our knowledge, this is the first report on nanostructured gold modified MIP-based LSG sensor for Her-2. LSG electrodes are fabricated by irradiation of a polyimide sheet using a CO2 laser. Nanostructured gold is electrodeposited onto the LSG to enhance its sensitivity and facilitate better Her-2 immobilization on the sensor surface. For MIP preparation, 3, 4-ethylenedioxythiophene (EDOT) was electropolymerized after pre-adsorption of Her-2 on the electrode surface for 20 min. The MIP deposition, removal, and adsorption parameters were investigated and optimized. The developed sensing strategy showed an excellent ability to detect Her-2 in the concentration range from 1 to 200 ng/mL with a LOD of 0.43 ng/mL. The biomimetic sensor showed high selectivity towards the detection of Her-2 in the presence of other interfering molecules and appreciable recovery values of Her-2 in the spiked undiluted human serum samples. Finally, to show the potential application of the developed LSG-AuNS-MIP sensor as a point-of-care device, the sensor is integrated with a homemade open-source electrochemical analyzer KAUSTat to detect Her-2.
  • Tris(Keto-Hydrazone): A Fully Integrated Highly Stable and Exceptionally Sensitive H 2 S Capacitive Sensor

    Yuvaraja, Saravanan; Bhyranalyar, Veerabhadraswamy Nagarajappa; Bhat, Sachin A.; Vijjapu, Mani Teja; Surya, Sandeep Goud; Yelamaggad, Channabasaveshwar Veerappa; Salama, Khaled N. (Advanced Electronic Materials, Wiley, 2021-06-23) [Article]
    Here a novel tris(keto-hydrazone) monomer having secondary amines and alkoxy groups to detect toxic hydrogen sulfide (H2S) gas is reported. The as-synthesized tris(keto-hydrazone) monomer is successfully integrated on a micro-fabricated device to realize an organic capacitive sensor. The organic sensor's quantitative detection capability toward H2S gas and its specificity against the other toxic gases and volatile organic compounds are investigated. The capacitance sensor achieves an excellent sensitivity (80% parts per million–1) toward H2S gas with an experimental limit of detection of around 25 parts per billion. Besides, the fabricated capacitive sensor displays minimal response to humidity (0.005% RH–1), and high ambient stability (≈8 months) without compromising sensing performance. Furthermore, the energy-dispersive X-ray spectroscopy spectrum analysis confirms the adsorption of sulfur atoms over the surface of the monomer after the exposure to H2S gas. After that, a short purge of N2 gas would suffice to revive the whole device and can work with negligible losses.
  • Robust, Long-Term, and Exceptionally Sensitive Microneedle-Based Bioimpedance Sensor for Precision Farming

    Bu Khamsin, Abdullah; Moussi, Khalil; Tao, Ran; Lubineau, Gilles; Blilou, Ikram; Salama, Khaled N.; Kosel, Jürgen (Advanced Science, Wiley, 2021-06-17) [Article]
    Precision farming has the potential to increase global food production capacity whilst minimizing traditional inputs. However, the adoption and impact of precision farming are contingent on the availability of sensors that can discern the state of crops, while not interfering with their growth. Electrical impedance spectroscopy offers an avenue for nondestructive monitoring of crops. To that end, it is reported on the deployment of impedimetric sensors utilizing microneedles (MNs) that can be used to pierce the waxy exterior of plants to obtain sensitive impedance spectra in open-air settings with an average relative noise value of 3.83%. The sensors are fabricated using a novel micromolding and release method that is compatible with UV photocurable and thermosetting polymers. Assessments of the quality of the MNs under scanning electron microscopy show that the replication process is high in fidelity to the original design of the master mold and that it can be used for upward of 20 replication cycles. The sensor's performance is validated against conventional planar sensors for obtaining the impedance values of Arabidopsis thaliana. As a change is detected in impedance due to lighting and hydration, this raises the possibility for their widespread use in precision farming.
  • IoT Enabled, Leaf Wetness Sensor on the Flexible Substrates for In-situ Plant Disease Management

    Patle, Kamlesh S.; Saini, Riya; Kumar, Ahlad; Surya, Sandeep Goud; Palaparthy, Vinay S; Salama, Khaled N. (IEEE Sensors Journal, IEEE, 2021-06-16) [Article]
    Early plant disease detection and providing the control measures have become highly desirable to improve crop yield. Leaf wetness duration (LWD) is one of the essential parameters related to the development of fungal disease on the leaf canopy. To measured LWD, the leaf wetness sensor (LWS) is widely used. Commercially available LWS are made on printed circuit board (PCB) technology, which has an operational issue during field deployment such as weight of the sensor, contact resistance between the sensor and the leaves, form factor and most importantly, affordability. To mitigate the issues associated with the commercially available LWS, in this work, we have fabricated the in-house IoT-enabled and affordable electronic leaf wetness sensor on the flexible substrates, which is used for integrated plant disease management. Fabricated LWS comprises the interdigitated electrodes (IDEs) on the polyimide flexible substrate. The lab measurement results indicate that fabricated LWS on the flexible substrates offers a response of about 36000% when LWS is exposed to water w.r.t air. The observed response time of the fabricated LWS is about 10 seconds and hysteresis of about ± 4 %. Further, sensor capacitance changes only by 6% over a temperature range from 20 °C to 65 °C. Furthermore, three fabricated sensors LWS and in-house developed internet of things (IoT) enabled systems are deployed on the Ocimum tenuiflorum (Tulsi) medical plant. Field measurement indicates that measured LWD using the fabricated flexible LWS and commercially available LWS (Phytos 31:LWS-L12), METER Group, Inc. USA) shows the absolute difference of 30 minutes.
  • Rapid Point-of-Care COVID-19 Diagnosis with a Gold-Nanoarchitecture-Assisted Laser-Scribed Graphene Biosensor

    Beduk, Tutku; Beduk, Duygu; De Oliveira Filho, Jose; Zihnioglu, Figen; Cicek, Candan; Sertoz, Ruchan; Arda, Bilgin; Goksel, Tuncay; Turhan, Kutsal; Salama, Khaled N.; Timur, Suna (Analytical Chemistry, American Chemical Society (ACS), 2021-06-03) [Article]
    The global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has revealed the urgent need for accurate, rapid, and affordable diagnostic tests for epidemic understanding and management by monitoring the population worldwide. Though current diagnostic methods including real-time polymerase chain reaction (RT-PCR) provide sensitive detection of SARS-CoV-2, they require relatively long processing time, equipped laboratory facilities, and highly skilled personnel. Laser-scribed graphene (LSG)-based biosensing platforms have gained enormous attention as miniaturized electrochemical systems, holding an enormous potential as point-of-care (POC) diagnostic tools. We describe here a miniaturized LSG-based electrochemical sensing scheme for coronavirus disease 2019 (COVID-19) diagnosis combined with three-dimensional (3D) gold nanostructures. This electrode was modified with the SARS-CoV-2 spike protein antibody following the proper surface modifications proved by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM) characterizations as well as electrochemical techniques. The system was integrated into a handheld POC detection system operated using a custom smartphone application, providing a user-friendly diagnostic platform due to its ease of operation, accessibility, and systematic data management. The analytical features of the electrochemical immunoassay were evaluated using the standard solution of S-protein in the range of 5.0-500 ng/mL with a detection limit of 2.9 ng/mL. A clinical study was carried out on 23 patient blood serum samples with successful COVID-19 diagnosis, compared to the commercial RT-PCR, antibody blood test, and enzyme-linked immunosorbent assay (ELISA) IgG and IgA test results. Our test provides faster results compared to commercial diagnostic tools and offers a promising alternative solution for next-generation POC applications.
  • Reply to “Comment on ‘Scattering Cancellation-Based Cloaking for the Maxwell-Cattaneo Heat Waves’”

    Farhat, Mohamed; Guenneau, Sebastien; Chen, P.-Y.; Alù, A.; Salama, Khaled N. (Physical Review Applied, American Physical Society (APS), 2021-05-28) [Article]
    Comment [1] points out possible inconsistencies in the notations of our paper [2] and, based on these remarks, it questions the validity of our conclusions. In this Reply, we demonstrate the general validity of all conclusions in Ref. [2], and we take the opportunity to clarify our notation and our results and to discuss their domain of validity.
  • Breath as the Mirror of Our body, is the Answer Really Blowing in the Wind? Recent Technologies in Exhaled Breath Analysis Systems as Non-invasive Sensing Platforms

    Beduk, Tutku; Durmus, Ceren; Hanoglu, Simge Balaban; Beduk, Duygu; Salama, Khaled N.; Goksel, Tuncay; Turhan, Kutsal; Timur, Suna (TrAC Trends in Analytical Chemistry, Elsevier BV, 2021-05-14) [Article]
    Health care monitoring is an enormous field of research that has great potential to solve many problems in human life. In recent years, non-invasive health monitoring has become a prerequisite for early diagnosis of various diseases such as lung cancer, oxidative stress, diabetes, to enable the prompt treatment and screening of crucial chemicals. Although analyzing of exhaled breath has been correlated with advanced analytical techniques such as gas chromatography and infrared spectroscopy, breath analyzing biosensing systems offer a cost-effective, sensitive platform for a straightforward analysis. However, current non-invasive sensing strategies have been lacking in practicality in terms of the design and usage, on-site ability and accessibility. This review will critically discuss current commercialized breath analyzers, the recent achievements for the use of the detection towards chemical and biological substances from exhaled breath as non-invasive sensing systems including challenges/drawbacks by addressing the practical applications and concerns in the field. The different fabrication strategies, methodology of detection techniques involved in the development of the breath analyzing systems will be overviewed and discussed along with the future opportunities for possible point of care applications with smartphone integration in this review. The scientific and technological challenges in the field are discussed in the conclusion.
  • Hardware Acceleration of High Sensitivity Power-Aware Epileptic Seizure Detection System Using Dynamic Partial Reconfiguration

    Elhosary, Heba; Zakhari, Michael H.; Elgammal, Mohamed A.; Kelany, Khaled A. Helal; Ghany, Mohamed A. Abd El; Salama, Khaled N.; Mostafa, Hassan (IEEE Access, IEEE, 2021-05-11) [Article]
    In this paper, a high-sensitivity low-cost power-aware Support Vector Machine (SVM) training and classification based system, is hardware implemented for a neural seizure detection application. The training accelerator algorithm, adopted in this work, is the sequential minimal optimization (SMO). System blocks are implemented to achieve the best trade-off between sensitivity and the consumption of area and power. The proposed seizure detection system achieves 98.38% sensitivity when tested with the implemented linear kernel classifier. The system is implemented on different platforms: such as Field Programmable Gate Array (FPGA) Xilinx Virtex-7 board and Application Specific Integrated Circuit (ASIC) using hardware-calibrated UMC 65nm CMOS technology. A power consumption evaluation is performed on both the ASIC and FPGA platforms showing that the ASIC power consumption is lower by at least 65% when compared with the FPGA counterpart. A power-aware system is implemented with FPGAs by the adoption of the Dynamic Partial Reconfiguration (DPR) technique that allows the dynamic operation of the system based on power level available to the system at the expense of degradation of the system accuracy. The proposed system exploits the advantages of DPR technology in FPGAs to switch between two proposed designs providing a decrease of 64% in power consumption.
  • Binary transition metal oxide modified laser-scribed graphene electrochemical aptasensor for the accurate and sensitive screening of acute myocardial infarction

    Rauf, Sakandar; Mani, Veerappan; Ait Lahcen, Abdellatif; Yuvaraja, Saravanan; Beduk, Tutku; Salama, Khaled N. (Electrochimica Acta, Elsevier BV, 2021-05-01) [Article]
    Laser-scribed graphene (LSG) electrodes have gained significant interest due to the ease in fabrication, surface modification, and potential to develop various types of electrochemical sensors and biosensors. In these studies, a new type of zinc ferrite nanoparticles (ZnFe2O4 NPs) modified LSG electrochemical sensing system comprising LSG-ZnFe2O4 working electrode, LSG reference, and LSG counter electrode on a single polyimide substrate is presented. LSG-ZnFe2O4 electrodes are fabricated by drop-casting a solution of ZnFe2O4 NPs onto the LSG electrode, which gave a 31% enhancement of sensitivity and electrocatalytic activity compared to the bare LSG electrode. LSG-ZnFe2O4 electrochemical aptasensor for acute myocardial infarction (AMI) screening is developed by detecting the cardiac Troponin-I (cTn-I) biomarker. The results show that the developed aptasensor could detect a broad concentration range of cTn-I with a limit of detection of 0.001 ng/mL and a sensitivity of 19.32 (±0.25) µA/(ng/mL). In addition to this, LSG-ZnFe2O4-aptasensor shows higher selectivity towards the detection of cTn-I and negligible cross-reactivity with other interfering biomolecules. Finally, it is demonstrated that LSG-ZnFe2O4-aptasensor can easily detect different concentrations of cTn-I spiked in human serum samples. These results show that the LSG-ZnFe2O4-aptasensor is a promising diagnostic tool to monitor cTn-I and could be a potential candidate to develop point-of-care devices for cTn-I biomarker detection and various other disease biomarkers in the future.
  • A 0.002-mm2 8-bit 1-MS/s low-power time-based DAC (T-DAC)

    Hassan, Ali H.; Mostafa, Hassan; Refky, Mohamed; Salama, Khaled N.; Soliman, Ahmed M. (IET Circuits, Devices & Systems, Institution of Engineering and Technology (IET), 2021-04-08) [Article]
    Digital-to-analogue converters (DACs) are essential blocks for interfacing the digital environment with the real world. A novel architecture, using a digital-to-time converter (DTC) and a time-to-voltage converter (TVC), is employed to form a low-power time-based DAC (T-DAC) that fits low-power low-speed applications. This novel conversion mixes the digital input code into a digital pulse width modulated (D-PWM) signal through the DTC circuit, then converts this D-PWM signal into an analogue voltage through the TVC circuit. This new T-DAC is not only an energy-efficient design but also an area-efficient implementation. Power optimization is achieved by controlling the supply voltage of the TVC circuit with a discontinuous waveform using a low bias current. Moreover, the implementation area is optimized by proposing a new DAC architecture with a coarse-fine DTC circuit. Post-layout simulations of the proposed T-DAC is conducted using industrial hardware-calibrated 0.13 μm. Complementary metal oxide semiconductor technology with a 1 V supply voltage, 1 MS/s conversion rate, and 0.9 μW power dissipation.
  • Enhanced acoustic pressure sensors based on coherent perfect absorber-laser effect

    Farhat, Mohamed; Ahmed, Waqas Waseem; Khelif, Abdelkrim; Salama, Khaled N.; Wu, Ying (Journal of Applied Physics, AIP Publishing, 2021-03-14) [Article]
    Lasing is a well-established field in optics with several applications. Yet, having lasing or huge amplification in other wave systems remains an elusive goal. Here, we utilize the concept of coherent perfect absorber-laser to realize an acoustic analog of laser with a proven amplification of more than 10 4 in terms of the scattered acoustic signal at a frequency of a few kHz. The obtained acoustic laser (or the coherent perfect absorber-laser) is shown to possess extremely high sensitivity and figure of merit with regard to ultra-small variations of the pressure (density and compressibility) and suggests its evident potential to build future acoustic pressure devices such as precise sensors.
  • On Coding and Decoding Reconfigurable Radiation Pattern Modulation Symbols

    Celis Sierra, Sebastian; Farhat, Mohamed; Zhang, Li; Bagci, Hakan; Eltawil, Ahmed; Salama, Khaled N. (Electronics, MDPI AG, 2021-03-06) [Article]
    In this paper, we propose the theoretical framework for a reconfigurable radiation pattern modulation (RRPM) scheme, which is reminiscent of the index modulation technique. In the proposed scheme, information is encoded using far-field radiation patterns generated by a set of programmable radiating elements. A considerable effort has been invested to allow for high transmission of the reconfigurable radiation pattern symbols; yet, the receiving system has received little attention and has always been considered ideal. Depending on the number of receivers and their respective positions, two variables are considered here for data transmission: the sampling resolution and the fraction of the covered space by the receiving antennas. Hence, we quantitatively investigate their effect on the bit-error-rate (BER) by making use of a limited number of measurements that approximate the behavior of the system under real-field conditions.
  • A Wideband Magnetic Frequency Up-Converter Energy Harvester

    Fakeih, Esraa; Almansouri, Abdullah S.; Kosel, Jürgen; Younis, Mohammad I.; Salama, Khaled N. (Advanced Engineering Materials, Wiley, 2021-03-05) [Article]
    Many sensor applications require small and noninvasive methods of powering, such as marine animal tracking and implantable healthcare monitoring. In such cases, energy harvesting is a viable solution. Vibrational energy harvesting is abundantly available in the environment. These vibrations usually are low in frequency and amplitude. Conventional vibrational harvesters convert the environmental vibrations into electrical signals; however, they suffer from low-voltage outputs and narrow bandwidths, limiting the harvesting to a small range of frequencies. Herein, a new mechanical harvester is introduced using a magnetic frequency up-converter. It is implemented using attractive-force magnetic coupling between a soft magnet and a permanent magnet to convert low-frequency vibrations into high-frequency pulses. Combined with a piezoelectric generator, the harvester generates a high output voltage for an extended bandwidth of operation. The proposed harvester shows a 50.15% increase in output voltage at the resonant frequency (12.2 Hz), resulting in 14.79 V at 1.0 g, with a maximum peak voltage of 16.28 V. The bandwidth of operation ranges from 10.77 to 22.16 Hz (11.39 Hz), which when compared with a single-beam harvester shows an increase of 3250% in the bandwidth, where the average power is greater for 92.56% of this bandwidth.
  • Neural Coding in Spiking Neural Networks: A Comparative Study for Robust Neuromorphic Systems

    Guo, Wenzhe; Fouda, Mohammed Elneanaei; Eltawil, Ahmed; Salama, Khaled N. (Frontiers in Neuroscience, Frontiers Media SA, 2021-03-04) [Article]
    Various hypotheses of information representation in brain, referred to as neural codes, have been proposed to explain the information transmission between neurons. Neural coding plays an essential role in enabling the brain-inspired spiking neural networks (SNNs) to perform different tasks. To search for the best coding scheme, we performed an extensive comparative study on the impact and performance of four important neural coding schemes, namely, rate coding, time-to-first spike (TTFS) coding, phase coding, and burst coding. The comparative study was carried out using a biological 2-layer SNN trained with an unsupervised spike-timing-dependent plasticity (STDP) algorithm. Various aspects of network performance were considered, including classification accuracy, processing latency, synaptic operations (SOPs), hardware implementation, network compression efficacy, input and synaptic noise resilience, and synaptic fault tolerance. The classification tasks on Modified National Institute of Standards and Technology (MNIST) and Fashion-MNIST datasets were applied in our study. For hardware implementation, area and power consumption were estimated for these coding schemes, and the network compression efficacy was analyzed using pruning and quantization techniques. Different types of input noise and noise variations in the datasets were considered and applied. Furthermore, the robustness of each coding scheme to the non-ideality-induced synaptic noise and fault in analog neuromorphic systems was studied and compared. Our results show that TTFS coding is the best choice in achieving the highest computational performance with very low hardware implementation overhead. TTFS coding requires 4x/7.5x lower processing latency and 3.5x/6.5x fewer SOPs than rate coding during the training/inference process. Phase coding is the most resilient scheme to input noise. Burst coding offers the highest network compression efficacy and the best overall robustness to hardware non-idealities for both training and inference processes. The study presented in this paper reveals the design space created by the choice of each coding scheme, allowing designers to frame each scheme in terms of its strength and weakness given a designs’ constraints and considerations in neuromorphic systems.
  • Gold nanostructured laser-scribed graphene: A new electrochemical biosensing platform for potential point-of-care testing of disease biomarkers

    Rauf, Sakandar; Lahcen, Abdellatif Ait; Aljedaibi, Abdulrahman; Beduk, Tutku; Ilton de Oliveira Filho, José; Salama, Khaled N. (Biosensors and Bioelectronics, Elsevier BV, 2021-02-27) [Article]
    Improvements in the Laser-scribed graphene (LSG)-based electrodes are critical to overcoming limitations of bare LSG electrodes in terms of sensitivity, direct immobilization of detection probes for biosensor fabrication, and ease of integration with point-of-care (POC) devices. Herein, we introduce a new class of nanostructured gold modified LSG (LSG-AuNS) electrochemical sensing system comprising LSG-AuNS working electrode, LSG reference, and LSG counter electrode. LSG-AuNS electrodes are realized by electrodeposition of gold chloride (HAuCl4) solution, which gave ∼2-fold enhancement in sensitivity and electrocatalytic activity compared to bare LSG electrode and commercially available screen-printed gold electrode (SPAuE). We demonstrate LSG-AuNS electrochemical aptasensor for detecting human epidermal growth factor receptor 2 (Her-2) with a limit of detection (LOD) of 0.008 ng/mL and a linear range of 0.1-200 ng/mL. LSG-AuNS-aptasensor can easily detect different concentrations of Her-2 spiked in undiluted human serum. Finally, to show the LSG-AuNS sensor system's potential to develop POC biosensor devices, we integrated LSG-AuNS electrodes with a handheld electrochemical system operated using a custom-developed mobile application.
  • IMCA: An Efficient In-Memory Convolution Accelerator

    Yantir, Hasan Erdem; Eltawil, Ahmed; Salama, Khaled N. (IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Institute of Electrical and Electronics Engineers (IEEE), 2021-01-14) [Article]
    Traditional convolutional neural network (CNN) architectures suffer from two bottlenecks: computational complexity and memory access cost. In this study, an efficient in-memory convolution accelerator (IMCA) is proposed based on associative in-memory processing to alleviate these two problems directly. In the IMCA, the convolution operations are directly performed inside the memory as in-place operations. The proposed memory computational structure allows for a significant improvement in computational metrics, namely, TOPS/W. Furthermore, due to its unconventional computation style, the IMCA can take advantage of many potential opportunities, such as constant multiplication, bit-level sparsity, and dynamic approximate computing, which, while supported by traditional architectures, require extra overhead to exploit, thus reducing any potential gains. The proposed accelerator architecture exhibits a significant efficiency in terms of area and performance, achieving around 0.65 GOPS and 1.64 TOPS/W at 16-bit fixed-point precision with an area less than 0.25 mm².
  • Coating of Conducting and Insulating Threads with Porous MOF Particles through Langmuir-Blodgett Technique

    Rauf, Sakandar; Andrés, Miguel A.; Roubeau, Olivier; Gascón, Ignacio; Serre, Christian; Eddaoudi, Mohamed; Salama, Khaled N. (Nanomaterials, MDPI AG, 2021-01-10) [Article]
    The Langmuir-Blodgett (LB) method is a well-known deposition technique for the fabrication of ordered monolayer and multilayer thin films of nanomaterials onto different substrates that plays a critical role in the development of functional devices for various applications. This paper describes detailed studies about the best coating configuration for nanoparticles of a porous metal-organic framework (MOF) onto both insulating or conductive threads and nylon fiber. We design and fabricate customized polymethylmethacrylate sheets (PMMA) holders to deposit MOF layers onto the threads or fiber using the LB technique. Two different orientations, namely, horizontal and vertical, are used to deposit MIL-96(Al) monolayer films onto five different types of threads and nylon fiber. These studies show that LB film formation strongly depends on deposition orientation and the type of threads or fiber. Among all the samples tested, cotton thread and nylon fiber with vertical deposition show more homogenous monolayer coverage. In the case of conductive threads, the MOF particles tend to aggregate between the conductive thread’s fibers instead of forming a continuous monolayer coating. Our results show a significant contribution in terms of MOF monolayer deposition onto single fiber and threads that will contribute to the fabrication of single fiber or thread-based devices in the future.

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