1,721,070 research outputs found
Dataset: Microstructured hybrid scaffolds for aligning neonatal rat ventricular myocytes
No full textThis dataset supports the paper:
Sanzari, I., Dinelli, F., Humphrey, E., Terracciano, C., Prodromakis, T., (2019)
Microstructured hybrid scaffolds for aligning neonatal rat ventricular myocytes Materials Science and Engineering C
DOI: https://doi.org/10.1016/j.msec.2019.109783</span
Dataset for Electrothermal deterioration factors in gold planar inductors designed for microscale bio-applications
No full textDatasets used in figures of the article "Electrothermal deterioration factors in gold planar inductors designed for microscale bio-applications" in Microelectronic Engineering journal. DOI:10.1016/j.mee.2018.05.006</span
High density crossbar arrays with sub- 15 nm single cells via liftoff process only
No full textEmerging nano-scale technologies are pushing the fabrication boundaries at their limits, for leveraging an even higher density of nano-devices towards reaching 4F2/cell footprint in 3D arrays. Here, we study the liftoff process limits to achieve extreme dense nanowires while ensuring preservation of thin film quality. The proposed method is optimized for attaining a multiple layer fabrication to reliably achieve 3D nano-device stacks of 32?×?32 nanowire arrays across 6-inch wafer, using electron beam lithography at 100?kV and polymethyl methacrylate (PMMA) resist at different thicknesses. The resist thickness and its geometric profile after development were identified to be the major limiting factors, and suggestions for addressing these issues are provided. Multiple layers were successfully achieved to fabricate arrays of 1 Ki cells that have sub- 15?nm nanowires distant by 28?nm across 6-inch wafer
Challenges hindering memristive neuromorphic hardware from going mainstream
No full textMemristive devices have elicited intense research in the past decade thanks to their inherent low voltage operation, multi-bit storage and cost-effective manufacturability. Nonetheless, several outstanding performance and manufacturability challenges have prevented the widespread industry adoption of redox-based memristive matrices. Here, we discuss these challenges in terms of key metrics and propose a roadmap towards realizing competitive memristive-based neuromorphic processing systems.</p
Dataset for the article: "Measured Behaviour of a Memristor-Based Tuneable Instrumentation Amplifier"
No full textThe excel file includes the measured data used for generating the Fig 2 to 5 in the paper 'Measured Behaviour of a Memristor-Based Tuneable Instrumentation Amplifier'.
The PNG file inclues the Fig 2 to 5 in the paper which were generated based on the data in the excel file. The figures are as follows:
Fig2. Impedance-frequency function of TiOx/Al2O3 10×10µm2 memristor devices.
Fig3. Gain response of the instrumentation amplifier for a set of memristor resistances and a based line given by 30kΩ discrete resistor.
Fig4. THD+N of the instrumentation amplifier with input signal amplitude from 30mV to 300mV.
Fig5. THD+N of the instrumentation amplifier uses 3 memristors compare with uses 1 memristor.</span
Dataset for article "UV Induced Resistive Switching in Hybrid Polymer Metal Oxide Memristors"
No full textDataset supports the article 'UV Induced Resistive Switching in Hybrid Polymer Metal Oxide Memristors' published in Scientific Reports.</span
Dataset in support of the Southampton doctoral thesis 'Ultra-Fine Signal Classification Using Memristor-Enabled Hardware'
No full textThe data is in the form of .csv file, created from Cadence Virtuoso. They correspond to three circuits simulation results in the doctoral thesis 'Ultra-Fine Signal Classification Using Memristor-Enabled Hardware'.</span
UV induced resistive switching in hybrid polymer metal oxide memristors
No full textThere is an increasing interest for alternative ways to program memristive devices to arbitrary resistive levels. Among them, light-controlled programming approach, where optical input is used to improve or to promote the resistive switching, has drawn particular attention. Here, we present a straight-forward method to induce resistive switching to a memristive device, introducing a new version of a metal-oxide memristive architecture coupled with a UV-sensitive hybrid top electrode obtained through direct surface treatment with PEDOT:PSS of an established resistive random access memory (RRAM) platform. UV-illumination ultimately results to resistive switching, without involving any additional stimulation, and a relation between the switching magnitude and the applied wavelength is depicted. Overall, the system and method presented showcase a promising proof-of-concept for granting an exclusively light-triggered resistive switching to memristive devices irrespectively of the structure and materials comprising their main core, and, in perspective can be considered for functional integrations optical-induced sensing
Ultra-fine signal classification using memristor-enabled hardware
No full textNeural activity recording system promotes the development of diagnostic and therapeutic programs and neuroscience research. Direct recordings of neural signals from the brain have helped scientists access to study and unlock the secrets of neural coding gradually. This can be realised by applying implantable neural recording systems to monitor and record neural signals. Then, the neural information can be transmitted to the external device for processing, storage or application. However, the power consumption of the neural recording system is the primary constraint to monitoring large groups of neurons. It leads the development of neural recording systems in two directions: 'high-channel-count but wired' and 'wireless but low-channel-count'. To address the power issue, we proposed a neural front-end that aims to detect neural spikes by thresholding and output as one-bit digital data so that the afterwards processing can only work on spikes rather than processing all the data points. The most significant feature is that we induce memristors as trimming devices to tune the threshold voltage for spike detection.Meanwhile, it contributes to rejecting up to 50mV DC offset from electrodes. The measurement presents that the memristor-based pre-amplifier is capable of achieving above 95% spike detection accuracy with hundreds of nanowatt power consumption per channel. This design indicates a promising approach to conduct spike-detection on-chip with low power consumption and demonstrates the potential of a hybrid memristor/CMOS circuit for power-efficient large-scale neural interfacing application
An analogue-domain, switch-capacitor-based arithmetic-logic unit
No full textThe continuous maturation of novel nanoelectronic devices exhibiting finely tuneable resistive switching is rekindling interest in analogue-domain computation. Regardless of domain, a useful computational module is the arithmetic-logic unit (ALU), which is capable of performing one or more fundamental mathematical operations (typical example: addition and subtraction). In this work we report on a design for an analogue ALU (aAL U) capable of performing barrel addition and subtraction (i.e. ADD/SUB in modular arithmetic). The circuit only requires 5 minimum-size transistors and 1 capacitor. We show that our aALU is in principle capable of handling 5 bits of information using a single input/output wire. Core power dissipation per operation is estimated to peak at ~ 59 f J (input operand-dependent) in TSMC's 65 nm technology.</p
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