The deffect effect on electronic conductance in binomially tailored quantum wire

The paper considers the effect of the defects on the electronic transmission properties in binomially tailored waveguide quantum wires, in which each Dirac delta function potential strength have been weight on the binomial distribution law. We have assumed that a single free-electron channel is incident on the structure and the scattering of electrons is solely from the geometric nature of the problem. We have used the transfer matrix method to study the electron transmission. We found this novel structure has a good defect tolerance. We found the structure tolerate up to in strength defect and in position defect for the central Dirac delta function in the binomial distribution. Also, we found this structure can tolerate both defect up to in strength and in position dislocationComment: Submitted on behalf of TIMA Editions (http://irevues.inist.fr/tima-editions

Nanocarbon Devices and Sensors

Nanocarbon materials have the potential to substitute the silicon in devices that are needed to further improve in terms of scalability, speed of operation, and performance. Therefore, carbon nanotubes and graphene - allotropes with outstanding properties have been intensively explored over the years. This thesis contributes to the synthesis of nanocarbon materials and its use as sensing and transistor material by focusing on the topics: hysteresis in carbon nanotube field-effect transistors, selective molecule sensing with graphene field-effect transistors, and sensing applications in nanocrystalline graphene. Hysteresis in carbon nanotube transistors has limited its utility in large-scale device implementation. The issue of hysteresis in such device structures is addressed. A hysteresis-free device operation is achieved by packaging the carbon nanotube field-effect transistors between hexagonal boron nitride and a hydrophobic polymer Teflon. The findings indicate that hysteresis is eradicated only if the metal-carbon nanotube contacts along with the tubes are completely encapsulated with Teflon. The time dependence of reducing hysteresis for encapsulated devices indicates out-diffusion of water molecules adsorbed at the metal-nanotube contacts. Graphene field-effect transistors suffer the issue of selectivity applications. A novel sensor based on graphene field-effect transistor and surface-mounted metal-organic frameworks is demonstrated. The sensor shows sensitivity and selectivity to ethanol molecules by the shift in Dirac voltage of graphene and is insensitive to other alcohols like methanol and isopropanol, and molecules like CO2, H2O, H2. The device performance shows a detection limit of 100 ppm levels. This class of sensors is tailorable and opens up a completely new range of sensors. Nanocrystalline graphene is an interesting material for several sensing applications like strain sensing, moisture sensing, gas sensing, etc. In order to be investigated as strain sensor, thin films should be either grown or transferred on flexible substrates. This motivated the study of the low-temperature synthesis (600°C) process using a metal capping layer over a carbon source. Raman spectroscopy is used to characterize the grown films. The results indicate this technique promising for a low-temperature NCG synthesis. Next, thin-film transfer technique on flexible substrate is studied. The quality of transferred films on different substrates is confirmed by atomic force microscopy. Next, influence of temperature on conductivity of thin films of NCG is investigated. Piezoresistive property of nanocrystalline graphene is explored based on changes in sheet resistance of the film and Raman spectroscopy. Finally, a potential application is demonstrated where a top (ionic liquid) gate field effect configuration of NCG works as a moisture sensor

Magnetometric techniques for the measurement of initial susceptibility and for non-contact sensing of displacement

PhD ThesisPart 1 of the thesis describes a new instrument that simultaneously measures the real magnetic susceptibility X' and the imaginary magnetic susceptibility X". The instrument measures the temperature dependences of X' and X" in rock samples between 16°C and 800°C; natural developments are working down to -200°C and measuring the anisotropy of susceptibility. The instrument's heart is a tuned circuit driven at its natural frequency by a 5MHz crystal oscillator. The tuned circuit's inductance is a sample coil that encloses-a furnace. The random noise level in the signal for X' is 7.4 x l0-13 m3 r. m. s., the noise level in the signal for X" is 2x 10 ^12 m3 r. m. s. Sample volumes are 0.1 cm3 or less. Equations describing the instrument are derived and verified, particular attention is paid to the sample coil. Circuit diagrams are included. Some results are presented and equations that broadly describe the observed temperature dependences of X' and X" are developed. Some methods for substantially improving the instrument's performance are outlined. Part 2 of the thesis describes a new method for non-contact sensing of displacement. A magnet is mounted on the object whose displacement is to be measured. The magnet's field is sensed and fed to a 6502 microprocessor programmed to display the distance between the magnet and the sensor; intervening barriers with a permeability very close to unity do not affect the readings. The accuracy is better than 2.0% of full scale deflection (FSD) over the useful range of 250 mm and better than 0.1% FSD over a range of 110 mm. The magnet's volume is 4.00 mm3 and the moment is 3.1 x 10-7 Vbm. Circuit diagrams are presented and a complete software listing is included, the design will work with any magnet and magnetometer. There are directions for greatly improving the instrument's performance.Natural Environment Research Council

Towards A Non-Destructive Single Molecular Ion State Readout And Rotational Inelastic Collisions Between Molecular Nitrogen Ions and Argon Atoms

Precision spectroscopy on narrow dipole-forbidden transitions in trapped ultra-cold ions can be used to investigate a possible time-variation of fundamental constants like the fine-structure constant or the proton-to-electron mass ratio. For the investigation of the proton-to-electron mass ratio, molecular ions, like N+2, can possibly offer a higher precision than atomic ions. But due to the lack of closed-cycling transitions in most molecular and many atomic ions, the state detection of these ions remains challenging and often destructive readout techniques have to be employed. In recent years, various techniques to overcome these limitations were proposed and some experimentally demonstrated. These techniques make use of the shared motion of the spectroscopic ion and a co-trapped laser-coolable atomic ion to couple the two ions dependent on the internal state of the spectroscopic ion and determine the state via the co-trapped ion. Here, a simple and robust non-destructive state readout technique for ultra-cold co-trapped N+2 ions based on exciting the shared motion of the ground-state cooled two-ion system by the optical dipole force of an off-resonant optical lattice is presented. The properties and behavior of this non-destructive readout are investigated theoretically and possible implementations and transitions in N+2 are evaluated. In a second step, the properties of this non-destructive state readout scheme were characterized on laser-cooled Ca+ ions and a first trial on single N+2 ions was attempted. Tough designed for N+2 , the technique presented in here can be easily adopted for other ions lacking closed-cycling transition as well. Moreover, the rotational inelastic collision rate between cold N+2 ions in the vibrational ground state and neutral Ar atoms was experimentally re-investigated in this thesis. Recent theoretical studies indicated that the rate of these inelastic collisions could be larger than previously measured. Therefore, the inelastic collision rate wit Ar was re-investigated using trapped and sympathetically cooled N+2 ions

LIPIcs, Volume 261, ICALP 2023, Complete Volume

LIPIcs, Volume 261, ICALP 2023, Complete Volum

CIRCUITS AND ARCHITECTURE FOR BIO-INSPIRED AI ACCELERATORS

Technological advances in microelectronics envisioned through Moore’s law have led to powerful processors that can handle complex and computationally intensive tasks. Nonetheless, these advancements through technology scaling have come at an unfavorable cost of significantly larger power consumption, which has posed challenges for data processing centers and computers at scale. Moreover, with the emergence of mobile computing platforms constrained by power and bandwidth for distributed computing, the necessity for more energy-efficient scalable local processing has become more significant. Unconventional Compute-in-Memory architectures such as the analog winner-takes-all associative-memory and the Charge-Injection Device processor have been proposed as alternatives. Unconventional charge-based computation has been employed for neural network accelerators in the past, where impressive energy efficiency per operation has been attained in 1-bit vector-vector multiplications, and in recent work, multi-bit vector-vector multiplications. In the latter, computation was carried out by counting quanta of charge at the thermal noise limit, using packets of about 1000 electrons. These systems are neither analog nor digital in the traditional sense but employ mixed-signal circuits to count the packets of charge and hence we call them Quasi-Digital. By amortizing the energy costs of the mixed-signal encoding/decoding over compute-vectors with many elements, high energy efficiencies can be achieved. In this dissertation, I present a design framework for AI accelerators using scalable compute-in-memory architectures. On the device level, two primitive elements are designed and characterized as target computational technologies: (i) a multilevel non-volatile cell and (ii) a pseudo Dynamic Random-Access Memory (pseudo-DRAM) bit-cell. At the level of circuit description, compute-in-memory crossbars and mixed-signal circuits were designed, allowing seamless connectivity to digital controllers. At the level of data representation, both binary and stochastic-unary coding are used to compute Vector-Vector Multiplications (VMMs) at the array level. Finally, on the architectural level, two AI accelerator for data-center processing and edge computing are discussed. Both designs are scalable multi-core Systems-on-Chip (SoCs), where vector-processor arrays are tiled on a 2-layer Network-on-Chip (NoC), enabling neighbor communication and flexible compute vs. memory trade-off. General purpose Arm/RISCV co-processors provide adequate bootstrapping and system-housekeeping and a high-speed interface fabric facilitates Input/Output to main memory

Electronic conductance in binomially tailored quantum wire

We have studied the electronic transmission properties through binomially tailored waveguide quantum wires with Dirac delta function potentials. The potential's strength is weighted according to the binomial distribution law. We have assumed that single free-electron channel is incident on the structure and the scattering of electrons is solely from the geometric nature of the problem. We have used the transfer matrix method to study the electron transmission. We found that this structure pattern allows us to have well-defined allowed conduction bands due to transmission resonance. We also found that the electronic conductance spectrum depends on the number of the Dirac delta function potential in the quantum wire. When the number of Dirac delta function potentials in the structure and their strengths are increased, both well-defined conductance bands and sharper and narrower forbidden bands are formed