Assessment of thermal instabilities and oscillations in multifinger heterojunction bipolar transistors through a harmonic-balance-based CAD-oriented dynamic stability analysis technique

We present a novel analysis of thermal instabilities and oscillations in multifinger heterojunction bipolar transistors (HBTs), based on a harmonic-balance computer-aided-design (CAD)-oriented approach to the dynamic stability assessment. The stability analysis is carried out in time-periodic dynamic conditions by calculating the Floquet multipliers of the limit cycle representing the HBT working point. Such a computation is performed directly in the frequency domain, on the basis of the Jacobian of the harmonic-balance problem yielding the limit cycle. The corresponding stability assessment is rigorous, and the efficient calculation method makes it readily implementable in CAD tools, thus allowing for circuit and device optimization. Results on three- and four-finger layouts are presented, including closed-form oscillation criteria for two-finger device

Efficient spectral domain technique for the frequency locking analysis of nonlinear oscillators

After discussing an implementation of the harmonic balance technique that enables the efficient determination of the limit cycles for a nonlinear autonomous dynamical system, we consider the frequency locking of a set of oscillators that is studied by means of a proper extension of the aforementioned approach. Harmonic balance is also used for the numerical computation of the Floquet exponents and eigenvectors of the frequency locked limit cycle, thus enabling the assessment of its stability properties. The proposed technique is applied to the study of the frequency locking properties of a set of coupled Chua’s oscillators as a function of several parameters

Dry turning of alumina/aluminum composites with CVD diamond coated Co-cemented tungsten carbide tools

Triangular (TPGN 160308) WC-6 wt.%Co inserts having different average grain sizes (1 and 3 µm) were submitted to surface roughening either by wet etching with Murakami's reagent or by a heat treatment in the hot filament chemical vapour deposition (HFCVD) reactor. The heat treatment was performed in a monohydrogen-rich atmosphere at substrate temperatures as high as 1000 degrees C. Scanning electron microscopy and energy-dispersive spectroscopy showed that this pre-treatment led to surface roughening of the as-ground inserts and to a lower surface Co concentration. Prior to deposition, all inserts were etched with an acid solution of hydrogen peroxide. Diamond coatings were deposited by HFCVD. The coated inserts were tested by dry machining of aluminum-matrix composite (Al-10%Al2O3) bars. Turning test results indicated that a proper combination of substrate pretreatment and microstructure can significantly improve tool life

Memcomputing NP-complete problems in polynomial time using polynomial resources and collective states

Memcomputing is a novel non-Turing paradigm of computation that uses interacting memory cells (memprocessors for short) to store and process information on the same physical platform. It was recently proven mathematically that memcomputing machines have the same computational power of nondeterministic Turing machines. Therefore, they can solve NP-complete problems in polynomial time and, using the appropriate architecture, with resources that only grow polynomially with the input size. The reason for this computational power stems from properties inspired by the brain and shared by any universal memcomputing machine, in particular intrinsic parallelism and information overhead, namely, the capability of compressing information in the collective state of the memprocessor network. We show an experimental demonstration of an actual memcomputing architecture that solves the NP-complete version of the subset sum problem in only one step and is composed of a number of memprocessors that scales linearly with the size of the problem. We have fabricated this architecture using standard microelectronic technology so that it can be easily realized in any laboratory setting. Although the particular machine presented here is eventually limited by noise—and will thus require error-correcting codes to scale to an arbitrary number of memprocessors—it represents the first proof of concept of a machine capable of working with the collective state of interacting memory cells, unlike the present-day single-state machines built using the von Neumann architecture

Strontium and iron-doped barium cobaltite prepared by solution combustion synthesis: exploring a mixed-fuel approach for tailored intermediate temperature solid oxide fuel cell cathode materials

Ba0.5Sr0.5Co0.8Fe0.2O3–δ (BSCF) powders were prepared by solution combustion synthesis using single and double fuels. The effect of the fuel mixture on the main properties of this well-known solid oxide fuel cell cathode material with high oxygen ion and electronic conduction was investigated in detail. Results showed that the fuel mixture significantly affected the area-specific resistance of the BSCF cathode materials, by controlling the oxygen deficiency and stabilizing the Co2+ oxidation state. It was demonstrated that high fuel-to-metal cations molar ratios and high reducing power of the combustion fuel mixture are mainly responsible for the decreasing of the area-specific resistance of BSCF cathode materials. Moreover, a new metastable monoclinic phase with Ba0.5Sr0.5CO3 composition was discovered in the as-burned BSCF powders, enlarging the existing information on the BSCF phase formation mechanis