ECE professor Kaustav Banerjee has been named co-recipient of the 2015 IEEE Kiyo Tomiyasu Award with Professor Vivek Subramanian of UC Berkeley
The Kiyo Tomiyasu Award is a Technical Field Award administered by the IEEE Awards Board covering all areas of the institute, and is one of the highest-level awards given by the IEEE.
The award recognizes outstanding early to mid-career contributions to technologies holding the promise of innovative applications. Banerjee received this award in recognition of his “contributions to nano-materials, devices, circuits, and CAD, enabling low-power and low-cost electronics”.
Banerjee’s visionary ideas and research into low-power electronics, including 3-dimensional ICs and thermal-aware IC design, have found wide scale implementation in the semiconductor industry. His research group has also spearheaded the use of low-dimensional nanomaterials such as carbon nanotubes, graphene and other 2D crystals for overcoming power dissipation and other fundamental challenges in nanoscale devices, interconnects and sensors.
Professor Xie recognized by the IEEE for his work with three-dimensional integrated circuits
We carry more computing power in our current smartphones than mission control had at its disposal when sending men to the moon in 1969 (They had a backup calculator, just in case!). Our handheld tablets and ebook readers can crunch numbers with more speed and ease than the first commercially available personal computer could, just over half a century ago. In 2015, a chip no bigger than a human fingertip can accomplish more than what 30 tons of computer could do back in 1946.
What’s responsible for this incredible shrinking computer phenomenon? Integrated circuits. The brains behind today’s modern devices, these are tiny components that relay and manipulate information and perform complex calculations in the blink of an eye. And it is for his work in the area of integrated circuits that Yuan Xie, professor of electrical and computer engineering, has been elected fellow by the Institute of Electrical and Electronics Engineers (IEEE).
“This well-deserved, prestigious recognition by his peers around the world is highly valued and much appreciated at UCSB,” said Rod Alferness, dean of the UCSB College of Engineering.
“It’s very exciting,” Xie said of the recognition that honors his “contributions to design automation and architecture of three-dimensional integrated circuits.”
In this talk, we show four laser demonstrations that use the hybrid silicon platform to lower phase noise due to spontaneous emission, based on the following two techniques, viz. confinement factor reduction and negative optical feedback. The first two demonstrations are of mode-locked lasers and the next two are of tunable lasers. Some of the key results include; (a) 14dB white frequency noise reduction of a 20GHz radio-frequency (RF) signal from a harmonically mode-locked long cavity laser with greater than 55dB supermode noise suppression, (b) 8dB white frequency noise reduction from a colliding pulse mode-locked laser by reducing the number of quantum wells and a further 6dB noise reduction using coherent photon seeding from long on-chip coupled cavity, (c) linewidth reduction of a tunable laser down to 160kHz using negative optical feedback from coupled ring resonator mirrors, and (d) linewidth reduction of a widely tunable laser down to 50kHz using on-chip coupled cavity feedback effect.
Next, we present the results of a reliability study conducted to investigate the influence of molecular wafer bonding between Si and InP on the lifetime of distributed feedback lasers, a common laser source used in optical communication. No degradation in lasing threshold or slope efficiency was observed after aging the lasers for 5000hrs at 70°C and 2500hrs at 85°C. However, among the three chosen bonding interface layer options, the devices with an interface superlattice layer showed a higher yield for lasers and lower dark current values in the on-chip monitor photodiodes after aging.
This work examines the efforts pursued to extend the bandwidth of InP-based DHBTs above 1 THz. Aggressive lithographic and epitaxial scaling of key device dimensions and simultaneous reduction of contact resistivities have enabled increased RF bandwidths by reduction of device RC and transit delays. A fabrication process for forming base electrodes and base/collector mesas of highly scaled transistors has been developed that exploits superior resolution (10nm) and alignment (<30nm) of electron beam lithography. Ultra-low resistance, thermally stable base contacts are critical for extended fmax bandwidth: a novel dual-deposition base metalization technique is presented that removes contaminating lithographic processes from the formation of the base contact, thereby enabling low resistivity contacts (4 Ω-µm²) to ultra-thin base layers (20 nm). The composite base metal stack exploits an ultra-thin layer of platinum that controllably reacts with base, yielding low contact resistivity, as well as a thick refractory diffusion barrier which permits stable operation at high current densities and elevated temperatures. Reduction in emitter-base surface leakage and subsequent increase of current gain was achieved by passivating emitter-base semiconductor surfaces with conformally grown ALD Al2O3. RF bandwidth limiting parasitics associated to the perimeter of highly scaled transistors have been identified and significantly reduced, among which are high sheet resistance of base electrodes, excess undercut of emitter stripes and improperly scaled base posts. At 100nm collector thickness , the breakdown voltage of the transistor BVCEO has been increased to more than 4.1V by passivating base/collector surfaces.
With the technology improvements discussed, transistors with ft of 480 GHz and fmax in excess of 1 THz have been demonstrated at 200nm emitter width and 80nm single-sided base contact width. Transistors at the same emitter width, but 30nm base contact width exhibit ft of 550 GHz and fmax of 850 GHz. Estimations from a finite element model predict higher bandwidth on smaller footprint transistors. However, inadequacies of RF calibration structures prevent fmax extraction on these devices.
The two UCSB Electrical and Computer Engineering alumni honored at the annual regional awards ceremony
Thien Nguyen received an award for Project of the Year for Autoliv’s Night Vision 3 System. Nguyen is the Aftermarket Project Manager at Autoliv Electronics.
Armando Veloz (Electrical Engineering, 1979) received an award for Engineer of the Year for his contributions to STEM education for local students. Veloz, with the Santa Barbara chapter of the Society of Hispanic Professional Engineers, conducts outreach engineering activities for students, kindergarten through college, including the UCSB MESA group. Veloz, who is a founding member of UCSB Los Ingenieros, is a Senior Electronics Engineer at Moog Space and Defense Group.
Wafer-bonding is a novel technique which enables realizations of heterostructures consisting of heteroepitaxy-incompatible materials with a large lattice mismatch. Since its discovery, wafer-bonding has continued to expand its impact in diverse applications related to the field of semiconductors — from silicon-on-insulator wafers to hybrid III-V/Si photonics to many more. Likewise, if high-quality wafer-bonded heterostructures with unique combinations of materials can be successfully demonstrated, it is evident that their implementation in electronic devices will result in several breakthroughs.
Acknowledging the potential of wafer-bonding in expanding the design space in the field of electronics, a concept of wafer-bonded transistor consisting of a III-As channel (with superior carrier transport properties) and III-N drain (with very high breakdown voltage) has been developed with the aim of simultaneously achieving both the high-frequency and high-power performances within a single device. The transistor design selected for the wafer-bonded heterojunctions of III-As/III-N is the current aperture vertical electron transistor (CAVET), from which the regrown AlGaN/GaN channel with a two-dimensional electron gas is substituted with a wafer-bonded InGaAs channel.
In light of the notable advantages offered from the N-polar III-N materials in wafer-bonded CAVETs (or BAVETs), all BAVETs fabricated and analyzed throughout this dissertation are based on the N-polar III-N. In comparison to the past Ga-polar BAVETs, the first functional N-polar BAVET showed a markedly higher current, but it exhibited most of the same problems observed from the Ga-polar BAVETs, such as the anomalously high saturation voltage, finite turn-on voltage, and high gate leakage. By performing elaborated series studies on the doping in the gate heterobarrier, thickness of the added InGaN interlayer, and gate electrode geometry, the abovementioned problems seen in the BAVETs could be better understood and addressed. Finally, in the latest generation BAVET designed with all of the key observations taken into account, the turn-on voltage, which has been a persistent problem observed from the majority of the functional wafer-bonded transistors studied so far, was successfully eliminated, thus showing promise in expanding the use of wafer-bonding into the field of electronic devices.
This dissertation work aspired to demonstrate that — with continued research efforts invested in this field — the extra degree of freedom in the materials design offered by wafer-bonding may enable realizations of cutting edge electronic devices in the future, hence expanding the design space that is currently bound by heteroepitaxy.
In the modernization of infrastructure systems spanning energy, transportation, and health we are seeing the convergence of big data analytics, cyber-physical systems, and the internet of things. The resulting societal-scale cyber-physical systems (S-CPS) provide new opportunities for efficiency yet expose novel vulnerabilities. In the energy systems, for example, the availability of streaming data from smart metering enables monetization of energy savings. These savings can be realized by employing novel variants of machine learning algorithms to generate energy analytics that allow customization of offerings to consumers and by creating the economic incentives necessary for investment in the instrumentation of physical infrastructure. On the other hand, these emerging service models depend on the underlying CPS infrastructure and thus, reveal new vulnerabilities due to ubiquitous sensing, real-time constraints, and ‘closing-the-loop’ attributes. This efficiency-vulnerability tradeoff is a fundamental challenge facing S-CPS, wherein scarce resources must be allocated amongst competitive agents with misaligned goals. To manage this tradeoff, a coordinator can provide incentives to align these goals, for instance, by ensuring the equilibrium behavior optimizes a societal cost.
In this talk, I present an algorithm for synthesizing incentive strategies that lead to efficient behavior when the preferences of the underlying agents are unknown to the coordinator and must be learned. In support of the incentive design and learning steps in the algorithm, I present an intrinsic characterization of Nash equilibria that is amenable to computation. This learning and mechanism design procedure aims to bridge the gap between the non-cooperative Nash equilibrium and a more efficient, perhaps socially optimal, solution. A coordinator can leverage the underlying CPS infrastructure to enhance system efficiency at the expense of revealing vulnerabilities. By focusing on the demand-side of the power grid, I provide tools for analysis of consumer privacy and the design of economic mechanisms for balancing the efficiency-vulnerability tradeoff. The combination of data-driven models and game-theoretic tools I present provides the foundation for a systems theory of S-CPS.
The next generation of complex engineered systems will see an unprecedented integration of electromechanical components, communication, and embedded computation. Imminent examples include self-driving vehicles, smart buildings, and UAVs for automated delivery of goods. It is critical that these new technologies be safe and efficient, as their failure would be socially and economically catastrophic.
This talk will focus on the challenge of integrating data-driven optimization algorithms into safety-critical control systems. The problem of selecting a suitable algorithm for use in large-scale optimization is currently more of an art than a science; a great deal of expertise is required to know which algorithms to apply and how to properly tune them. Moreover, there are seldom performance or robustness guarantees.
Our key observation is that iterative optimization algorithms may be viewed as discrete-time controllers, and the problem of algorithm selection/tuning may be viewed as a robust control problem. This viewpoint allows us to treat both electromechanical and algorithmic components in a unified manner. By solving simple semidefinite programs, we can derive robust bounds on convergence rates for popular algorithms such as the gradient method, proximal methods, fast/accelerated methods, and operator-splitting methods such as ADMM. Finally, our framework can be used to search for algorithms that meet desired performance guarantees, thus establishing a new and principled methodology for algorithm design. As an illustrative example, we synthesize a new family of first-order algorithms that explore the trade-off between performance and robustness to noise.
Imagine you are a brain-in-a-vat that wakes up connected to an unknown (robotic) body. You are connected to two streams of uninterpreted observations and commands. You have zero prior knowledge on the body morphology, its sensors, its actuators, and the external world. Would you be able to “bootstrap” a model of your body from scratch, in an unsupervised manner, and use it to perform useful tasks? This bootstrapping problem sits at the intersection of numerous scientific questions and engineering problems.Biology gives us a proof of existence of a solution, given that the neocortex demonstrates similar abilities.
I am interested in understanding whether the bootstrapping problem can be formalized to the point where it can be solved with the rigor of control theory. I will discuss a tractable subset of the set of all robots called the “Vehicles Universe”, which I consider a updated version, with modern sensors, of Braitenberg’s Vehicles. I will show that the dynamics of three “canonical” robotic sensors (camera, range-finder, field sampler) are very similar at the “sensel” level. I will present classes of models that can capture the dynamics of those sensors simultaneously and allow exactly the same agent to perform equivalent spatial tasks when embodied in different robots.
Schuller to use the award to study how light interacts with certain materials, particularly those with complex and asymmetric molecular arrangements, such as plastics.
“Getting the CAREER Award is a great honor,” said Schuller. “It’s a great validation for me and my work as a young researcher.”
The award, which amounts to $500,000 over five years, will allow Schuller and his research group to examine the interactions between light and possible alternative semiconducting materials. Whereas conventional photonic (light-manipulating) materials such as silicon crystals tend to exhibit uniform optical behaviors in all directions (isotropic), other materials, including plastics, have optical properties that differ by direction (anisotropic).
Schuller’s research group will focus on examining the complex optical properties of organic (carbon-based) materials such as plastics. Their findings could in turn lead to developments that could enhance the performance of organic photonic devices. Additionally, the research could open new doors to the manufacture of low-cost, lightweight and flexible semiconductors that can harness and manipulate light for various applications.