Lin Zhu, Ph.D. - US grants

Enrollment in online courses in the United States has been growing substantially faster than the overall higher education enrollment. Almost 3.9 million students were taking at least one online course during the Fall 2007 term. This represents 21.9% of the total enrollment in Fall 2007, up from 9.9% in Fall 2002. Over 80% of the 3.9 million students are studying at the undergraduate level. Public institutions and community colleges have seen the highest rate of increase in online courses including the science disciplines with the exception of engineering. In order to reach all students taking undergraduate science courses, efforts need to focus on creating a variety of effective cyberlearning environments.
Intellectual Merit: This project is producing and studying the tools and conditions required for enhanced cyberlearning through Peer-Led Team Learning (PLTL). The project investigates how technology can be used to enhance an educational strategy that already has proven beneficial in STEM courses. To accomplish this goal, the project is creating a cyber PLTL (cPLTL), an online collaborative environment for conducting PLTL Workshops; studying the effectiveness of a cPLTL environment in duplicating the proven benefits of the traditional, face-to-face PLTL method; examining the effectiveness of the existing PLTL materials in cPLTL Workshops; modifying the existing training course for the peer leaders to be effective facilitators in the cPLTL model; developing brief technology training for students learning chemistry in cPLTL workshops; and articulating the critical components vital to successful implementation of a cPLTL program. An evaluation is gathering data on the process of development and implementation of cPLTL. The evaluation also includes a quasi-experimental study of how cPLTL compares to traditional PLTL sections that are taught at the same time.
Broader Impacts: cPLTL has the potential to increase participation and retention of underrepresented groups in the STEM fields by providing active learning and leadership opportunities to a more diverse group of students in a flexible time frame. Also, cPLTL has the potential to strengthen the ability of community colleges to recruit students, who typically leave the institution after the sophomore year, to serve as peer leaders. In addition, if successful, cPLTL implementation will encourage adoption by other chemistry courses, STEM disciplines, and institutions, especially those with large non-traditional and commuter student populations. While research on cPLTL is not within the scope of this project, other complementary projects are probing a number of research questions. The cPLTL environment allows data collection on student interactions by capturing chat sessions, written collaboration, voice recordings, and video. This captured and saved data allows for research on student interactions in cPLTL, which has not been possible at this level of detail in face-to-face PLTL Workshops.

The objective of this program is to create a highly integrated sensor system through hybrid integration of passive plasmonic interferometers and Si waveguide array coupled active optoelectronic devices on a single microfluidic chip for low cost, real-time, label-free, lens-free, and multiplexed sensing applications. The proposed device provides a compact and portable sensing solution for point-of-care diagnostics that does not currently exist but is critical for overcoming size and cost barriers of conventional angular-tunable, prism-based surface plasmon resonance systems.

The intellectual merit is to integrate chip-scale semiconductor light sources and detectors with plasmonic sensors on a single chip so that light does not need to be coupled into/out of the sensors for analysis. Vertical plasmonic interferometers will perform the sensing function through intensity interrogation at a single wavelength. Curved silicon waveguides are proposed to interconnect active optoelectronic devices and plasmonic interferometers and enhance the sensor performance by preventing uncoupled light from entering the detector. Novel methods to obtain on-chip cancellation of temperature-induced signal drift will also be investigated.

The broader impacts are to investigate chip-scale all-in-one sensor platforms and integrate research and education. The outcome of the proposed research will have enormous long-term impacts on biosensing, health care and the national needs. The main goals of the education and outreach program are to enhance the PIs? undergraduate laboratory courses, improve the participation of graduate and undergraduate students in cutting-edge research in nanophotonics and biophotonics, and provide opportunities for under-represented groups in science, technology, engineering, and mathematics disciplines.

Objective: The objective of this program is to control optical gradient forces in lightwave circuits through waveguide dispersion, to enhance optical gradient forces by using plasmonic effects, and to create novel resonant optomechanical devices. Optical gradient forces can be generated between integrated optical components by light and be used to control both optical and mechanical behavior of these components. The resulting integrated optomechanical devices provide a fascinating system to study the coupling between optics and mechanics.

Intellectual merit: The intellectual merit is to investigate new methods, such as waveguide dispersion and plasmonic effects, to manipulate and enhance optical gradient forces and explore novel applications. Non-resonant optomechanical systems consisting of coupled waveguides with very different dispersion properties will be used to control optical gradient forces through wavelength and polarization. Hybrid plasmonic waveguides are proposed to enhance optical forces through stronger evanescent fields and larger field gradients.

Broader impacts: The broader impacts are to create novel devices for information processing and fundamental physics. The outcome of the proposed research will have significant impacts across many disciplines, such as light-controlled biomechanical manipulation and detection, photonic information processing, and strong light-matter interactions. The proposed education program will augment students? classroom instruction through an education plan that will integrate research activities and an outreach plan that will disseminate this research to local K-12 students. The education and outreach activities include establishing an interdisciplinary research program, developing undergraduate research experiences, and promoting participation of under-represented students.

Objective: The objective of this program is to design, fabricate, and characterize a new class of coupled optomechanical resonators and arrays. The photon-phonon interaction in chip-scale optomechanical cavities has been the subject of recent research as they can be used to create integrated hybrid optical/mechanical/quantum information processing systems. This project will investigate coupled optomechanical resonators and arrays with complex composite resonance functions.

Intellectual merit: The intellectual merit is to use the coupled optical resonance to coherently control and enhance optomechanical interactions in a chip-scale platform. In the strong coupling regime of the coupled optomechanical resonator system, the split optical resonances will be matched to the optical driving field and one of its motion sidebands, to enhance optomechanical interactions. In the weak coupling regime, opposite optical forces induced by the phase shift in separate resonators will be used to simultaneously cool one mechanical resonator and heat the other to obtain optically-controlled mechanical energy transfers.

Broader impacts: The broader impacts are to create signal processing and sensing platforms by using the versatile information processing capability and extremely high displacement sensitivity provided by coupled optomechanical resonators and arrays. This program will fund a full time graduate student and engage undergraduate students in focused sub-projects related to the proposed research through building Creative Inquiry teams and providing REU research opportunities. An extensive outreach effort is proposed, including a summer internship program for both undergraduate and high school students and a science workshop for high school teachers.

As a critical underpinning of modern society, the electric power grid is one of the most complex and man-made dynamic systems in the world. Numerous real-time data of different types, different components, and various locations are generated to monitor and control power grids. Currently, the control of large-scale power grids is still mainly based on the physical system model, while the hidden knowledge in the abovementioned large-volume data has not been fully exploited. This project selects one typical control function in smart grids, low-frequency oscillation control, to explore the potential to enhance smart grid controls using the hidden knowledge.
Low-frequency oscillation is a common phenomenon in operation of large-scale power systems. If not controlled properly, these oscillations may degrade power system security and make a large number of customers lose their power. This project aims at developing an intelligent controller to mitigate these low-frequency oscillations using data and machine learning technologies. If successful, it will advance the technology in smart grid, and remove obstacles for application of machine learning technologies in smart grid control. The proposed approach will contribute to more secure, reliable and economic operations of U.S. power grids. For example, the risk of blackout can be significantly mitigated; and thus outage cost could be saved, e.g., more than $1 billion for U.S. western grid collapse in 1996. The proposed project is also coupled with a broad dissemination of research findings and a strong educational component to engage students from underrepresented groups.

The proposed research effort focuses on a completely new design methodology of intelligent oscillation damping control using the data-driven models. These data-driven models of power grids derive from synchronized measurement data using machine learning technologies, in conjunction with power grid domain knowledge. Specifically, this project will: (1) build a self-evolving dynamic knowledge base based on historical measurement data under different oscillation scenarios; (2) extract the critical features from historical and real-time data, and select the optimal features to improve data-driven model prediction accuracy; (3) develop machine learning algorithms to predict data-driven models for oscillation damping control design; and (4) validate and demonstrate the proposed methodology via computer simulations and hardware testbed experiments. This advanced approach will contribute to the energy security and efficiency of the U.S. electric power grids. This project will expose both undergraduate and graduate students to the state-of-the-art machine learning education and workforce training program. By coordinating with an established outreach program in an existing NSF/DOE engineering research center, the research results will be integrated into weekly seminars and short courses that are accessible to four partner universities, nine affiliate universities and more than 35 industry partners. Moreover, this project will encourage students to get involved with STEM (Science, Technology, Engineering and Mathematics) courses early in their pre-college years to prepare for STEM careers.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Although targeting the ubiquitin-proteasome pathway by proteasome inhibitors, e.g. bortezomib (BTZ), is considered a targeted anticancer approach, its applications are hampered by poor drug solubility, low tumor specificity, drug resistance, side effects, and unsatisfying efficacy toward solid tumors. The current attempts, including the design of new proteasome inhibitors and drug delivery systems, focused mainly on improving drug bioavailability, but failed to address other important issues. Folate receptors (FRs) are overexpressed on many cancer cells as the major mechanism supportive of rapid cell growth, providing the rationale for the development of FR-targeted therapeutics. Unfortunately, some normal cells also express FRs, increasing the risk of off-tumor toxicity. The cancer targetability of these therapeutics has to be further improved. The matrix metalloproteinase 2 (MMP2) upregulation is highly associated with cancer growth, invasion and metastasis and emerged recently as a stimulus for the tumor-targeted drug delivery. To deal with the aforementioned issues of BTZ, in this application, a novel micellar nanopreparation is proposed, which contains a FR-targeted small-molecule drug conjugate (FA-Cat-BTZ) and an MMP2-sensitive self-assembling polymer (PEG2k-pp-PE). In the design, the MMP2-sensitive FR-targeting will improve the BTZ?s tumor specificity. In the tumor, the upregulated MMP2 will deshield the PEG layer and collapse the micellar nanoparticles, leading to the rapid release of FA-Cat-BTZ. Then, the released FA-Cat-BTZ will bind to the FRs on cancer cells for endocytosis. Therefore, this system undergoes the ?two-stage? transition from a nanoparticle to a small molecule, which will satisfy the nanoparticles? tumor accumulation, small molecules? tissue penetration, and cancer cell-specific drug uptake. Additionally, PEG2k-pp-PE possesses the capability of overcoming the efflux-mediated drug resistance. As a result, the novel strategy will maximize BTZ?s anticancer activity, overcome drug resistance, and minimize side effects. The major goals of this proposal are to preclinically evaluate the strategy and gather the essential information/data for future clinical translation. Three specific aims are proposed: (i) Prepare and optimize the micelles; (ii) Evaluate the combinatorial effects of PEG2k-pp-PE and FA-Cat-BTZ; and (iii) Evaluate the in vivo tumor targeting and anticancer activity. The proposal is driven by the need to broaden the anticancer spectrum and improve the efficacy of proteasome inhibitors, and to develop a strategy that can be a stepping stone towards attaining the ultimate goal of cancer-specific drug delivery. This study will be the first exploration of the dual (MMP2 and FR) targeted delivery of targeted therapeutics to the solid tumor and the novel combination regimen (proteasome inhibitor and efflux inhibitor) for treating drug-resistant cancers. The positive findings from this study are expected to be translated into potential clinical progress. This AREA grant will also strengthen the research environment in the College of Pharmacy at TAMHSC and provide more research opportunities for PharmD, graduate, and undergraduate students.

RAISE-EQuIP: A high-speed, reconfigurable, fully integrated circuit platform for quantum photonic applications

Quantum photonics utilizes the intriguing quantum characteristics of photons for information processing. Fast manipulation and transformation of photonic quantum states at a high speed underlie crucially the capability and capacity of quantum communication and computing. However, to date, it remains an open challenge to do so, which becomes a bottleneck for the speedup of photonic quantum information processing. On the other hand, current integrated quantum photonic circuits rely seriously on external off-chip laser sources for proper operation, which becomes a major obstacle limiting the integration and miniaturization of quantum photonic circuits which in turn limits the degree of functional complexity they can offer. The proposed research aims to address these challenges. With the synergetic research effort of our team, we propose to focus on innovative circuit- and system-level engineering to build large-scale fully-integrated quantum photonic circuit systems that can be flexibly reconfigured and modulated at high speed, aiming to achieve novel quantum functionalities with unprecedented functional complexity inaccessible to other means.
The proposed research covers all three thrusts of the EQuIP program. With our proposed research, we envision an entirely transformative avenue towards integrated quantum photonics that may ultimately revolutionize the state of the art of communication and information processing, advancing its maturity level towards practical implementation that would have significant impact on industrial sectors. The proposed research offers comprehensive training in the diverse interdisciplinary areas of quantum and integrated photonics, high-speed RF circuitry, electronic circuit design, lasers, and signal processing, to prepare workforces for future quantum engineering industry. It will also result in promoting the interest and participation of K-12 students and broadening the participations from underrepresented groups, through outreach programs.

The proposed research aims to explore and develop high-speed, flexibly reconfigurable, fully integrated quantum photonic circuits that offer unprecedented capability of manipulating, translating, and transducing photonic quantum states, encoding/decoding and processing quantum information. To this end, we have assembled a multidisciplinary team of leading experts with strong expertise and extensive experience in quantum photonics, nanophotonics, optoelectronic integration, high-speed RF circuitry, electronic IC design, semiconductor lasers, hybrid optoelectronic integration, to propose a fundamental research effort directed at the realization of scalable high-speed hybrid quantum photonic circuit systems that perform significantly beyond the reach of single individual components. The proposed research will integrate elegantly the outstanding and unique properties of underlying material platforms with innovative circuit and system design and engineering and laser-chip integration to realize very high speed modulation, tuning, and reconfiguration of large-scale integrated quantum photonic circuits that would enable novel quantum photonic functionalities with unprecedented functional complexity and capability. The preliminary results show great promise to achieve these goals. The strong expertise and extensive experiences of our team position us uniquely for the proposed research project.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Quantum computers are expected to revolutionize the future of science and technology by solving complex problems that are beyond the reach of current classical supercomputers. So far, several physical platforms have been demonstrated as prototypes for implementation of universal quantum processors. Each physical implementation holds specific benefits in demonstrating coherent manipulation of quantum state while suffering downfalls that prevent their scalable integration. Many quantum computing tasks would benefit enormously from the ability to coherently connect those physically distinct information processing platforms. One such application is quantum random access memory (QRAM), a key component in many well-known quantum algorithms that allows stored data to be extracted in quantum superposition. This research develops a hybrid QRAM device composed of superconducting qubits and high-quality acoustic cavities joined together by highly tunable interconnects. The team will draw on their expertise in materials science, nanofabrication, quantum device physics, and quantum information theory to construct and optimize this device. This project entails integrated research, education, and outreach efforts that encourage full participation of underrepresented groups in quantum science and technology, including summer camps for K-12 students and teachers, course and outreach material development, undergraduate and graduate research and advising, and postdoc mentoring.

Although QRAM is central to many important applications such as Grover’s search algorithm and solving linear systems of equations on a quantum computer, its experimental implementation has remained elusive. This is due to challenges in building a system that offers both a high-quality multi-mode quantum memory and a high degree of controllability. This project addresses this long-standing challenge by combining one of the frontrunners for quantum computing---superconducting Transmon qubits---with state-of-the-art acoustic resonator memories, which offer highly compact, long-lived quantum information storage. A coherent switchable interconnect needed for QRAM or transduction operation is provided by a voltage-tunable resonator that integrates a hybrid superconductor–semiconductor Josephson junction for on demand tuning of resonance frequency. This effort will not only lead to the first demonstration of QRAM in the laboratory but will also significantly advance the field of quantum transduction, where acoustic cavity modes are widely recognized as one of the most promising ways to connect distinct physical platforms due to their versatility and compatibility with a range of quantum systems.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.