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Open Access Publications from the University of California

Scholarly Works (26 results)

  • Thesis
  • Peer Reviewed
UC Riverside Electronic Theses and Dissertations (2012)

Design and verification of today's nanometer very-large-scale integrated (VLSI) system remain a very challenging problem. For instance, the sub-90-nm technology has caused extremely large parasitic global interconnects and complicated models such as clock networks, power delivery networks and thermal models for packaged systems, which are difficult to be analyzed directly due to the limited computing resources. In addition, the high performance VLSI systems such as multi-core and emerging 3D stacked integrated systems, also lead to excessive high temperature on chip due to the elevated power densities. As a result, temperature should be explicitly managed both at design time through thermal-aware optimization and design techniques and at runtime through on-chip dynamic thermal management (DTM). Hence, accurate yet compact thermal models are required for thermal-aware design and optimization.

In this dissertation, we focus on those challenging issues and have proposed three novel techniques to facilitate the verification of the electronic and thermal effects of the nanometer integrated systems. Specifically, first, we have introduced a wideband model order reduction algorithm (WBMOR) to provide a general solution for the large system analysis problems. With the novel imaginary axis sampling technique and adaptive sample point placement, WBMOR is able to generate a reduced system accurate within the specified frequency band. Second, we have proposed a com- posable thermal modeling technique (ThermComp) for compact thermal modeling. ThermComp builds compact thermal models for each basic module, and uses these models to assemble different multi-core architecture thermal models, which improves the thermal modeling and analysis efficiency at design time. Last but not least, a runtime thermal estimation and prediction method (FRETEP) framework has been proposed to enable fine-grained DTM. With a thermal sensor based error compen- sation method utilizing only limited number of thermal sensors, FRETEP is able to estimate and predict the full-chip thermal behavior accurately with even inaccurate power estimation. Furthermore, a power-driven thermal sensor placement algorithm has been developed for FRETEP to further enhance the thermal estimation accuracy.

    Cover page: Compact Modeling and Analysis for Electronic and Thermal Effects of Nanometer Integrated and Packaged Systems
    • Article
    • Peer Reviewed
    UC Riverside Previously Published Works (2014)
    This paper proposes a new thermal modeling method for package design of high-performance microprocessors. The new approach builds the thermal behavioral models from the given accurate temperature and power information by means of the subspace method. The subspace method, however, may suffer predictability problem when the practical power is given as a number of power maps where power inputs are spatially correlated. We show that the input power signal needs to meet some dependency requirements to ensure model predictability. We develop a new algorithm, which generates independent power maps to meet the spatial rank requirement and can also automatically select the order of the resulting thermal models for the given error bounds. Experimental results validates the proposed method on a practical microprocessor package constructed via COMSOL software under practical power signal inputs.
      Cover page: Compact thermal modeling for package design with practical power maps
      • Article
      • Peer Reviewed
      LBL Publications (2016)
      Laminar flame speed measurements were carried for mixture of air with eight C3-4 hydrocarbons (propene, propane, 1,3-butadiene, 1-butene, 2-butene, iso-butene, n-butane, and iso-butane) at the room temperature and ambient pressure. Along with C1-2 hydrocarbon data reported in a recent study, the entire dataset was used to demonstrate how laminar flame speed data can be utilized to explore and minimize the uncertainties in a reaction model for foundation fuels. The USC Mech II kinetic model was chosen as a case study. The method of uncertainty minimization using polynomial chaos expansions (MUM-PCE) (D.A. Sheen and H. Wang, Combust. Flame 2011, 158, 2358-2374) was employed to constrain the model uncertainty for laminar flame speed predictions. Results demonstrate that a reaction model constrained only by the laminar flame speed values of methane/air flames notably reduces the uncertainty in the predictions of the laminar flame speeds of C3 and C4 alkanes, because the key chemical pathways of all of these flames are similar to each other. The uncertainty in model predictions for flames of unsaturated C3-4 hydrocarbons remain significant without considering fuel specific laminar flames speeds in the constraining target data set, because the secondary rate controlling reaction steps are different from those in the saturated alkanes. It is shown that the constraints provided by the laminar flame speeds of the foundation fuels could reduce notably the uncertainties in the predictions of laminar flame speeds of C4 alcohol/air mixtures. Furthermore, it is demonstrated that an accurate prediction of the laminar flame speed of a particular C4 alcohol/air mixture is better achieved through measurements for key molecular intermediates formed during the pyrolysis and oxidation of the parent fuel.
        • Article
        • Peer Reviewed
        UC San Diego Previously Published Works (2008)
        We used molecular dynamics (MD) simulations to explore the transport of single cations through the channel of the muscle nicotinic acetylcholine receptor (nAChR). Four MD simulations of 16 ns were performed at physiological and hyperpolarized membrane potentials, with and without restraints of the structure, but all without bound agonist. With the structure unrestrained and a potential of -100 mV, one cation traversed the channel during a transient period of channel hydration; at -200 mV, the channel was continuously hydrated and two cations traversed the channel. With the structure restrained, however, cations did not traverse the channel at either membrane potential, even though the channel was continuously hydrated. The overall results show that cation selective transport through the nAChR channel is governed by electrostatic interactions to achieve charge selectivity, but ion translocation relies on channel hydration, facilitated by a trans-membrane field, coupled with dynamic fluctuations of the channel structure.
          Cover page: Control of Cation Permeation through the Nicotinic Receptor Channel
          • Article
          • Peer Reviewed
          UC Irvine Previously Published Works (2019)
          We consider an on-demand service platform using earning-sensitive independent providers with heterogeneous reservation price (for work participation) to serve its time and price-sensitive customers with heterogeneous valuation of the service. As such, the supply and demand are “endogenously” dependent on the price the platform charges its customers and the wage the platform pays its independent providers. We present an analytical model with endogenous supply (number of participating agents) and endogenous demand (customer request rate) to study this on-demand service platform. To coordinate endogenous demand with endogenous supply, we include the steady-state waiting time performance based on a queueing model in the customer utility function to characterize the optimal price and wage rates that maximize the profit of the platform. We first analyze a base model that uses a fixed payout ratio (i.e., the ratio of wage over price), and then extend our model to allow the platform to adopt a time-based payout ratio. We find that it is optimal for the platform to charge a higher price when demand increases; however, the optimal price is not necessarily monotonic when the provider capacity or the waiting cost increases. Furthermore, the platform should offer a higher payout ratio as demand increases, capacity decreases or customers become more sensitive to waiting time. We also find that the platform should lower its payout ratio as it grows with the number of providers and customer demand increasing at about the same rate. We use a set of actual data from a large on-demand ride-hailing platform to calibrate our model parameters in numerical experiments to illustrate some of our main insights.
            Cover page: Coordinating Supply and Demand on an On-Demand Service Platform with Impatient Customers
            • Article
            • Peer Reviewed
            UC Riverside Previously Published Works (2014)
            In this paper, we propose a new behavioral thermal modeling technique for high-performance microprocessors at package level. Firstly, the new approach applies the subspace identification method with the consideration of practical power maps with correlated power signals. We show that the input power signal needs to meet an independence requirement to ensure the model predictability and propose an iterative process to build the models with given error bounds. Secondly, we show that thermal systems fundamentally are nonlinear and then propose a piecewise linear (PWL) scheme to deal with nonlinear effects. The experimental results validated the proposed method on a realistic packaged integrated system modeled by the multi-domain/physics commercial tool, COMSOL. The new piecewise linear models can model thermal behaviors over wide temperature ranges or over different thermal boundary convective conditions due to different fan speeds. Further, the PWL modeling technique can lead to much smaller model order without accuracy loss, which translates to significant savings in both the simulation time and the time required to identify the reduced models compared to the simple modeling method by using the high order models. © 2013 Elsevier B.V. All rights reserved.
              • Article
              • Peer Reviewed
              LBL Publications (2017)
              Well-defined molecular brushes bearing polypeptides as side chains were prepared by a "grafting through" synthetic strategy with two-dimensional control over the brush molecular architectures. By integrating N-carboxyanhydride ring-opening polymerizations (NCA ROPs) and ring-opening metathesis polymerizations (ROMPs), desirable segment lengths of polypeptide side chains and polynorbornene brush backbones were independently constructed in controlled manners. The N2 flow accelerated NCA ROP was utilized to prepare polypeptide macromonomers with different lengths initiated from a norbornene-based primary amine, and those macromonomers were then polymerized via ROMP. It was found that a mixture of dichloromethane and an ionic liquid were required as the solvent system to allow for construction of molecular brush polymers having densely-grafted peptide chains emanating from a polynorbornene backbone, poly(norbornene-graft-poly(β-benzyl-l-aspartate)) (P(NB-g-PBLA)). Highly efficient postpolymerization modification was achieved by aminolysis of PBLA side chains for facile installment of functional moieties onto the molecular brushes.
                Cover page: Two-Dimensional Controlled Syntheses of Polypeptide Molecular Brushes via N-Carboxyanhydride Ring-Opening Polymerization and Ring-Opening Metathesis Polymerization.
                • Article
                • Peer Reviewed
                UC Berkeley Previously Published Works (2023)
                Understanding nanodiamond structures is of great scientific and practical interest. It has been a long-standing challenge to unravel the complexity underlying nanodiamond structures and to resolve the controversies surrounding their polymorphic forms. Here, we use transmission electron microscopy with high-resolution imaging, electron diffraction, multislice simulations, and other supplementary techniques to study the impacts of small sizes and defects on cubic diamond nanostructures. The experimental results show that common cubic diamond nanoparticles display the (200) forbidden reflections in their electron diffraction patterns, which makes them indistinguishable from new diamond (n-diamond). The multislice simulations demonstrate that cubic nanodiamonds smaller than 5 nm can present the d-spacing at 1.78 Å corresponding to the (200) forbidden reflections, and the relative intensity of these reflections increases as the particle size decreases. Our simulation results also reveal that defects, such as surface distortions, internal dislocations, and grain boundaries can also make the (200) forbidden reflections visible. These findings provide valuable insights into the diamond structural complexity at nanoscale, the impact of defects on nanodiamond structures, and the discovery of novel diamond structures.
                  Cover page: Unveiling the complexity of nanodiamond structures
                  • Article
                  • Peer Reviewed
                  UC Davis Previously Published Works (2019)
                  Triple-negative breast cancer (TNBC) is a heterogeneous disease with a poor prognosis due to the lack of an effective targeted therapy. Histone lysine methyltransferases (KMTs) have emerged as attractive drug targets for cancer therapy. However, the function of the majority of KMTs in TNBC has remained largely unknown. In the current study, we found that KMT nuclear receptor binding SET domain protein 2 (NSD2) is overexpressed in TNBC tumors and that its overexpression is associated with poor survival of TNBC patients. NSD2 regulates TNBC cell survival and invasion and is required for tumorigenesis and tumor growth. Mechanistically, NSD2 directly controls the expression of EGFR and ADAM9, a member of the ADAM (a disintegrin and metalloproteinase) family that mediates the release of growth factors, such as HB-EGF. Through its methylase activity, NSD2 overexpression stimulates EGFR-AKT signaling and promotes TNBC cell resistance to the EGFR inhibitor gefitinib. Together, our results identify NSD2 as a major epigenetic regulator in TNBC and provide a rationale for targeting NSD2 alone or in combination with EGFR inhibitors as a targeted therapy for TNBC.
                    Cover page: Histone methyltransferase NSD2 mediates the survival and invasion of triple-negative breast cancer cells via stimulating ADAM9-EGFR-AKT signaling
                    • Article
                    • Peer Reviewed
                    UC Berkeley Previously Published Works (2015)
                    Low detection sensitivity stemming from the weak polarization of nuclear spins is a primary limitation of magnetic resonance spectroscopy and imaging. Methods have been developed to enhance nuclear spin polarization but they typically require high magnetic fields, cryogenic temperatures or sample transfer between magnets. Here we report bulk, room-temperature hyperpolarization of (13)C nuclear spins observed via high-field magnetic resonance. The technique harnesses the high optically induced spin polarization of diamond nitrogen vacancy centres at room temperature in combination with dynamic nuclear polarization. We observe bulk nuclear spin polarization of 6%, an enhancement of ∼170,000 over thermal equilibrium. The signal of the hyperpolarized spins was detected in situ with a standard nuclear magnetic resonance probe without the need for sample shuttling or precise crystal orientation. Hyperpolarization via optical pumping/dynamic nuclear polarization should function at arbitrary magnetic fields enabling orders of magnitude sensitivity enhancement for nuclear magnetic resonance of solids and liquids under ambient conditions.
                      Cover page: Room-temperature in situ nuclear spin hyperpolarization from optically pumped nitrogen vacancy centres in diamond
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