Theoretical Performance Limits Research Articles

Electroenzymatic glutamate sensing at near the theoretical performance limit.

The sensitivity and response time of glutamate sensors based on glutamate oxidase immobilized on planar platinum microelectrodes have been improved to near the theoretical performance limits predicted by a detailed mathematical model. Microprobes with an array of electroenzymatic sensing sites have emerged as useful tools for the monitoring of glutamate and other neurotransmitters in vivo; and implemented as such, they can be used to study many complex neurological diseases and disorders including Parkinson's disease and drug addiction. However, less than optimal sensitivity and response time has limited the spatiotemporal resolution of these promising research tools. A mathematical model has guided systematic improvement of an electroenzymatic glutamate microsensor constructed with a 1-2 μm-thick crosslinked glutamate oxidase layer and underlying permselective coating of polyphenylenediamine and Nafion reduced to less than 200 nm thick. These design modifications led to a nearly 6-fold improvement in sensitivity to 320 ± 20 nA μM-1 cm-2 at 37 °C and a ∼10-fold reduction in response time to 80 ± 10 ms. Importantly, the sensitivity and response times were attained while maintaining a low detection limit and excellent selectivity. Direct measurement of the transport properties of the enzyme and polymer layers used to create the biosensors enabled improvement of the mathematical model as well. Subsequent model simulations indicated that the performance characteristics achieved with the optimized biosensors approach the theoretical limits predicted for devices of this construction. Such high-performance glutamate biosensors will be more effective in vivo at a size closer to cellular dimension and will enable better correlation of glutamate signaling events with electrical recordings.

Metal/BaTiO3/β-Ga2O3 dielectric heterojunction diode with 5.7 MV/cm breakdown field

Wide and ultrawide bandgap semiconductors can provide excellent performance due to their high energy bandgap, which leads to breakdown electric fields that are more than an order of magnitude higher than conventional silicon electronics. In materials where p-type doping is not available, achieving this high breakdown field in a vertical diode or transistor is very challenging. We propose and demonstrate the use of dielectric heterojunctions that use extreme permittivity materials to achieve a high breakdown field in a unipolar device. We demonstrate the integration of a high permittivity material BaTiO3 with n-type β-Ga2O3 to enable a 5.7 MV/cm average electric field and a 7 MV/cm peak electric field at the device edge while maintaining forward conduction with relatively low on-resistance and voltage loss. The proposed dielectric heterojunction could enable improved design strategies to achieve theoretical device performance limits in wide and ultrawide bandgap semiconductors where bipolar doping is challenging.

Differential Scene Flow from Light Field Gradients

This paper presents novel techniques for recovering 3D dense scene flow, based on differential analysis of 4D light fields. The key enabling result is a per-ray linear equation, called the ray flow equation, that relates 3D scene flow to 4D light field gradients. The ray flow equation is invariant to 3D scene structure and applicable to a general class of scenes, but is under-constrained (3 unknowns per equation). Thus, additional constraints must be imposed to recover motion. We develop two families of scene flow algorithms by leveraging the structural similarity between ray flow and optical flow equations: local 'Lucas-Kanade' ray flow and global 'Horn-Schunck' ray flow, inspired by corresponding optical flow methods. We also develop a combined local-global method by utilizing the correspondence structure in the light fields. We demonstrate high precision 3D scene flow recovery for a wide range of scenarios, including rotation and non-rigid motion. We analyze the theoretical and practical performance limits of the proposed techniques via the light field structure tensor, a 3x3 matrix that encodes the local structure of light fields. We envision that the proposed analysis and algorithms will lead to design of future light-field cameras that are optimized for motion sensing, in addition to depth sensing.

Synthetic Systems Powered by Biological Molecular Motors

Biological molecular motors (or biomolecular motors for short) are nature's solution to the efficient conversion of chemical energy to mechanical movement. In biological systems, these fascinating molecules are responsible for movement of molecules, organelles, cells, and whole animals. In engineered systems, these motors can potentially be used to power actuators and engines, shuttle cargo to sensors, and enable new computing paradigms. Here, we review the progress in the past decade in the integration of biomolecular motors into hybrid nanosystems. After briefly introducing the motor proteins kinesin and myosin and their associated cytoskeletal filaments, we review recent work aiming for the integration of these biomolecular motors into actuators, sensors, and computing devices. In some systems, the creation of mechanical work and the processing of information become intertwined at the molecular scale, creating a fascinating type of "active matter". We discuss efforts to optimize biomolecular motor performance, construct new motors combining artificial and biological components, and contrast biomolecular motors with current artificial molecular motors. A recurrent theme in the work of the past decade was the induction and utilization of collective behavior between motile systems powered by biomolecular motors, and we discuss these advances. The exertion of external control over the motile structures powered by biomolecular motors has remained a topic of many studies describing exciting progress. Finally, we review the current limitations and challenges for the construction of hybrid systems powered by biomolecular motors and try to ascertain if there are theoretical performance limits. Engineering with biomolecular motors has the potential to yield commercially viable devices, but it also sharpens our understanding of the design problems solved by evolution in nature. This increased understanding is valuable for synthetic biology and potentially also for medicine.

Investigation of the Liquid–Vapor Separator Efficiency on the Performance of the Ejector Used as an Expansion Device in the Vapor-Compression Refrigeration Cycle

Abstract Ejector expansion refrigeration cycle with reference to the constant pressure mixing theory is investigated to display the effects of the liquid–vapor separator efficiency on the performance, entrainment ratio, and area ratio at various operation conditions. Reversible ejector assumption is used for the highest theoretical performance limit, whereas efficiency of the liquid–vapor separator and all ejector components is added to the model to calculate more realistic performance improvement potentials. R1234yf and R1234ze(E) having low global warming potential values are used in the analyses. Zero-dimensional thermodynamic models are constructed applying the conservation equations between the inlets and outlets of the refrigeration cycle and ejector components. Percentage performance decrease is higher when the mixing section and the separator efficiency is added to the model at higher condenser temperatures compared with the lower evaporator temperatures according to the investigated operation ranges. Vapor and liquid separation efficiency affects not only the performance but also the design of the ejector although it is an external component since it has influence on the area ratio and entrainment ratio. Finally, the difference between the percentage performance improvement of the reversible ejector cycle and the realistic ejector cycle including the separator and ejector components efficiencies is as high as 35% at the highest investigated condenser temperature for R1234yf.

Theoretical Performance Limits of Massive MIMO With Uncorrelated Rician Fading Channels

This paper considers a Massive MIMO network with $ {L}$ cells, each comprising a base stations (BS) with $ {M}$ antennas and $K$ single-antenna user equipments. Within this setting, we are interested in deriving approximations of the achievable rates in the uplink and downlink under the assumption that single-cell linear processing is used at each BS and that each intracell link forms an uncorrelated MIMO Rician fading channel matrix; that is, with a deterministic line-of-sight (LoS) path and a stochastic non-LoS component describing a spatial uncorrelated multipath environment. The analysis is conducted assuming that $ {N}$ and $ {K}$ grow large with a given ratio ${\textbf {N/K}}$ under the assumption that the data transmission in each cell is affected by channel estimation errors, pilot contamination, an arbitrary large scale attenuation and LoS components. Numerical results are used to prove that the approximations are asymptotically tight, but accurate for systems with finite dimensions. The asymptotic results are also used to evaluate the impact of LoS components. In particular, we exemplify how the number of antennas for achieving a target rate can be substantially reduced with LoS links of only a few dBs of strength.

A Tutorial on Lossy Forwarding Cooperative Relaying

Lossy decode-and-forward (DF) relaying, also referred to as lossy forwarding (LF), can significantly enhance the transmission reliability and expand the communication coverage at the cost of a small increase in computational effort compared to its DF counterpart. Furthermore, it can further simplify the operations at the relay nodes by removing the error-detecting operation, e.g., cyclic redundancy check, which is used in the conventional DF systems. Due to these advantages, LF has been intensively investigated with the aim of its applications to various cooperative communication networks with different topologies. This paper offers a comprehensive literature review on the LF relaying strategy and makes comparisons between LF and DF. Five basic exemplifying scenarios are taken into consideration. These are the three-node network, the single-source multi-relay network with direct source-to-destination link, the multiple access relay channel, the two-way relay network, and the general multi-source multi-relay network. The paper includes not only theoretical performance limit analyses, but also performance evaluation by employing low-complexity accumulator aided turbo codes at the sources and relays as well as joint decoding at the destination. As expected, the performance enhancement in terms of outage probability, frame error rate, and $ {\epsilon }$ -outage achievable rate by LF over DF is significant, which is demonstrated in all the exemplifying scenarios in the literatures. Hence LF has a great potential to be applied to future 5G wireless communication networks, e.g., device-to-device, vehicle-to-vehicle, and machine-type communications, which are composed of the aforementioned exemplifying scenarios.

Wireless Communications Through Reconfigurable Intelligent Surfaces

The future of mobile communications looks exciting with the potential new use cases and challenging requirements of future 6th generation (6G) and beyond wireless networks. Since the beginning of the modern era of wireless communications, the propagation medium has been perceived as a randomly behaving entity between the transmitter and the receiver, which degrades the quality of the received signal due to the uncontrollable interactions of the transmitted radio waves with the surrounding objects. The recent advent of reconfigurable intelligent surfaces in wireless communications enables, on the other hand, network operators to control the scattering, reflection, and refraction characteristics of the radio waves, by overcoming the negative effects of natural wireless propagation. Recent results have revealed that reconfigurable intelligent surfaces can effectively control the wavefront, e.g., the phase, amplitude, frequency, and even polarization, of the impinging signals without the need of complex decoding, encoding, and radio frequency processing operations. Motivated by the potential of this emerging technology, the present article is aimed to provide the readers with a detailed overview and historical perspective on state-of-the-art solutions, and to elaborate on the fundamental differences with other technologies, the most important open research issues to tackle, and the reasons why the use of reconfigurable intelligent surfaces necessitates to rethink the communication-theoretic models currently employed in wireless networks. This article also explores theoretical performance limits of reconfigurable intelligent surface-assisted communication systems using mathematical techniques and elaborates on the potential use cases of intelligent surfaces in 6G and beyond wireless networks.

The choice of sequence homologs included in multiple sequence alignments has a dramatic impact on evolutionary conservation analysis.

The analysis of sequence conservation patterns has been widely utilized to identify functionally important (catalytic and ligand-binding) protein residues for over a half-century. Despite decades of development, on average state-of-the-art non-template-based functional residue prediction methods must predict ∼25% of a protein's total residues to correctly identify half of the protein's functional site residues. The overwhelming proportion of false positives results in reported 'F-Scores' of ∼0.3. We investigated the limits of current approaches, focusing on the so-far neglected impact of the specific choice of homologs included in multiple sequence alignments (MSAs). The limits of conservation-based functional residue prediction were explored by surveying the binding sites of 1023 proteins. A straightforward conservation analysis of MSAs composed of randomly selected homologs sampled from a PSI-BLAST search achieves average F-Scores of ∼0.3, a performance matching that reported by state-of-the-art methods, which often consider additional features for the prediction in a machine learning setting. Interestingly, we found that a simple combinatorial MSA sampling algorithm will in almost every case produce an MSA with an optimal set of homologs whose conservation analysis reaches average F-Scores of ∼0.6, doubling state-of-the-art performance. We also show that this is nearly at the theoretical limit of possible performance given the agreement between different binding site definitions. Additionally, we showcase the progress in this direction made by Selection of Alignment by Maximal Mutual Information (SAMMI), an information-theory-based approach to identifying biologically informative MSAs. This work highlights the importance and the unused potential of optimally composed MSAs for conservation analysis. Supplementary data are available at Bioinformatics online.

Theoretical Performance Limits of an Isobaric Hybrid Compressed Air Energy Storage System

The desire to increase power production through renewable sources introduces a number of problems due to their inherent intermittency. One solution is to incorporate energy storage systems as a means of managing the intermittent energy and increasing the utilization of renewable sources. A novel hybrid thermal and compressed air energy storage (HT-CAES) system is presented which mitigates the shortcomings of the otherwise attractive conventional compressed air energy storage (CAES) systems and its derivatives, such as strict geological locations, low energy density, and the production of greenhouse gas emissions. The HT-CAES system is investigated, and the thermodynamic efficiency limits within which it operates have been drawn. The thermodynamic models considered assume a constant pressure cavern. It is shown that under this assumption the cavern acts just as a delay time in the operation of the plant, whereas an adiabatic constant volume cavern changes the quality of energy through the cavern. The efficiency of the HT-CAES system is compared with its Brayton cycle counterpart, in the case of pure thermal energy storage (TES). It is shown that the efficiency of the HT-CAES plant is generally not bound by the Carnot efficiency and always higher than that of the Brayton cycle, except for when the heat losses following compression rise above a critical level. The results of this paper demonstrate that the HT-CAES system has the potential of increasing the efficiency of a pure TES system executed through a Brayton cycle at the expense of an air storage medium.

Distinguishing Bulk Conduction from Band Bending Transduction Mechanisms in Chemiresistive Metal Oxide Gas Sensors

Chemiresistive metal oxide gas sensors based on materials including SnO2, ZnO, TiO2, and WO3 have been investigated extensively for a wide range of applications. The band bending model, based on the surface chemistry of highly reactive ionosorbed species (O2– or O–) and the semiconducting material properties of SnO2, TiO2, and ZnO, adequately predicts the dependence of steady state response on target gas pressure and temperature for these materials. However, the assumptions associated with the band bending model are not valid for sensors based on reducible oxides such as WO3, MoO3, and V2O5, in which lattice oxygen reacts with adsorbed target gases creating oxygen vacancies which diffuse rapidly into the bulk and modulate the conductivity. Here, we develop a model that includes surface reactions and vacancy diffusion for the bulk conduction mechanism and describe characteristics of the sensor behavior that allow bulk conduction to be distinguished from the band bending transduction mechanism. We illustrate the predictions of the model regarding how the change in conductivity, Δσ, and response time, τ, depend on target gas pressure, temperature, and film thickness using well-characterized WO3 sensors, including epitaxially oriented polycrystalline thin films and nanorod structured glancing angle deposition (GLAD) films. The physical/chemical parameters of the model are determined in independent measurements. Expressions for the limiting cases in which τ is determined either by surface reactions or by bulk diffusion provide design criteria to predict the theoretical performance limits of sensors which operate via this transduction mechanism.

Present status and future prospects of perovskite photovoltaics.

Solar cells based on metal halide perovskites continue to approach their theoretical performance limits thanks to worldwide research efforts. Mastering the materials properties and addressing stability may allow this technology to bring profound transformations to the electric power generation industry.

Multi-level radioisotope batteries based on 60Co γ source and Radio-voltaic/Radio-photovoltaic dual effects

A dual effect multi-level isotope battery based on γ radioisotope source was proposed. Two types of energy conversion mechanisms, namely, radio-voltaic (RV) and radio-photovoltaic (RPV) effects, was combined to convert the radiation energy of γ ray to electricity. The theoretical performance limit for the dual effect multi-level isotope battery irradiated by 60Co radioisotope source was calculated, and the characteristics of each conversion mechanism were analyzed by using MCNP5. The results revealed that the RPV effect produced more electrical output than the RV effect, but the contribution of each effect on the battery was significant. The output performance of the multi-level isotope battery was characterized under 60Co source at dose rates of 0.103 kGy/h and 0.68 kGy/h. The theoretical and experimental study investigated the feasibility of combining two kinds of energy conversion mechanisms to enhance the performance of nuclear batteries. The use of 60Co radioisotope sources with a large activity and conversion modules with additional levels could obtain a considerable output performance. Moreover, the thickness influence of the LYSO scintillator on the performance limit in the first-level conversion module was studied to optimize the structural parameters of the multi-level dual effect isotope battery. The thickness of scintillator strongly affects the energy deposition distribution of gamma rays in the multi-level conversion module, resulting in changes of the output generated by RV and RPV effects, which in turn affects the total output of the battery.

Imperceptible reversible watermarking of radiographic images based on quantum noise masking

Background and objectiveAdvances in information and communication technologies boost the sharing and remote access to medical images. Along with this evolution, needs in terms of data security are also increased. Watermarking can contribute to better protect images by dissimulating into their pixels some security attributes (e.g., digital signature, user identifier). But, to take full advantage of this technology in healthcare, one key problem to address is to ensure that the image distortion induced by the watermarking process does not endanger the image diagnosis value. To overcome this issue, reversible watermarking is one solution. It allows watermark removal with the exact recovery of the image. Unfortunately, reversibility does not mean that imperceptibility constraints are relaxed. Indeed, once the watermark removed, the image is unprotected. It is thus important to ensure the invisibility of reversible watermark in order to ensure a permanent image protection. MethodsWe propose a new fragile reversible watermarking scheme for digital radiographic images, the main originality of which stands in masking a reversible watermark into the image quantum noise (the dominant noise in radiographic images). More clearly, in order to ensure the watermark imperceptibility, our scheme differentiates the image black background, where message embedding is conducted into pixel gray values with the well-known histogram shifting (HS) modulation, from the anatomical object, where HS is applied to wavelet detail coefficients, masking the watermark with the image quantum noise. In order to maintain the watermark embedder and reader synchronized in terms of image partitioning and insertion domain, our scheme makes use of different classification processes that are invariant to message embedding. ResultsWe provide the theoretical performance limits of our scheme into the image quantum noise in terms of image distortion and message size (i.e. capacity). Experiments conducted on more than 800 12 bits radiographic images of different anatomical structures show that our scheme induces a very low image distortion (PSNR∼ 76.5 dB) for a relatively important capacity (capacity∼ 0.02 bits of message per pixel). ConclusionsThe proposed watermarking scheme, while being reversible, preserves the diagnosis value of radiographic images by masking the watermark into the quantum noise. As theoretically and experimentally established our scheme offers a good capacity/image quality compromise that can support different watermarking based security services such as integrity and authenticity control. The watermark can be kept into the image during the interpretation of the image, offering thus a continuous protection. Such a masking strategy can be seen as the first psychovisual model for radiographic images. The reversibility allows the watermark update when necessary.

Non-Uniform Wavelet Sampling for RF Analog-to-Information Conversion

Feature extraction, such as spectral occupancy, interferer energy and type, or direction-of-arrival, from wideband radio-frequency (RF) signals finds use in a growing number of applications as it enhances RF transceivers with cognitive abilities and enables parameter tuning of traditional RF chains. In power and cost limited applications, e.g., for sensor nodes in the Internet of Things, wideband RF feature extraction with conventional, Nyquist-rate analog-to-digital converters is infeasible. However, the structure of many RF features (such as signal sparsity) enables the use of compressive sensing (CS) techniques that acquire such signals at sub-Nyquist rates; while such CS-based analog-to-information (A2I) converters have the potential to enable low-cost and energy-efficient wideband RF sensing, they suffer from a variety of real-world limitations, such as noise folding, low sensitivity, aliasing, and limited flexibility. This paper proposes a novel CS-based A2I architecture called non-uniform wavelet sampling. Our solution extracts a carefully-selected subset of wavelet coefficients directly in the RF domain, which mitigates the main issues of existing A2I converter architectures. For multi-band RF signals, we propose a specialized variant called non-uniform wavelet bandpass sampling (NUWBS), which further improves sensitivity and reduces hardware complexity by leveraging the multi-band signal structure. We use simulations to demonstrate that NUWBS approaches the theoretical performance limits of $\ell_{1}$ -norm-based sparse signal recovery. We investigate hardware-design aspects and show ASIC measurement results for the wavelet generation stage, which highlight the efficacy of NUWBS for a broad range of RF feature extraction tasks in cost- and power-limited applications.

Scalable Urban Mobile Crowdsourcing

In this article, we investigate effective ways of utilizing crowdworkers in providing various urban services. The task recommendation platform that we design can match tasks to crowdworkers based on workers’ historical trajectories and time budget limits, thus making recommendations personal and efficient. One major challenge we manage to address is the handling of crowdworker’s trajectory uncertainties. In this article, we explicitly allow multiple routine routes to be probabilistically associated with each worker. We formulate this problem as an integer linear program whose goal is to maximize the expected total utility achieved by all workers. We further exploit the separable structures of the formulation and apply the Lagrangian relaxation technique to scale up computation. Numerical experiments have been performed over the instances generated using the realistic public transit dataset in Singapore. The results show that we can find significantly better solutions than the deterministic formulation, and in most cases we can find solutions that are very close to the theoretical performance limit. To demonstrate the practicality of our approach, we deployed our recommendation engine to a campus-scale field trial, and we demonstrate that workers receiving our recommendations incur fewer detours and complete more tasks, and are more efficient against workers relying on their own planning (25% more for top workers who receive recommendations). This is achieved despite having highly uncertain worker trajectories. We also demonstrate how to further improve the robustness of the system by using a simple multi-coverage mechanism.

Zinc-based field effect transistors get performance boost from clever engineering

Adding a fourth component offers charge concentration properties to zinc oxide-based field effect transistors that bring them closer to yet-unachieved theoretical limits of performance.

Theoretical Performance Limit of the IGBT

In this paper, an analytical model of insulated gate bipolar transistor (IGBT) on-state voltage ( ${V}_{\mathrm {{ {{ON}}}}}$ ) and turn-off loss ( ${E}_{\mathrm {{ {{OFF}}}}}$ ) is developed to find the optimum solution (minimum power loss) for a given application. With this model, it is found that IGBT on-state voltage is limited by the fact that holes can only flow from the anode to the cathode. The minimum on-state voltage for a Si IGBT with 110- $\mu \text{m}$ wide drift region is found out to be around 0.835 V at 100 A/cm2 and room temperature. For a given operating frequency and chip size, a tradeoff between on-state voltage and turn-off loss that gives minimum device power loss can be achieved by manipulating the carrier profile in the drift region with an optimum structure design. This minimum device loss decreases mildly with increasing chip size, i.e., a merely 45% loss reduction when the chip size increases from 0.2 to 5 cm2. These results clearly indicate that the performance of an IGBT is not area sensitive. They are encouraging for device manufacturers who wish to reduce the device chip size to lower cost. However, the constraint comes from the device thermal dissipation capabilities which decrease quickly with decreasing chip size. These results are validated with numerical 2-D device simulations for a large variety of device structures, chip size, and operating frequencies (2 to 200 kHz). State-of-the-art IGBT product performance is compared against the theoretical limit indicating there is still substantial room for improvement at low and high frequencies.

Numerical study and theoretical performance limit of interconnected multi-capillary gas chromatography columns with perfectly ordered pillar patterns

We present the results of a theoretical and numerical study of the chromatographic performance of a novel type of microfabricated GC column. The column consists of an array of rectangular flow diverters (pillars), creating a network of perfectly ordered, interconnected and tortuous flow-through paths. Using van Deemter and kinetic plots of simulated band broadening data, we could demonstrate that the proposed column structure performs as a bundle of parallel open-tubular capillaries with rectangular cross-section, connected by a regular pattern of channel-intermixing points that allow compensating for inevitable channel-to-channel differences in migration velocity without adding any significant dispersion themselves. The established kinetic plots also allowed to propose design rules for the optimal distance between the pillars as a function of the desired separation efficiency and the available column pressure. The simulations also allowed establishing an expression for the plate height as a function of the velocity of the carrier gas. Results are also compared to the results of a recent experimental study.

(Invited) Achieving Vertical Trench-Gate GaN MOSFETs via Process Optimization

Gallium nitride is a strong candidate material for advanced power electronics that exceed the capabilities of current Si and SiC technologies. The ideal device structure for GaN power switches is the vertical metal-oxide-semiconductor field effect transistor (MOSFET). Current vertical GaN MOSFETs have not reached theoretical performance limits. Optimization of these devices is required to improve their performance, particularly with respect to the dielectric/semiconductor interface along the device active regions, and processing used to fabricate the vertical channel regions. We have studied two atomic layer deposition precursor systems for ZrO2 dielectrics on both as-grown and plasma-etched c-plane GaN. Piranha etching of GaN surfaces before ALD improved the capacitance-voltage response of the deposited ZrO2. 5-10 µm deep trenches in GaN substrates have also been fabricated, to allow more detailed study of the trench sidewalls and dielectric interfaces on the etched surfaces before and after hydroxide-based wet etching.