Top Research Papers on Low Power VLSI Design

An extensive review of research related to the main power system operational challenges with respect to the massive deployment of PV sources and various control approaches and applications of battery energy storage system (BESS) to improve the inertial response of a low-inertia power system is presented.

Abstract Graphs have provided an expressive mathematical tool to model quantum-mechanical devices and systems. In particular, it has been recently discovered that graph theory can be used to describe and design quantum components, devices, setups and systems, based on the two-dimensional lattice of parametric nonlinear optical crystals and linear optical circuits, different to the standard quantum photonic framework. Realizing such graph-theoretical quantum photonic hardware, however, remains extremely challenging experimentally using conventional technologies. Here we demonstrate a graph-theo...

A genome-wide association study of plasma protein levels measured with 4,907 aptamers in 35,559 Icelanders highlights links with over 370 disease endpoints and other traits.

A scenario for 2030 for the Moroccan electricity system is studied and the challenges that need to be addressed are identified in order to accelerate the integration of renewable energies in the Moroccan energy mix and to achieve a possible export of such green energy towards Europe.

Grid integration of renewable energy (REN) requires efficient and reliable power conversion stages, particularly with an increasing demand for high controllability and flexibility seen from the grid side. Underpinned by advanced control and information technologies, power electronics converters play an essential role in large-scale REN generation. However, the use of power converters has also exposed several challenges in conventional power grids, e.g., reducing the system inertia. In this article, grid integration using power electronics is presented for large-scale REN generation. Technical ...

This work designs a data engine to collect and automatically annotate large-scale unlabeled data and develops an auxiliary supervision to enforce the model to inherit rich semantic priors from pre-trained encoders, which results in a better depth-conditioned ControlNet.

Power-to-gas (PtG) is widely expected to play a valuable role in future renewable energy systems. In addition to partly allowing a further utilization of the existing gas infrastructure for energy transport and storage, hydrogen or synthetic natural gas (SNG) from electric power represents a high-density energy carrier and important feedstock material for further processing. This premise leads to a significant demand for large-scale PtG plants, which was evaluated with an amount of up to 4530 GWel for electrolysis and up to 1360 GWSNG for methanation capacities at a global scale. Together with...

Intrinsically stretchable electronics with skin-like mechanical properties have been identified as a promising platform for emerging applications ranging from continuous physiological monitoring to real-time analysis of health conditions, to closed-loop delivery of autonomous medical treatment 1-7 . However, current technologies could only reach electrical performance at amorphous-silicon level (that is, charge-carrier mobility of about 1 cm 2 V -1 s -1 ), low integration scale (for example, 54 transistors per circuit) and limited functionalities 8-11 . Here we report high-density, intrinsical...

The ability to assemble large numbers of nearly indistinguishable and tunable artificial atoms into phase-stable PICs marks a key step towards multiplexed quantum repeaters 7 and general-purpose quantum processors.

Abstract Monolayer molybdenum disulfide (ML-MoS 2 ) is an emergent two-dimensional (2D) semiconductor holding potential for flexible integrated circuits (ICs). The most important demands for the application of such ML-MoS 2 ICs are low power consumption and high performance. However, these are currently challenging to satisfy due to limitations in the material quality and device fabrication technology. In this work, we develop an ultra-thin high-κ dielectric/metal gate fabrication technique for the realization of thin film transistors based on high-quality wafer scale ML-MoS 2 on both rigid an...

The vigorous expansion of renewable energy as a substitute for fossil energy is the predominant route of action to achieve worldwide carbon neutrality. However, clean energy supplies in multi-energy building districts are still at the preliminary stages for energy paradigm transitions. In particular, technologies and methodologies for large-scale renewable energy integrations are still not sufficiently sophisticated, in terms of intelligent control management. Artificial intelligent (AI) techniques powered renewable energy systems can learn from bio-inspired lessons and provide power systems w...

Optical metasurfaces are planar arrangements of subwavelength meta-atoms that implement a wide range of transformations on incident light. The design of efficient metasurfaces requires that the responses of and interactions among meta-atoms are accurately modeled. Conventionally, each meta-atom's response is approximated by that of a meta-atom located in a periodic array. Although this approximation is accurate for metastructures with slowly varying meta-atoms, it does not accurately model the complex interactions among meta-atoms in more rapidly varying metasurfaces. Optimization-based design...

Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address the authors' most pressing challenges in climate, agriculture and healthcare, and this work introduces ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design.

The results show that the current grid codes require high power – medium energy storage, being Li-Ion batteries the most suitable technology, and the best location of the energy storage within the photovoltaic power plays an important role and depends on the service.

This paper proposes a novel end-to-end attention-guided method based on multi-branch convolutional neural network that can produce high fidelity enhancement results for low-light images and outperforms the current state-of-the-art methods both quantitatively and visually.

This work proposes a hybrid model based on a long short-term memory-based encoder-decoder neural network and a Savitzky-Golay filter that can investigate nonlinear characteristics in a complicated water environment.

In this review, the newly emerging methods for the large-scale production of CDs are summarized, such as microwave, ultrasonic, plasma, magnetic hyperthermia and microfluidic technology.

Green ammonia, synthesized from air, water, and renewable energy, is a carbon-free energy storage vector with numerous potential energy applications, including dispatchable green electricity for the power sector. Due to the low cost of storing and transporting ammonia, green ammonia can be available as an energy source in all geographies, without the geological storage requirements of carbon capture and storage (CCS) or underground hydrogen storage. Here we contribute a novel techno-economic analysis to forecast the levelized cost of electricity (LCOE) from ammonia based on near-term and long-...

The rising tide of mental ill‐health in young people globally demands that this focus be elevated to a top priority in global health.

ABSTRACT We present the BACCO project, a simulation framework specially designed to provide highly-accurate predictions for the distribution of mass, galaxies, and gas as a function of cosmological parameters. In this paper, we describe our main suite of gravity-only simulations ($L\sim 2\,$ Gpc and 43203 particles) and present various validation tests. Using a cosmology-rescaling technique, we predict the non-linear mass power spectrum over the redshift range 0 < z < 1.5 and over scales $10^{-2} \lt k/(\, h\, {\rm Mpc}^{-1}) \lt 5$ for 800 points in an eight-dimensional cosmolog...