skip to main content

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Linearization for High-Speed Current-Steering DACs Using Neural Networks
This paper proposes a novel foreground lineariza- tion scheme for a high-speed current-steering (CS) digital-to- analog converter (DAC). The technique leverages neural networks (NNs) to derive a lookup-table (LUT) that maps the inverse of the DAC transfer characteristic onto the input codes. The algorithm is shown to improve conventional methods by at least 6dB in terms of intermodulation (IM) performance for frequencies up to 9GHz on a state-of-the-art 10-bit CS-DAC operating at 40.96GS/s (gigasamples-per-second) in 14nm CMOS.  more » « less
Award ID(s):
1763747
PAR ID:
10295989
Author(s) / Creator(s):
;
Date Published:
Journal Name:
IEEE 12th Latin America Symposium on Circuits and Systems
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ( , Nature Communications)
    Abstract

    Direct air capture (DAC) is critical for achieving stringent climate targets, yet the environmental implications of its large-scale deployment have not been evaluated in this context. Performing a prospective life cycle assessment for two promising technologies in a series of climate change mitigation scenarios, we find that electricity sector decarbonization and DAC technology improvements are both indispensable to avoid environmental problem-shifting. Decarbonizing the electricity sector improves the sequestration efficiency, but also increases the terrestrial ecotoxicity and metal depletion levels per tonne of CO2sequestered via DAC. These increases can be reduced by improvements in DAC material and energy use efficiencies. DAC exhibits regional environmental impact variations, highlighting the importance of smart siting related to energy system planning and integration. DAC deployment aids the achievement of long-term climate targets, its environmental and climate performance however depend on sectoral mitigation actions, and thus should not suggest a relaxation of sectoral decarbonization targets.

     
    more » « less
  2. ; ; ; ; ; ; ; ( , Advanced Functional Materials)
    Abstract

    Global reliance on fossil fuel combustion for energy production has contributed to the rising concentration of atmospheric CO2, creating significant global climate challenges. In this regard, direct air capture (DAC) of CO2from the atmosphere has emerged as one of the most promising strategies to counteract the harmful effects on the environment, and the further development and commercialization of this technology will play a pivotal role in achieving the goal of net‐zero emissions by 2050. Among various DAC adsorbents, metal–organic frameworks (MOFs) show great potential due to their high porosity and ability to reversibly adsorb CO2at low concentrations. However, the adsorption efficiency and cost‐effectiveness of these materials must be improved to be widely deployed as DAC sorbents. To that end, this perspective provides a critical discussion on several types of benchmark MOFs that have demonstrated high CO2capture capacities, including an assessment of their stability, CO2capture mechanism, capture‐release cycling behavior, and scale‐up synthesis. It then concludes by highlighting limitations that must be addressed for these MOFs to go from the research laboratory to implementation in DAC devices on a global scale so they can effectively mitigate climate change.

     
    more » « less
  3. ; ( , AIChE Journal)
    Abstract

    Direct air capture (DAC) can help in reduction of atmospheric CO2levels by capturing CO2from disperse emission sources. We analyze DAC process through solid adsorbent and perform comprehensive energy and techno‐economic analysis for different parametric scenarios. The parameters are varied such that it reflects list of possible cases of DAC solid adsorbent systems ranging from worst case to best case situations. A mid‐range estimate has also been analyzed which considers the parameter values feasible with the current state of the art. The modeling results for the mid‐range estimate indicate that the cost of DAC lies between $86 and 221 per tCO2, the thermal energy range varies from 3.4 to 4.8 GJ per tCO2captured and the electrical energy range varies from 0.55 to 1.12 GJ per tCO2captured. For the best and worst case scenarios, the cost of DAC ranges from $14 to 1,065 per tCO2, thermal energy ranges from 1.85 to 19.30 per tCO2captured and the electrical energy ranges from 0.08 to 3.79 GJ per tCO2captured. Flux and intensity estimates have been performed which shows higher flux and lower intensity of DAC process as compared to a tropical tree.

     
    more » « less
  4. ; ; ; ; ( , Forecasting)
    A divide-and-conquer (DAC) machine learning approach was first proposed by Wang et al. to forecast the sea surface height (SSH) of the Loop Current System (LCS) in the Gulf of Mexico. In this DAC approach, the forecast domain was divided into non-overlapping partitions, each of which had their own prediction model. The full domain SSH prediction was recovered by interpolating the SSH across each partition boundaries. Although the original DAC model was able to predict the LCS evolution and eddy shedding more than two months and three months in advance, respectively, growing errors at the partition boundaries negatively affected the model forecasting skills. In the study herein, a new partitioning method, which consists of overlapping partitions is presented. The region of interest is divided into 50%-overlapping partitions. At each prediction step, the SSH value at each point is computed from overlapping partitions, which significantly reduces the occurrence of unrealistic SSH features at partition boundaries. This new approach led to a significant improvement of the overall model performance both in terms of features prediction such as the location of the LC eddy SSH contours but also in terms of event prediction, such as the LC ring separation. We observed an approximate 12% decrease in error over a 10-week prediction, and also show that this method can approximate the location and shedding of eddy Cameron better than the original DAC method. 
    more » « less
  5. ; ; ; ( , Plasma Processes and Polymers)
    Abstract

    Ion bombardment of photoresist materials during plasma etching results in the formation of a surface dense amorphous carbon (DAC) layer that contributes to both etch resistance and the development of surface roughness. Real‐time ellipsometric measurements/analysis reveals that a C4F8‐containing plasma interacts with an Ar‐plasma‐formed DAC layer to produce a modified DAC/fluorocarbon (FC) layer by FC deposition/diffusion of fluorine into the surface. The depletion of the DAC layer via modification and ion bombardment causes the etch rate of the bulk layer to increase. As the modified surface layer is formed, a noticeable decrease in surface roughness decrease is observed. These findings provide an understanding of the mechanisms of atomic layer etching processes in photoresist materials.

     
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email