Patents by Inventor Lok-kun Tsui

Lok-kun Tsui has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11825609
    Abstract: Highly conductive electrical traces formed over mechanical steps or on non-planar surfaces with linewidths of 10 to 100 ?m and a method for forming such electrical traces are disclosed. The method employs two steps, with the first step using an aerosol jet printing (AJP) process to form thin electrical traces that serve as the seed layers for the second step. The first step preferably employs multiple passes with the AJP to create multiple seed sub-layers with improved continuity and conductivity. In the second step, the seed layers are subjected to an electrodeposition process that forms the bulk of the thickness of the electrical traces. The electrodeposition process may include one, two, or three phases at corresponding low or high biases, with low biases providing denser, more highly conductive plating sub-layers, while high biases provide plating sub-layers having better gap bridging properties.
    Type: Grant
    Filed: March 9, 2021
    Date of Patent: November 21, 2023
    Assignees: National Technology & Engineering Solutions of Sandia, LLC, UNM Rainforest Innovations
    Inventors: Judith Maria Lavin, Lok-Kun Tsui
  • Patent number: 11283020
    Abstract: An resistive switch having a first platinum layer, an electrolyte layer that is formed by extrusion based additive manufacturing, a silver layer, and a second platinum layer, and methods of manufacturing and using the resistive switch.
    Type: Grant
    Filed: February 14, 2020
    Date of Patent: March 22, 2022
    Assignee: UNM RAINFOREST INNOVATIONS
    Inventors: Lok-kun Tsui, John Bryan Plumley, Fernando Garzon, Benjamin J. Brownlee, Thomas L. Peng
  • Publication number: 20180217086
    Abstract: A three-electrode mixed-potential electrochemical sensor coupled with an artificial neural network data analysis approach can extract concentrations from voltages and identify gas streams consisting of single and binary mixtures of NO2, NO, CO, and C3H8. By using the data from the sensors in biased and unbiased mode, single and binary mixtures can be identified with >98% accuracy identify all single and binary mixtures. While concentrations can be readily extracted from single test gas mixtures through a linear fit to the most sensitive electrode pair, binary mixture concentrations analyzed with an artificial neural network resulted in error distributions with a 95% peak accuracy in concentration with 80% of the data points having an accuracy at the 88% level. The sensor is suitable for control and monitoring of diesel and gasoline engines, turbines, steam power plants, and other combustion technologies.
    Type: Application
    Filed: February 2, 2017
    Publication date: August 2, 2018
    Inventors: Fernando Henry Garzon, Lok-kun Tsui