Du H Nguyen

20210302452, Sep 30, 2021

Jun 10, 2021

17/344183

- Livermore CA, US
Eric B. Duoss - Dublin CA, US
Du Nguyen - Fremont CA, US
William Smith - Oakland CA, US
Sachin Subhash Talathi - Pleasanton CA, US
Aaron Creighton Wilson - Livermore CA, US

G01N 35/00
G05B 13/02
G05D 7/06
B01L 3/00
G01N 15/14
G01N 15/00

A system is provided to automatically monitor and control the operation of a microfluidic device using machine learning technology. The system receives images of a channel of a microfluidic device collected by a camera during operation of the microfluidic device. Upon receiving an image, the system applies a classifier to the image to classify the operation of the microfluidic device as normal, in which no adjustment to the operation is needed, or as abnormal, in which an adjustment to the operation is needed. When an image is classified as normal, the system may make no adjustment to the microfluidic device. If, however, an image is classified as abnormal, the system may output an indication that the operation is abnormal, output an indication of a needed adjustment, or control the microfluidic device to make the needed adjustment.

20200315975, Oct 8, 2020

Apr 3, 2019

16/374629

- Livermore CA, US
Eric B. Duoss - Dublin CA, US
Jeremy Lenhardt - Tracy CA, US
Du Nguyen - Fremont CA, US
Thomas S. Wilson - San Leandro CA, US

A61K 9/50
C08L 83/04
A61K 9/48
C09D 11/102
C09D 11/03
B33Y 10/00
B33Y 70/00
B33Y 80/00
B29C 64/118

According to one embodiment, a core-shell microsphere includes a polyorganosiloxane shell, and a core inside the shell, the core having a carrier and at least one component, where the at least one component is configured to be released post processing. In addition, an average diameter of the polyorganosiloxane shell is in a range of greater than about 1 micron to less than about 100 microns.

20200215480, Jul 9, 2020

Jan 9, 2019

16/243810

- Livermore CA, US
Du NGUYEN - Fremont CA, US
Joshuah K. STOLAROFF - Oakland CA, US

B01D 53/22
B33Y 80/00
B33Y 10/00
B01D 71/02
B01D 71/70
B01D 67/00
B01D 53/02
B01J 20/28

The present disclosure relates to a transport mechanism apparatus for transporting at least one of a gas or a fluid. The transport mechanism may have an inlet, an outlet and a triply periodic minimal surface (TPMS) structure. The TPMS structure is formed in a layer-by-layer three dimensional (3D) printing operation to include cells propagating in three dimensions, where the cells include wall portions having openings, and where the cells form a plurality of flow paths throughout the transport mechanism from the inlet to the outlet, and where the cells form the inlet and the outlet.

20200190345, Jun 18, 2020

Oct 21, 2019

16/659025

- Livermore CA, US
Eric B. Duoss - Dublin CA, US
Jeremy Lenhardt - Tracy CA, US
Du Nguyen - Fremont CA, US
Thomas S. Wilson - San Leandro CA, US
Alexandra Golobic - Pleasanton CA, US

C09D 11/102
C09D 11/037
B33Y 10/00
B33Y 70/00
B33Y 80/00
B33Y 40/00
B29C 64/314
B29C 64/106

According to one aspect of an inventive concept, an ink formulation for forming a gas blown polysiloxane product includes a polysiloxane having at least one vinyl group, a silane crosslinker, a catalyst, a gas blowing agent, and a thixotropic agent. According to another aspect of an inventive concept, a product includes a three-dimensional printed polymer structure formed from at least one filament. The three-dimensional printed polymer structure has a plurality of layers arranged in a geometric pattern, the layers being formed from the at least one filament, where the at least one filament comprises a polysiloxane material having a plurality of closed cell pores formed therein.

20200024465, Jan 23, 2020

Dec 6, 2018

16/212525

- Livermore CA, US
Theodore F. Baumann - Discovery Bay CA, US
Eric B. Duoss - Dublin CA, US
Joshua D. Kuntz - Livermore CA, US
Robin Miles - San Ramon CA, US
Du Nguyen - Fremont CA, US
Christopher Spadaccini - Oakland CA, US
Tayyab I. Suratwala - Pleasanton CA, US
Timothy Dexter Yee - Alameda CA, US
Cheng Zhu - Livermore CA, US
Cameron David Meyers - Minneapolis MN, US
Nikola Dudukovic - Hayward CA, US
Tyler Fears - Pleasanton CA, US
Fang Qian - Santa Cruz CA, US
Koroush Sasan - Pleasanton CA, US
Joel Destino - Omaha NE, US

C09D 11/03
C09D 11/02
C09D 11/033
B33Y 70/00
C03B 19/01
B33Y 10/00

According to one embodiment, a method includes forming a structure by printing an ink, the ink including a glass-forming material, and heat treating the formed structure for converting the glass-forming material to glass. According to another embodiment, an ink composition includes a glass-forming material and a solvent.

20190234976, Aug 1, 2019

Apr 5, 2019

16/376380

- Livermore CA, US
Eric B. Duoss - Dublin CA, US
Du Nguyen - Fremont CA, US
William Smith - Oakland CA, US
Sachin Subhash Talathi - Pleasanton CA, US
Aaron Creighton Wilson - Livermore CA, US

G01N 35/00
G05B 13/02
G05D 7/06
B01L 3/00
G01N 15/00

A system is provided to automatically monitor and control the operation of a microfluidic device using machine learning technology. The system receives images of a channel of a microfluidic device collected by a camera during operation of the microfluidic device. Upon receiving an image, the system applies a classifier to the image to classify the operation of the microfluidic device as normal, in which no adjustment to the operation is needed, or as abnormal, in which an adjustment to the operation is needed. When an image is classified as normal, the system may make no adjustment to the microfluidic device. If, however, an image is classified as abnormal, the system may output an indication that the operation is abnormal, output an indication of a needed adjustment, or control the microfluidic device to make the needed adjustment.

20180311663, Nov 1, 2018

Apr 26, 2017

15/498282

- Livermore CA, US
Eric Duoss - Dublin CA, US
Du Nguyen - Fremont CA, US
William Smith - Oakland CA, US
Sachin Subhash Talathi - Pleasanton CA, US
Aaron Creighton Wilson - Livermore CA, US

B01L 3/00
G05B 13/02
G05D 7/06
G01N 35/00

A system is provided to automatically monitor and control the operation of a microfluidic device using machine learning technology. The system receives images of a channel of a microfluidic device collected by a camera during operation of the microfluidic device. Upon receiving an image, the system applies a classifier to the image to classify the operation of the microfluidic device as normal, in which no adjustment to the operation is needed, or as abnormal, in which an adjustment to the operation is needed. When an image is classified as normal, the system may make no adjustment to the microfluidic device. If, however, an image is classified as abnormal, the system may output an indication that the operation is abnormal, output an indication of a needed adjustment, or control the microfluidic device to make the needed adjustment.