公开(公告)号：US20220284269A1

公开(公告)日：2022-09-08

申请号：US17653077

申请日：2022-03-01

Applicant: LanzaTech, Inc.

Inventor： James Howden Daniell ,  Steven Samuel Glasker ,  Michael Emerson Martin ,  Melvin Moore ,  Michael James Harry Mawdsley ,  Jim Jeffrey Daleiden

IPC: G06N3/04 ,  G06K9/62 ,  C12P7/06

Abstract: This disclosure relates to analyzing a fermentation process that occurs in a bioreactor. Such a fermentation process may involve microbes consuming a substrate, and producing various metabolites. A computing device may train and execute one or more machine learning models to analyze such a fermentation process. Such a machine learning model may be configured to determine a current fermentation state of such a fermentation process as one example. As another example, a machine learning model may be configured to predict metabolite production of a fermentation process based on historical fermentation data and a window of control decisions for the fermentation process.

公开(公告)号：US20230407271A1

公开(公告)日：2023-12-21

申请号：US18339050

申请日：2023-06-21

Applicant: LanzaTech, Inc.

Inventor： Sean Dennis Simpson ,  Jennifer Rosa Holmgren ,  James MacAllister Clomburg ,  Jim Jeffrey Daleiden ,  Audrey Jean Harris ,  Stephanie Rhianon Jones ,  Michael Koepke ,  Timothy James Politano

IPC: C12N9/02 ,  C12P5/02

CPC classification number: C12N9/0069 ,  C12Y113/12019 ,  C12P5/026

Abstract: Methods and microorganisms are genetically engineered to continuously produce ethylene by microbial fermentation, particularly by the microbial fermentation of a gaseous substrate. The microorganisms are C1-fixing. Further, the gaseous substrate comprises CO2 and an energy source. The production of ethylene can be improved by varying promoters or nutrient limiting means.