Machine Learning Control for CO2-Fed Algae Reactors

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Solution Overview

Problem

Current carbon capture technologies face challenges such as high costs, energy inefficiencies, and logistical complexities associated with storage and transportation of captured CO2, particularly for industries with limited financial capabilities.

Innovation Solution

The implementation of a predictive control system for an algae reactor using machine-learning models to optimize CO2 capture and biomass production, which involves receiving correlation data, training the model, polling sensor data, and instructing the reactor to perform necessary actions based on predicted values.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional carbon capture and separation apparatus are implemented, then CO2 capture capability is improved, but system cost increases by 30% or more

Engineering Contradiction:

ImproveCO2 capture capabilityVSAvoidsystem cost

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent converts the harmful CO2 emissions into a beneficial resource by using algae to consume CO2 and produce biomass. The algae reactor system transforms waste CO2 from industrial processes into valuable biomass products, eliminating the need for expensive capture and storage infrastructure while creating economic value from what was previously a liability.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Solution Approach 2:

The algae-based system is self-sustaining, using natural photosynthesis to capture CO2 and produce biomass without requiring external energy inputs for capture operations. The system serves itself by using the CO2 it captures as food for algae growth, converting the capture process into a productive biological function rather than a mechanical separation process.

Inventive Principle:

Principle #25Self-service

2Reliability

If solvent-based capture techniques are used, then CO2 separation efficiency is improved, but energy consumption increases

Engineering Contradiction:

ImproveCO2 separation efficiencyVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent replaces mechanical solvent-based separation systems with a biological system. Instead of using energy-intensive chemical solvents and compression equipment, the system uses algae's natural photosynthetic machinery to selectively consume CO2, substituting biological processes for mechanical and chemical separation methods.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system changes the operational parameters from high-energy mechanical separation to low-energy biological consumption. By operating at ambient temperatures and pressures and using biological metabolism instead of thermal or pressure-driven separation, the system achieves CO2 removal with significantly lower energy input.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If underground CO2 storage is implemented, then CO2 sequestration capacity is improved, but environmental risks and public opposition increase

Engineering Contradiction:

ImproveCO2 sequestration capacityVSAvoidenvironmental risks

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

Instead of storing CO2 underground with associated leakage and contamination risks, the system converts CO2 into beneficial biomass products. The carbon is transformed from a harmful greenhouse gas into valuable algal biomass that can be used for food, feed, fertilizer, or biofuel production, eliminating sequestration risks while creating economic value.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Solution Approach 2:

The system recovers carbon from CO2 in the form of algal biomass rather than discarding it underground. The biomass can be harvested and utilized for various products, effectively recovering the carbon in a useful form and eliminating the need for permanent geological storage infrastructure.

Inventive Principle:

Principle #34Discarding and recovering

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach enhances the efficiency and effectiveness of carbon capture and storage by optimizing algae reactor operations, reducing energy consumption, and mitigating storage and transportation challenges.

Implementation Method 1

cultivating biomass such as microalgae which consumes carbon dioxide within a specially managed and controlled closed system

Methodology Applied

Scientific EffectPhotosynthesis: Photosynthesis

Data Source

PatentUS20250163358A1Machine learning analysis and control of co2-fed photobioreactors

Publication Date: 2025.05.22 PACIFIC AGRITEC LLC

AI summary

A system and method for predictive control of an algae reactor are disclosed. The method involves receiving correlation data from a correlation database, determining one or more correlations between parameters above a predetermined threshold, querying a parameter database to select associated data, training a machine-learning model based on the correlations and selected data, polling sensor data, predicting future values using the trained model, and instructing the algae reactor to perform required actions based on predicted values exceeding operational thresholds. The machine-learning model is trained to optimize predictions for improved control of the algae reactor.