NIR Biomass Model for Rapid Saccharification Prediction
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Solution Overview
Problem
Current methods for analyzing biomass composition and conversion efficiency are slow, expensive, and require skilled labor, limiting their use in selecting improved plant biomass feedstocks and monitoring process intermediates, which hinders the development of economically viable biofuel processes.
Innovation Solution
Development of Near Infrared (NIR) models that characterize plant biomass components, predicting saccharification efficiency and biofuel yield by correlating spectroscopic data with chemical composition and processing conditions, enabling rapid and cost-effective selection of feedstocks and optimization of processing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional wet chemical methods are used to analyze biomass composition, then measurement precision is achieved, but analysis time and cost increase significantly
Solution Approach 1:
The patent replaces traditional wet chemical analysis methods with Near-Infrared Spectroscopy (NIR), substituting a mechanical/optical measurement system for a chemical analysis system. NIR spectroscopy uses infrared light to excite molecular vibrations that correspond to specific chemical bonds, enabling rapid non-contact measurement of biomass composition without requiring time-consuming laboratory processing.
Solution Approach 2:
The patent creates a predictive model that copies the results of complex wet chemical analysis through NIR spectroscopy. By calibrating the NIR instrument against reference chemical analyses, the system generates predictive predictions of biomass composition that replicate the accuracy of traditional methods but with much faster analysis time, effectively creating a virtual copy of the analysis process.
2Measurement precision
If traditional analytical methods are used for biomass conversion efficiency determination, then measurement precision is achieved, but device complexity and operational difficulty increase
Solution Approach 1:
The patent replaces complex laboratory infrastructure including incubators, spectrophotometers, and multiple processing steps with a portable NIR instrument that performs all measurements through simple optical scanning. This substitution dramatically reduces device complexity while maintaining the ability to determine conversion efficiency through predictive modeling.
Solution Approach 2:
The NIR system performs self-contained analysis without requiring complex laboratory support systems. The instrument automatically acquires spectral data, applies calibrated predictive models, and outputs results independently, eliminating the need for skilled laboratory personnel and complex infrastructure while maintaining measurement precision.
3Measurement precision
If comprehensive biomass analysis is performed to select improved feedstocks, then selection accuracy improves, but productivity of the overall process decreases
Solution Approach 1:
The patent replaces time-consuming laboratory-based feedstock evaluation with rapid NIR spectral scanning that can be performed in the field or at the point of receipt. This substitution enables comprehensive analysis of multiple feedstock samples simultaneously, dramatically increasing throughput while maintaining selection accuracy through calibrated predictive models.
Solution Approach 2:
The patent performs preliminary characterization of biomass feedstocks using NIR spectroscopy before they enter the conversion process. By rapidly assessing key compositional parameters and conversion efficiency predictions upfront, the system enables informed feedstock selection and process optimization without delaying subsequent production activities, thereby maintaining high productivity.
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
Enables rapid and accurate prediction of biomass composition and conversion efficiency, facilitating the development of improved plant varieties and processes, optimizing biofuel production and reducing costs in biorefineries.
Implementation Method 1
subjecting a plurality of diverse biomass feedstock samples of the same type to near infrared spectroscopy to produce NIR spectroscopic data from each sample
Data Source
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AI summary
Methods and materials for measuring the composition of plant biomass and predicting the efficiency of conversion of such biomass to various end products under various processing conditions are disclosed. For example, methods and materials for identifying plant material having higher levels of accessible carbohydrate, as well as materials and methods for processing plant material having higher levels of accessible carbohydrate are disclosed. Also disclosed are computer-implemented methods and systems that provide improved economic efficiencies to biorefineries.