Microsoft technology licensing, llc (20240112760). CHEMICAL SYNTHESIS RECIPE EXTRACTION FOR LIFE CYCLE INVENTORY simplified abstract
Contents
- 1 CHEMICAL SYNTHESIS RECIPE EXTRACTION FOR LIFE CYCLE INVENTORY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 CHEMICAL SYNTHESIS RECIPE EXTRACTION FOR LIFE CYCLE INVENTORY - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 How does this technology compare to traditional methods of LCI creation for chemical products?
- 1.11 What are the limitations of using NLP for determining chemical synthesis recipes?
- 1.12 Original Abstract Submitted
CHEMICAL SYNTHESIS RECIPE EXTRACTION FOR LIFE CYCLE INVENTORY
Organization Name
microsoft technology licensing, llc
Inventor(s)
Kali Diane Frost of Indianapolis IN (US)
Bichlien Hoang Nguyen of Seattle WA (US)
Jake Allen Smith of Seattle WA (US)
Griffin Adams of New York NY (US)
Shang Zhu of Pittsburgh PA (US)
CHEMICAL SYNTHESIS RECIPE EXTRACTION FOR LIFE CYCLE INVENTORY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240112760 titled 'CHEMICAL SYNTHESIS RECIPE EXTRACTION FOR LIFE CYCLE INVENTORY
Simplified Explanation
The patent application abstract describes using natural language processing (NLP) to determine a recipe for a chemical synthesis described in a text to create a life cycle inventory (LCI).
- Method involves receiving a text describing a chemical product, analyzing it using NLP to determine a synthesis recipe with action and action metadata.
- Obtaining LCI information for the reactant, determining energy used for the action, and estimating environmental impact for the product.
Potential Applications
This technology could be applied in the fields of chemical engineering, environmental science, and sustainability research.
Problems Solved
This technology streamlines the process of determining the environmental impact of chemical products by automating the synthesis recipe extraction and LCI creation.
Benefits
The benefits of this technology include increased efficiency in assessing environmental impacts, improved accuracy in LCI creation, and potential cost savings in research and development processes.
Potential Commercial Applications
Potential commercial applications include software tools for environmental impact assessment, consulting services for sustainable product development, and integration into chemical manufacturing processes for green chemistry initiatives.
Possible Prior Art
One possible prior art could be the use of machine learning algorithms in chemical synthesis prediction and environmental impact assessment.
Unanswered Questions
How does this technology compare to traditional methods of LCI creation for chemical products?
This article does not provide a direct comparison between the proposed NLP-based method and traditional manual methods of LCI creation.
What are the limitations of using NLP for determining chemical synthesis recipes?
The article does not address potential limitations or challenges that may arise when using NLP to extract synthesis recipes from text descriptions.
Original Abstract Submitted
examples are disclosed that relate to using natural language processing (nlp) to determine a recipe for a chemical synthesis described in a text to create a life cycle inventory (lci). one example provides a method comprising receiving an input of a text from a publication comprising a description of a chemical product, and analyzing the text using nlp to determine a recipe for the chemical synthesis, the recipe comprising and action and action metadata, the action metadata comprising a reactant. the method further discloses obtaining lci information for the reactant, determining an energy utilized for the action, and creating an estimate of an environmental impact for the product.
