17937001. CHEMICAL SYNTHESIS RECIPE EXTRACTION FOR LIFE CYCLE INVENTORY simplified abstract (Microsoft Technology Licensing, LLC)
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 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 17937001 titled 'CHEMICAL SYNTHESIS RECIPE EXTRACTION FOR LIFE CYCLE INVENTORY
Simplified Explanation
The abstract describes using natural language processing to determine a recipe for a chemical synthesis described in a text to create a life cycle inventory.
- Analyzing text using NLP to determine a recipe for chemical synthesis
- Obtaining LCI information for reactant
- Determining energy utilized for the action
- Creating an estimate of environmental impact for the product
Potential Applications
This technology could be applied in various industries such as pharmaceuticals, chemicals, and environmental science for efficient and sustainable product development.
Problems Solved
This technology helps in automating the process of determining chemical synthesis recipes and estimating environmental impacts, saving time and resources.
Benefits
The benefits of this technology include improved efficiency in product development, reduced environmental impact assessments, and enhanced sustainability practices.
Potential Commercial Applications
The potential commercial applications of this technology include software development for chemical synthesis optimization, environmental impact assessment tools, and sustainability consulting services.
Possible Prior Art
One possible prior art could be the use of machine learning algorithms for chemical synthesis prediction and optimization in the pharmaceutical industry.
Unanswered Questions
How does this technology compare to traditional methods of determining chemical synthesis recipes?
This technology offers a more automated and efficient approach compared to traditional manual methods, saving time and resources in product development processes.
What are the limitations of using natural language processing for determining chemical synthesis recipes?
Limitations may include accuracy of NLP algorithms in understanding complex chemical reactions and the need for validation by experts in the field to ensure the reliability of the results.
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.
