Unveiling Evolutionary Path of Nanogenerator Technology: A Novel Method Based on Sentence-BERT

Area of Science:

• Materials Science and Engineering
• Computer Science
• Electrical Engineering

Background:

• Nanogenerator technology is rapidly advancing, driven by fields like AI and cloud computing.
• Identifying technological evolution paths is crucial for grasping trends and research focus.
• Previous methods often overlook semantic information and offer limited analytical perspectives.

Purpose of the Study:

• To propose a novel framework for analyzing the evolutionary path of nanogenerator technology.
• To overcome limitations of traditional bibliometric and patent analysis methods.
• To provide a multi-dimensional view of technological development and predict future applications.

Main Methods:

• Utilized Sentence-BERT for text vectorization and phrase mining to identify key technical themes.
• Employed clustering algorithms to group related research topics.
• Correlated themes using semantic similarity and visualized the evolutionary path with a "theme river map".

Main Results:

• Identified current technical themes of significant interest in nanogenerator research.
• Demonstrated a multi-dimensional evolutionary path by fusing themes from multi-source data.
• Provided an evolution analysis from frontier and technology research perspectives.

Conclusions:

• The proposed framework effectively unveils the evolutionary path of nanogenerator technology.
• Offers a more comprehensive understanding by integrating semantic information and multi-source data.
• Aids in discovering development focus and predicting future application prospects of nanogenerators.