In conclusion, the analysis of the similarity index of ChatGPT generated content, subject-wise, using various plagiarism checker software reveals several important findings. The ChatGPT generated content demonstrates a relatively low level of similarity with existing sources across different subjects in chemistry and majority of the paragraphs do not exhibit significant matches.The similarity index varies among different subjects. There are inconsistencies in the results obtained from different plagiarism checker software. While the similarity index provides a quantitative measure of similarity, it is crucial to conduct manual examination and contextual analysis of the matching paragraphs to determine the appropriateness, originality, and accuracy of the ChatGPT generated content.Plagiarism checker software should be used as complementary tools alongside manual assessment to make informed judgments about the quality and originality of the content generated by ChatGPT.Based on these findings, it can be concluded that ChatGPT, when trained on a comprehensive dataset of chemistry and allied sciences, has the potential to generate content with limited similarity to existing sources. Future research and improvements in NLP models can further enhance the reliability and credibility of the generated content, expanding the possibilities for scientific communication and knowledge dissemination in the field of chemistry and allied sciences.