The authors clarified that their claims of novelty referred to the materials being new to their prediction platform, not necessarily new to the broader scientific community. The article has been updated in both HTML and PDF versions to reflect this clarification, with a detailed breakdown of textual changes available as supplementary information.

Post-publication peer review involved a manual re-analysis of diffraction patterns. This re-analysis confirmed the prediction platform's accuracy in 36 out of 40 reported successful syntheses. The remaining four compounds were deemed inconclusive.

The original article detailed the development and application of an autonomous system capable of designing, synthesizing, and characterizing new inorganic materials at an accelerated pace. This type of automated research platform represents a significant advancement in materials science, potentially speeding up the discovery and development of new materials for various applications, including energy storage, catalysis, and electronics.

The use of computational methods, characterization techniques, and analytical tools are central to the autonomous laboratory's operation. The system leverages predictive algorithms to identify promising material candidates, then automatically synthesizes and analyzes these materials, creating a feedback loop for continuous learning and optimization.

While the correction addresses specific concerns about the initial publication, the underlying concept of autonomous materials discovery remains a promising area of research. Such systems have the potential to revolutionize the field by reducing the time and resources required for materials innovation. The development of robust and reliable autonomous laboratories is crucial for accelerating scientific progress and addressing global challenges that require advanced materials solutions.