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The author analyzes recent earnings reports from tech giants using a “two phases, three steps” framework, arguing that the current AI boom is primarily driven by investment rather than a surge in total factor productivity, and will use this framework to analyze the superconductivity industry chain.
The author argues that discovering higher-temperature superconductors—moving from the current ~150K record toward room-temperature (293K) superconductivity at ambient pressure—would make an ideal AI benchmark for engineering with major benefits for humanity.
This article explores whether current AI models could drive breakthrough scientific discoveries, such as new materials, by accelerating hypothesis generation and research, drawing parallels to the LK-99 superconductor episode.
This paper reports on the study of superconductivity in a monolayer cuprate material with a single CuO2 plane, which could advance understanding of high-temperature superconductors.
Researchers from Peking University report new evidence that quantum geometry plays a key role in the behavior of strange metals, potentially advancing understanding of high-temperature superconductivity. The study was published in Physical Review Letters.
Researchers from Peking University's School of Physics have discovered a hidden geometric pattern governing electron behavior in quasicrystals, offering a new perspective on quantum materials and establishing a theoretical foundation for future research into superconductivity and quantum technologies.
An experiment running the same research prompt about LENR and superconductivity through six AI systems in five languages reveals significant linguistic bias, with non-English queries surfacing information about real industrial commitments that English-only searches miss.