Two Indian researchers have claimed to achieve superconductivity at room temperature, sending the world of physicists into a state of frenzy.
As expected, these claims have raised several eyebrows. Also, a series of strange events involving the impersonation of a renowned physicist through email has added more to the bizarreness of this situation.
But first, let’s talk about superconductivity. Why is it so important?
Superconductivity is the state when there is zero electrical resistance in a material – meaning that electrons can flow freely through the object without any hindrance. So far, this state has been achieved only by bringing the materials to extremely cold temperatures.
But if superconductivity is made possible at room temperature, it would facilitate free transport of energy, incredibly fast computers – basically, change the world as it is now.
Last month, Dev Thapa and Anshu Pandey, chemical physicists from the Indian Institute of Science in Bangalore, India, posted a paper on arXiv claiming they have succeeded in achieving “superconductivity at ambient temperature and pressure conditions.”
What’s more baffling is that they did it by using a matrix of gold and silver particles — materials that have never exhibited superconductivity even at incredibly cold temperatures.
So physicists from all of the world began to take a closer look at the data as something didn’t seem right. Finally, Brian Skinner, a physicist at MIT, found a strange correlation between two independent measurements in Thapa and Pandey’s arXiv paper.
9/ But when I zoomed in closely on the figure, I saw something very surprising. Look closely at the green and blue data points here: pic.twitter.com/AEKqGOfks7
— Brian Skinner (@gravity_levity) August 10, 2018
The green and blue dots in the graph above represents the noise measured during two separate experiments run by the researchers to test the magnetic susceptibility of their superconducting material.
However, noise by definition is random. So there shouldn’t be any correlation between the noise measured in both the experiments. Yet the blue dots are exactly correlated to the green dots only a little offset.
Now, this graph could be the consequence of serial mistakes — when the same dataset is processed twice with a mistake made in the previous run. But its highly unlikely which raises the possibility of data misrepresentation or worse: faking of data.
Faking of data has severe repercussions like getting stripped of degree and retraction of papers leading scientific journals. We hope that’s not the case here.
There is also a lot of pressure on the duo researchers to share their test samples and data sets to the research community. But for now, they are keeping their samples and data under wraps while the scientific community awaits some resolution.
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