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Dataset reporting measurements of shot noise of tunneling current in La2-xSrxCuO4/La2CuO4/La2-xSrxCuO4 (LSCO/LCO/LSCO) heterostructures

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posted on 2020-01-21, 11:02 authored by Panpan Zhou, Liyang Chen, Yue Liu, Ilya Sochnikov, Anthony Bollinger, Myung-Geun Han, Yimei Zhu, xi he, Ivan Božović, Douglas Natelson

This dataset presents shot-noise measurements performed on LSCO-based tunnel junctions, in order to identify causes of the pseudogap associated with high-temperature superconductivity in copper oxides. The data reports measurements of shot noise of tunneling current in high-quality La2-xSrxCuO4/La2CuO4/La2-xSrxCuO4 (LSCO/LCO/LSCO) heterostructures fabricated using atomic-layer-by-layer molecular beam epitaxy, at four doping levels.

In the study, ALL-MBE was used to synethesise trilayer LSCO/LCO/LSCO films with LSCO doping level of x = 0.10, 0.12, 0.14, and 0.15, with film transition temperates of 28 K, 34 K, 37 K, and 38 K. Energy dispersive x-ray spectroscopy and atomic-resolution electron-energy-loss spectroscopy were used for La, Sr, and Cu elemental mapping. From these heterostructures, fabricated tunnel junction devices were fabricated using photolithography. Precision measurements of the bias dependence of the differential conductance (G = dI/dV, where I is the current and V is the voltage bias) were then performed using standard lock-in techniques. Two tunnel junctions were measured at each LSCO doping level in the top and bottom superconducting electrodes.

The dataset consists of a single compressed .rar archive, with eight subdirectories. Each subdirectory includes between 800-1100 files, with the data contained in each available in both .dat and .csv format.

Each subdirectory used the naming convention “lsco0pxxsn” where “xx” indicates the doping level of the La(2-x)Sr(x)CuO4 layers and n indicates either device 1 or device 2 for each doping.

The data within the subdirectories is as follows:

lsco0p10s1 (doping level .10, device 1)

lsco0p10s2 (doping level .10, device 2)

lsco0p12s1 (doping level .12, device 1)

lsco0p12s2 (doping level .12, device 2)

lsco0p14s1 (doping level .14, device 1)

lsco0p14s2 (doping level .14, device 2)

lsco0p15s1 (doping level .15, device 1)

lsco0p15s2 (doping level .15, device 2).

Each subdirectory contains four file types:

.dat files with filenames in the format “tt.00K_xxxxV.dat”. These are the raw data from the measurements of voltage noise, labeled by the temperature tt in Kelvin, and xxxx is the dc bias voltage applied to the series combination of the sample plus 380 kOhms of series resistance. These are two-column files. The first column is the frequency bin (Hz) and the second column is the voltage noise after the cross correlation (arb units set by the voltage gain of the preamplifiers; proportional to V^2/Hz).

.csv files which represent the same data as the .dat files above.

.dat files with filenames in the format “ttK_didv4noise.dat”. These contain the measured differential conductance data associated with each temperature, needed for fitting the frequency dependence of the noise. These files are five columns. The first column is the dc bias voltage across the sample itself, in volts. The third column is the dc current through the sample in Amps. The fifth column is the differential conductance in Siemens. (The second and fourth columns are lock-in readings in arb units used to calculate the fifth column.)

A single .xls file, containing the fit parameters obtained from the RsCp fitting analysis for each bias, with a separate sheet for each temperature. There are four columns for each temperature. Column 1 is the dc bias (in volts) applied across the series combination of the sample + 380 kOhms of series resistance. Column 2 is the fit magnitude of the voltage noise (in arb units). Column 3 is the noise magnitude converted into current noise, units of A^2/Hz, using the dI/dV at that bias. Column 4 is the RsCp fit parameter.

.rar files can be opened using open source decompression software, for example 7-Zip.

.dat files can be opened using text processing software. The .csv and .xls files can be opened using open source spreadsheet software such as OpenOffice Calc.


Funding

U.S. Department of Energy, Basic Energy Sciences, Materials Sciences and Engineering Division.

Gordon and Betty Moore Foundation’s EPiQS Initiative Grant GBMF4410

State of Connecticut

US Department of Energy, Basic Energy Sciences, Experimental Condensed Matter Physics award DE-FG02-06ER46337

NSF DMR-1704264

History

Research Data Support

Research data support provided by Springer Nature.