Measuring and analysing low frequency noise in nano devices

doi:10.1038/protex.2010.202

Method Article

Measuring and analysing low frequency noise in nano devices

https://doi.org/10.1038/protex.2010.202

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Low frequency noise gives additional informations to DC current in nanodevices such as estimation of number/position of defects in nanotransistors [1-14] and inelastic resonant energy levels in molecular devices [15-16]. It provides also the charge sensitivity limit [1,5] for sensors and memories. However, low frequency noise measurements remain marginal for device electrical characterization which is probably due to additional efforts required for non specialists to measure and analyse such signals. This is particularly true for nanodevices where current level is low and noise more difficult to measure. Here, we detail a protocol including experimental setup optimization, developed automation softwares and data analysis. An example of low frequency noise study of a silicon nanowire transistor is shown.

Nanoscience and technology

Low-frequency noise

Random Telegraph Signal

automation software

Nano MOSFETs

nanowire

single electron

Coulomb repulsion

A personal computer (Macintosh, Unix/Linux or Windows operating system).
An electrical measurement station.
An ultra low noise DC power supply (e.g. Shibasoku PA15A1) or batteries (Fig.1)
RC filters (Fig.1)
A current/voltage pre-amplifier (e.g. DL instrument DL 1211 or Stanford Research SR 570)(Fig.1)
A spectrum analyzer (e.g. Agilent 35570 or 35665) (Fig.1)
A php server (since latest versions of php might be incompatible with our scripts, we recommand to "download version 1.7 from Easyphp":http://chalet-bay.com/downloads/easyphp1-7_setup.exe)
Our automated softwares for "web interface":http://chalet-bay.com/downloads/programs_php.zip and "OriginC programs":http://chalet-bay.com/downloads/programs_originC.zip
Origin plotting software (From OriginLabs: minimum v.7 with OriginC Language updated)

Experimental setup optimization:

Electrical connexions are shown in Figure 1. Each electrical measurement system has some noise, usually at the utility frequency 50-60 Hz, due to ground loops. For sensitive nanodevices that can potentially detect the elementary charge, this extrinsic noise can hide the target signal. Therefore, the noise contribution of each connected equipment to the electrical measurement system should be carrefully investigated. For example, vacuum pumps or temperature controllers may increase 50 Hz noise amplitude. We consider that 50 Hz noise amplitude is reasonable if (SIxΔf)^0.5<0.1%xId, where SI is the power spectrum current peak noise, Δf~1.5 Hz is the 50 Hz peak bandwidth and Id the drain DC current.
Pre-amplifier parameters: The selection of preamplifier’s specifications are detailed in caption of Figure 1. If the rise time can be tuned, it should be used as a low pass filter to reduce the 50 Hz noise for very low frequency signals such as Random Telegraph Signal [1] if the resonant frequency is much lower than 50 Hz.
Dynamic Signal Analyser (DSA) parameters: We use the window Hanning for Fast Fourier Transform analysis with the maximum number of sampling points that the DSA provides (e.g. 1600). The input is set to ground and the ground of the DSA linked physically to the Faraday box of the electrical measurement system. For power specra acquisition, we select the average mode with a typical average of 100 spectra (meanwhile, it is possible to save curves in the time domain). Frequency axis is in log scale.
Data acquisition with the floppy disk: In order to use our automation softwares, spectra should be stored with the extension .DT and time domain datas with the extension .TP (Figure 2a). In order to obtain a spectrum covering the frequency range from 0.1Hz to 100kHz, experimentally 2 to 5 spectra are taken (depending on the number of samples per spectrum). No order (in file naming) is required for measurements in the time domain, but should be successive for a given channel resistance. Measurements in the time domain are optional.

Automation software (web interface):

1- Download and install the php server and our developed softwares (in the www folder)

2- Edit racine.php file and replace K:\test by the emplacement where you want to store datas. Replace the next constant the path to reach sdftoasc file.

3- Browse the local web and select exec>formdatatreatment

4- Fill in datas as shown in Figure 2c.

5- Press treatment button for converting the datas. Text lines will appear in the browser as shown in Figure 2c. These lines should be copied and past in the Labtalk window of origin (see OriginC interface)

6- Folders with original and converted files are automatically created (see Figure 2d).

Automation software (OriginC interface):

1- Download and install our developed OriginC code. All the procedure is detailed in the Readme file.

2- Double click on the new empty origin file (Figure 3a).

3- Paste the text lines copied from the web browser (Figure 3b).

4- Power spectra as in Figure 3c and time domain datas will be automatically created.

Calibration procedure:

Measuring the power spectrum current noise of known resistors is a safe procedure to verify that the white noise of amplitude 4kT/R is measured where k is the Boltzman constant, T the temperature and R the resistance value. It also shows the maximum bandwidth of the preamplifier. Figure 4c shows such calibration procedure with 4 different resistors and Stanford research SR570 preamplifier. Frequency bandwidth is much smaller than for DL1211 preamplifier at low gains and we therefore use the latter one for noise measurement in silicon nanowires.

Power spectrum noise analysis:

An example of power spectrum current noise spectra SI at different gate voltages for a silicon nanowire transistor as in [1] is shown in Figure 5a. Normalized noise makes the analyzis more direct. SI can be normalized by DC current I squared or transconductance gm squared [1,5,13] (see Figure 5b). The bell shape in figure 5b is due to a maximum noise at resonant energy level for a defect located close to the silicon nanowire. It can be fitted with equations detailed in [1].

Random telegraph signal analysis:

Random Telegraph Signal (RTS) is a two levels fluctuation of current mostly related to the trapping/detrapping of an electron in a defect close to the transistor’s channel [4]. Figure 5a is an example of RTS for a silicon nanowire as in [1] and Figure 5c the histogram of drain current. To evaluate up and down time constants, RTS is first cleaned as a perfect two levels system by substracting an average value (e.g. red line in Figure 5a) and getting the sign (e.g. with the functionSIGN() from Excel software). The modified signal is shown in Figure 5b and its histogram in Figure 5d. Finally, using the our web-based RTS function, we get from this point list each down and up times of our RTS (Figure 5e). If the two levels signal is not clear enough, this should be done manually.

The complete measurement and analysis of a device at different biasing points takes one working day or more if many RTSs to treat.

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(4)F. Liu and K.L.Wang, Correlated random telegraph signal and low-frequency noise in carbon nanotube transistors. Nanolett. 8, 147-151 (2008).

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Bouchiat, D. Fraboulet, D. Mariole, J. Gautier and V.

Safarov, “Electronic transport properties of single-crystal

silicon nanowires fabricated using an atomic force

microscope”, Physica E 13, 999-1002 (2002)

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The authors thank H. Inokawa for helpful advices for experimental setup optimization.

No conflicting financial interests

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Measuring and analysing low frequency noise in nano devices

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