READ ME File For ‘Dataset for Doctoral thesis ‘’Random telegraph signals in silicon single-electron devices for quantum technologies’’ ‘

[Revision record]
2020_05_27 Initial version was created.

Dataset DOI: https://doi.org/10.5258/SOTON/D1378

ReadMe Author: Kouta Ibukuro, University of Southampton

This dataset supports the doctoral thesis:
AUTHORS:  Kouta Ibukuro 
TITLE: Random telegraph signals in silicon single-electron devices for quantum technologies

This dataset is not a standard dataset, and it is called ‘metadata’ set.
That is, four datasets that are already available in public are also included in this dataset, 
as well as another, new dataset that contains data which are not included in the previously published datasets.
The DOI’s of the previously published dataset and associated papers were linked to this dataset.
In this readme file, it is aimed to accurately link figures in the thesis with the data, 
regardless of whether it has been already published and regenerated for thesis or it has not been published yet.

This ‘metadata’set contains all the figures which show the one that require data to be generated, such as measurement results and their analyses etc. 
Data, or its reference to the already published dataset, used to generate the figures are explained in this readme file.
Schematics and photos do not require any data to be generated, and therefore no data was associated with them.

Below is a list of dataset that are already published.

Dataset 1; Dataset for manipulation of random telegraph signals in a silicon nanowire transistor with a triple gate
DOI/Handle/URI: https://doi.org/10.5258/SOTON/D0555

Dataset 2; Dataset for ’single electron memory effect using random telegraph signals at room temperature’
DOI/Handle/URI: https://doi.org/10.5258/SOTON/D0843

Dataset 3; Raw data for ’random-telegraph-noise and wave-particle-duality found in a silicon nano-wire’
DOI/Handle/URI: https://doi.org/10.5258/SOTON/D0507

Dataset 4; Title: Dataset for Random telegraph signals caused by a single dopant in a metal oxide semiconductor field effect transistor at low temperature
DOI/Handle/URI: https://doi.org/10.5258/SOTON/D1193

If the data has not been published, the corresponding data should be found in this ‘metadata’ set.

—Chapter 2— 
Figure 2.14
Following data in Dataset 1 was used;
x02y03xx02yy01_timesampling_TG50m_FGn14.csv

Drain_I was plotted against time after 400s, in order to focus on RTSs.

Figure 2.16
Following data in Dataset 1 was used;
x02y03xx02yy01_timesampling_TG50m_FGn04.csv

Drain_I was plotted against time after 200s, in order to focus on RTSs.

—Chapter 3—

Figure 3.18
Following data was used;
2017-06-30-Kouta-B2-7-13.csv

Drain_I was plotted against Gate_V in log scale.

Figure 3.19
Following data was used;
2017-06-30-Kouta-B2-7-13-idvd.csv

Drain_I was plotted against Drain_V in linear scale.

Figure 3.26
Following data were used;
C-V Sweep [(1) ; 19_11_2019 14_05_17].csv
C-V Sweep [(1) ; 19_11_2019 14_10_02].csv

The method to generate the figure was explained in the main text, p37.

Figure 3.28
Following data in Dataset 4 were used;
Advanced split CV inversion Vwell 0V [(1) ; 19_11_2019 14_24_26].csv
Advanced split CV inversion Vwell 0V [(2) ; 19_11_2019 14_50_06].csv

The method to generate the figure was explained in the main text, p37.

Figure 3.30
Following data in Dataset 4 were used;
Advanced split CV accumulation VsVd 0V [(2) ; 19_11_2019 15_48_39].csv
Advanced split CV accumulation VsVd 0V [(1) ; 19_11_2019 15_23_34].csv

The method to generate the figure was explained in the main text, p37.

Figure 3.31
Following data were used;
W4ChipBX01Y03XX03YY04_BFG_TFGfloating_TG_0_5prober.csv
W4ChipBX01Y03XX03YY04_TFG_BFGfloating_TG_0_5prober.csv
W4ChipBX01Y03XX03YY04_TG_FG1and2_0_5prober.csv

Drain_I was plotted against Gate_V in log scale.

Figure 3.32
Following data were used;
W4ChipA1X01Y04XX04YY02_TG_FG1and2_0_5prober.csv
W4ChipA1X01Y04XX04YY02_BFG_TG0_TFGfloating_5prober.csv
W4ChipA1X01Y04XX04YY02_TFG_TG0_BFGfloating_5prober.csv

Drain_I was plotted against Gate_V in log scale.

Figure 3.33
Following data were used;
W4ChipA1X01Y04XX03YY04_TG_FG1and2_5prober.csv
W4ChipA1X01Y04XX03YY04_BFG_TG0_TFGfloating_5prober.csv
W4ChipA1X01Y04XX03YY04_TFG_TG0_BFGfloating_5prober.csv

Drain_I was plotted against Gate_V in log scale.

Figure 3.37
Following data were used;
SET057_W5A_X04Y02_FG1_rest_floating_; 10_04_2019 11_21_35].csv
SET057_W5A_X04Y02_FG2_rest_floating_; 10_04_2019 11_22_55].csv
SET057_W5A_X04Y02_TG_rest_floating_; 10_04_2019 11_19_55].csv

Drain_I was plotted against Gate_V in log scale.

—Chapter 4— 

Figure 4.1, 4.2
Following data were used;
x02y03xx04yy01_prsw_TG_snsw_LRFG.csv

Drain_I was plotted against Gate_V in log scale in Figure 4.1.
The method to generate Figure 4.2 from the data was explained in the main text, p46.


Figure 4.3
Following data was used;
x02y03xx04yy02_prsw_TG_snsw_LRFG.csv

Drain_I was plotted against Gate_V in log scale in Figure 4.3.

Figure 4.4, 4.5, 4.10 
Following data in Dataset 1 were used;
prsw_TG_p15 [(1) ; 03_05_2018 11_58_52].csv (For Figure 4.4,5,10)
prsw_TG_p14 [(1) ; 03_05_2018 11_57_54].csv (For Figure 4.4,5,10)
prsw_TG_p12 [(1) ; 03_05_2018 11_56_56].csv (For Figure 4.4,5,10)
prsw_TG_p10 [(1) ; 03_05_2018 11_55_58].csv (For Figure 4.4,5,10)
prsw_TG_p08 [(1) ; 03_05_2018 11_54_59].csv (For Figure 4.4,5,10)
prsw_TG_p06 [(1) ; 03_05_2018 11_54_01].csv (For Figure 4.4,5,10)
prsw_TG_p04 [(1) ; 03_05_2018 11_53_03].csv (For Figure 4.4,5,10)
prsw_TG_p02 [(1) ; 03_05_2018 11_52_05].csv (For Figure 4.4,5,10)
prsw_TG_0_[(1); 03_05_2018 11_28_03].csv     (For Figure 4.5)
prsw_TG_n02 [(1) ; 03_05_2018 11_50_09].csv (For Figure 4.4,5,10)
prsw_TG_n04 [(1) ; 03_05_2018 11_49_11].csv (For Figure 4.4,5,10)
prsw_TG_n06 [(1) ; 03_05_2018 11_48_13].csv (For Figure 4.4,5,10)
prsw_TG_n08 [(1) ; 03_05_2018 11_47_15].csv (For Figure 4.4,5,10)
prsw_TG_n10 [(1) ; 03_05_2018 11_46_17].csv (For Figure 4.4,5,10)
prsw_TG_n12 [(1) ; 03_05_2018 11_45_19].csv (For Figure 4.4,5,10)
prsw_TG_n14 [(1) ; 03_05_2018 11_44_21].csv (For Figure 4.4,5,10)
prsw_TG_n15 [(1) ; 03_05_2018 11_43_22].csv (For Figure 4.4,5,10)

See Dataset 1 for how the figures were generated.

Figure 4.6, 4.7, 4.8, 4.9, 4.11
Following data in Dataset 1 were used;
I_V-t Sampling FG 0 TG p040 [(1) ; 04_05_2018 04_38_10].csv (For Figure 4.7, 9, 11)
I_V-t Sampling FG 0 TG p035 [(1) ; 04_05_2018 04_22_42].csv (For Figure 4.7, 9, 11)
I_V-t Sampling FG 0 TG p030 [(1) ; 04_05_2018 04_07_17].csv (For Figure 4.6, 7, 8, 9, 11)
I_V-t Sampling FG 0 TG p025 [(1) ; 04_05_2018 03_51_40].csv (For Figure 4.7, 9, 11)
I_V-t Sampling FG 0 TG p020 [(1) ; 04_05_2018 03_36_18].csv (For Figure 4.7, 9, 11)
I_V-t Sampling FG 0 TG p015 [(1) ; 04_05_2018 03_20_53].csv (For Figure 4.7, 9, 11)

See Dataset 1 for how the figures were generated.

Figure 4.15, 4.16, 4.18
Following data in Dataset 2 were used 
x02y02xx02yy01_TG_500m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_600m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_700m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_800m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_900m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1000m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1100m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1200m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1300m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1400m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1500m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1600m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1700m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1800m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_1900m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)
x02y02xx02yy01_TG_2000m_FG_ground_D_200mV_100us_500ms_20s_delay.csv (For Figure 4.15, 16, 18)

See Dataset 2 for how the figures were generated.

Figure 4.19
Following data in Dataset 3 were used
x02y03xx02yy01_prsw_TG_FGn1.5.csv
x02y03xx02yy01_prsw_TG_FGn14.csv
x02y03xx02yy01_prsw_TG_FGn12csv
x02y03xx02yy01_prsw_TG_FGn10.csv
x02y03xx02yy01_prsw_TG_FGn08.csv
x02y03xx02yy01_prsw_TG_FGn06.csv
x02y03xx02yy01_prsw_TG_FGn04.csv
x02y03xx02yy01_prsw_TG_FGn02.csv
x02y03xx02yy01_prsw_TG_FG000.csv
x02y03xx02yy01_prsw_TG_FGp15.csv
x02y03xx02yy01_prsw_TG_FGp14.csv
x02y03xx02yy01_prsw_TG_FGp12csv
x02y03xx02yy01_prsw_TG_FGp10.csv
x02y03xx02yy01_prsw_TG_FGp08.csv
x02y03xx02yy01_prsw_TG_FGp06.csv
x02y03xx02yy01_prsw_TG_FGp04.csv
x02y03xx02yy01_prsw_TG_FGp02.csv


Figure 4.20, 4.21, 4.22, 4.23, 4.24, 4.25
Following data in Dataset 1 were used
x02y03xx02yy01_timesampling_TG50m_FGn16.csv  (For Figure 4.20, 21, 23, 25)
x02y03xx02yy01_timesampling_TG50m_FGn14.csv  (For Figure 4.20, 21, 23, 25) 
x02y03xx02yy01_timesampling_TG50m_FGn12.csv  (For Figure 4.20, 21, 23, 25)
x02y03xx02yy01_timesampling_TG50m_FGn10.csv  (For Figure 4.20, 21, 23, 25)
x02y03xx02yy01_timesampling_TG50m_FGn08.csv  (For Figure 4.20)
x02y03xx02yy01_timesampling_TG50m_FGn06.csv  (For Figure 4.20, 22, 24, 25)
x02y03xx02yy01_timesampling_TG50m_FGn04.csv  (For Figure 4.20, 22, 24, 25)
x02y03xx02yy01_timesampling_TG50m_FGn02.csv  (For Figure 4.20, 22, 24, 25)
x02y03xx02yy01_timesampling_TG50m_FG000.csv  (For Figure 4.20, 22, 24, 25)
x02y03xx02yy01_timesampling_TG50m_FGp02.csv  (For Figure 4.20)
x02y03xx02yy01_timesampling_TG50m_FGp04.csv  (For Figure 4.20)

See Dataset 1 for how the figures were generated.

Figure 4.26
Following data in Dataset 2 was used 
X12Y01_XX04YY1_B.rar

See Dataset 2 for how the figure was generated.

Figure 4.28
Following data in Dataset 2 were used
WGFMU SET048 SEM ((18) _x02y02xx02yy01_D200mV_PG_mode_; 11_9_2018 4_06_56 PM.csv
WGFMU SET048 SEM ((1) ; 11_9_2018 4_57_55 PM.csv
WGFMU SET048 SEM ((16) _x02y02xx02yy01_D200mV_fast_IV_; 11_9_2018 4_01_26 PM.csv
WGFMU SET048 SEM ((14) _x02y02xx02yy01_D200mV_2_; 11_9_2018 3_57_44 PM.csv
WGFMU SET048 SEM ((13) _x02y02xx02yy01_D200mV_1_; 11_9_2018 3_54_43 PM.csv
WGFMU SET048 SEM ((19) _x02y02xx02yy01_D200mV_6_; 11_9_2018 4_52_00 PM.csv
WGFMU SET048 SEM ((15) _x02y02xx02yy01_D200mV_3_; 11_9_2018 4_00_06 PM.csv

See Dataset 2 for how the figure was generated.

—Chapter 6— 

Figure 6.1 (c)
Following data in Dataset 4 were used;
std_idvg_0050 [(1) ; 23_07_2019 16_57_34].csv		(300K)
std_idvg_0050 [(3) _4K_; 24_07_2019 07_49_47].csv	(3.8K)

See Dataset 4 for how the figure was generated.

Figure 6.2
Following data in Dataset 4 was used;
std_csd_Id_wide_auto [(1) ; 30_07_2019 21_22_16].csv

See Dataset 4 for how the figure was generated.

Figure 6.3
Following data were used;
std_csd_Id_th_10nA [(1) ; 25_07_2019 12_06_10].csv (for (a))
std_csd_Id_th_10nA_Vd_sweep [(1) ; 26_07_2019 07_52_56].csv (for (b))

Figure 6.4, 6.5
Following data in Dataset 4 were used;
Advanced split CV accumulation VsVd n500mV [(2) ; 19_11_2019 16_04_39].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n450mV [(2) ; 19_11_2019 16_03_02].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n400mV [(2) ; 19_11_2019 16_01_27].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n350mV [(2) ; 19_11_2019 15_59_51].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n300mV [(2) ; 19_11_2019 15_58_15].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n250mV [(2) ; 19_11_2019 15_56_39].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n200mV [(2) ; 19_11_2019 15_55_03].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n150mV [(2) ; 19_11_2019 15_53_27].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n100mV [(2) ; 19_11_2019 15_51_51].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n50mV [(2) ; 19_11_2019 15_50_15].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd 0V [(2) ; 19_11_2019 15_48_39].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n500mV [(1) ; 19_11_2019 15_39_45].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n450mV [(1) ; 19_11_2019 15_38_09].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n400mV [(1) ; 19_11_2019 15_36_33].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n350mV [(1) ; 19_11_2019 15_34_57].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n300mV [(1) ; 19_11_2019 15_33_21].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n250mV [(1) ; 19_11_2019 15_31_45].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n200mV [(1) ; 19_11_2019 15_30_08].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n150mV [(1) ; 19_11_2019 15_28_33].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n100mV [(1) ; 19_11_2019 15_26_57].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd n50mV [(1) ; 19_11_2019 15_25_20].csv  (For Figure 6.4, 6.5)
Advanced split CV accumulation VsVd 0V [(1) ; 19_11_2019 15_23_34].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 500mV [(2) ; 19_11_2019 15_06_07].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 450mV [(2) ; 19_11_2019 15_04_31].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 400mV [(2) ; 19_11_2019 15_02_55].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 350mV [(2) ; 19_11_2019 15_01_19].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 300mV [(2) ; 19_11_2019 14_59_43].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 250mV [(2) ; 19_11_2019 14_58_07].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 200mV [(2) ; 19_11_2019 14_56_30].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 150mV [(2) ; 19_11_2019 14_54_54].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 100mV [(2) ; 19_11_2019 14_53_18].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 50mV [(2) ; 19_11_2019 14_51_42].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 0V [(2) ; 19_11_2019 14_50_06].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 500mV [(1) ; 19_11_2019 14_40_25].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 450mV [(1) ; 19_11_2019 14_38_49].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 400mV [(1) ; 19_11_2019 14_37_13].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 350mV [(1) ; 19_11_2019 14_35_38].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 300mV [(1) ; 19_11_2019 14_34_01].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 250mV [(1) ; 19_11_2019 14_32_26].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 200mV [(1) ; 19_11_2019 14_30_50].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 150mV [(1) ; 19_11_2019 14_29_14].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 100mV [(1) ; 19_11_2019 14_27_38].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 50mV [(1) ; 19_11_2019 14_26_02].csv  (For Figure 6.4, 6.5)
Advanced split CV inversion Vwell 0V [(1) ; 19_11_2019 14_24_26].csv  (For Figure 6.4, 6.5)

Also data for Figure 3.26 were used.

See Dataset 4 for how the figures were generated.

Figure 6.6
Following data in Dataset 4 were used;
SET067_chip_4_E2_W10um_L4um_pMOS_plc_3_Vsub.csv
SET067_chip_4_E2_W10um_L10um_pMOS_plc_3_Vsub.csv

See Dataset 4 for how the figure was generated

Figure 6.7
The data that were used to generate Figure 6.3 and 6.6 were used to generate this figure.

Figure 6.8, 6.9
Following data in Dataset 4 were used;
std_csd_Id_wide_auto [(1) ; 30_07_2019 21_22_16].csv  (For Figure 6.8, 6.9)
std_csd_Id_wide_auto_Vwell_p010 [(4) ; 30_07_2019 18_03_22].csv (For Figure 6.8, 6.9)
std_csd_Id_wide_auto_Vwell_p020 [(4) ; 30_07_2019 17_16_33].csv (For Figure 6.8, 6.9)
std_csd_Id_wide_auto_Vwell_p030 [(4) ; 30_07_2019 16_29_34].csv (For Figure 6.8, 6.9)
std_csd_Id_wide_auto_Vwell_p040 [(3) ; 30_07_2019 15_08_38].csv (For Figure 6.8, 6.9)
std_csd_Id_wide_auto_Vwell_p050 [(1) ; 30_07_2019 14_07_32].csv (For Figure 6.8, 6.9)

See Dataset 4 for how Figure 6.8 (a) -(c) and 6.9 (a)- (c) were generated.
For Figure 6.8 (d) -(f) and 6.9 (d)- (f), Drain_I was plotted against Gate_V in linear scale.

Figure 6.10
Following data in Dataset 4 was used;
std_csd_Id_wide_auto_Vwell_p020_Vth shifts.csv

See Dataset 4 for how the figure was generated.

Figure 6.11, 13, 14(a)
Following data in Dataset 4 were used;
std_tdm_vd_n0030_vw_p0200_1.csv (For Figure 6.11)
std_tdm_vd_n0030_vw_p0200_8.csv (For Figure 6.11, 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_9.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_10.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_11.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_12.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_13.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_14.csv (For Figure 6.11, 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_15.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_16.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_17.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_18.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_19.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_20.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_21.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_22.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_23.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_24.csv (For Figure 6.11, 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_25.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_26.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_27.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_28.csv (For Figure 6.13, 6.14)
std_tdm_vd_n0030_vw_p0200_33.csv (For Figure 6.11)

See Dataset 4 for how the figure was generated.

Figure 6.14 (b) and (c)
Following data in Dataset 4 was used;
std_tdm_vd_n0030_vw_p0200_v_10ks_3.csv

See Dataset 4 for how the figures were generated.

Figure 6.15
Following data in Dataset 4 was used;
std_tdm_vd_n0030_vw_p0200_14.csv	(for 3.8K)
std_tdm_vd_n0030_vw_p0200_vg_n0645_temp_1.csv (for 5K)
std_tdm_vd_n0030_vw_p0200_vg_n0645_temp_2.csv (for 7K)
std_tdm_vd_n0030_vw_p0200_vg_n0645_temp_3.csv (for 10K)
std_tdm_vd_n0030_vw_p0200_vg_n0645_temp_4.csv (for 11K)
std_tdm_vd_n0030_vw_p0200_vg_n0645_temp_5.csv (for 12.5K)
std_tdm_vd_n0030_vw_p0200_vg_n0645_temp_6.csv (for 14K)
std_tdm_vd_n0030_vw_p0200_vg_n0645_temp_7.csv (for 16K)
std_tdm_vd_n0030_vw_p0200_vg_n0645_temp_8.csv (for 20K)
std_tdm_vd_n0030_vw_p0200_vg_n0645_temp_9.csv (for 25K)

See Dataset 4 for how the figure was generated.

For data used in appendices B and C, please see zip files 'Data_for_Appendix_B.zip' and 'Data_for_Appendix_C.zip'.


Period of data acquisition;
2017/06/30-2019/11/19

Information about geographic location of data collection: University of Southampton, U.K.

Related projects:
This work is supported by EPSRC Manufacturing Fellowship (EP/M008975/1), 
Lloyds Register Foundation International Consortium of Nanotechnology, 
and the Joint Research Project (e-SI-Amp (15SIB08)).
This work is also supported by the European Metrology Programme for Innovation and Research (EMPIR) co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.