Characterization and modeling of single defects in GaN/AlGaN fin-MIS-HEMTs

Grill, Alexander; Stampfer, Bernhard; Waltl, Michael; Im, Ki‐Sik; Lee, J.-H.; Ostermaier, Clemens; Ceric, H.

doi:10.1109/irps.2017.7936285

Cited by 12 publications

(10 citation statements)

References 10 publications

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“…However, the RVS tests (Figure 3i) indicate that the conduction is not linear, meaning that the current signals observed in Figure 3d–h are pre‐BD behaviors, and therefore the RTN is associated with the capture and emission of charges at the atomic defects. [ 19 ] Figure 3g–h also indicates that, for this specific sample, voltages ≥0.2 V result in progressive current increase, due to the degradation of the microstructure of the insulating film [ 40 ] ; this behavior was not observed in any smaller device. The reason behind this area dependence is well explained by the DB theory as follows.…”

Section: Materials‐based Rtn Analysismentioning

confidence: 99%

“…As Figure 1c shows, the application of RVS from 0 to 10 V produced the hard‐DB of the HfO 2 film and no RTN, but the application of RVS from 0 to 8 V only produced the soft‐DB of the HfO 2 film and RTN. The RTN signals observed after the soft‐DB of the HfO 2 film drive relatively high currents (tens of µA) at high voltages (4.5 V), and the transitions between different states (related to charge capture and emission [ 19 ] ) are slow: in average, the capture time (σ C ) is 2.99 s and the emission time (σ E ) is 7.46 s. Such type of RTN could be considered of low quality because it would result in TRNGs with high power consumption and low throughput. Nevertheless, our experiments clearly indicate that, for the same electrodes (Ni and Au), same oxide deposition method (ALD) and thickness (5 nm), and same device size (5 µm × 5 µm), HfO 2 exhibits better RTN than Al 2 O 3 .…”

Section: Materials‐based Rtn Analysismentioning

confidence: 99%

“…[ 17 ] ii) The variability of the current within each level over time; lower variability is preferred because that will facilitate the recognition of each state using peripheral circuitry. [ 18 ] And iii) the duration of each current level, which in the field of memristors is often referred to as capture time (σ C ) and emission time (σ E ) because they refer to the emission and capture of electrical charges at the atomic defects [ 19 ] ; shorter times are preferred because that increases throughput of the device when used as entropy source in different circuits. [ 20 ] The acceptable current levels, current variability within a level, and capture and emission times of an RTN signal will depend on the application intended, which have been extensively discussed in the literature; [ 21,22 ] however, it is worth noting that in some cases no unanimous agreement among different research groups and/or companies has been reached, and in some cases values that are acceptable for one group/company are not acceptable for a different group/company.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Random Telegraph Noise in Metal‐Oxide Memristors for True Random Number Generators: A Materials Study

Zanotti

Wang

et al. 2021

Adv Funct Materials

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Some memristors with metal/insulator/metal (MIM) structure have exhibited random telegraph noise (RTN) current signals, which makes them ideal to build true random number generators (TRNG) for advanced data encryption. However, there is still no clear guide on how essential manufacturing parameters like materials selection, thicknesses, deposition methods, and device lateral size can influence the quality of the RTN signal. In this paper, an exhaustive statistical analysis on the quality of the RTN signals produced by different MIM‐like memristors is reported, and straightforward guidelines for the fabrication of memristors with enhanced RTN performance are presented, which are: i) Ni and Ti electrodes show better RTN than Au electrodes, ii) the 50 μm × 50 μm devices show better RTN than the 5 μm × 5 μm ones, iii) TiO2 shows better RTN than HfO2 and Al2O3, iv) sputtered‐oxides show better RTN than ALD‐oxides, and v) 10 nm thick oxides show better RTN than 5 nm thick oxides. The RTN signals recorded have been used as entropy sources in high‐throughput TRNG circuits, which have passed the randomness tests of the National Institute of Standards and Technology. The work can serve as a useful guide for materials scientists and electronic engineers when fabricating MIM‐like memristors for RTN applications.

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Section: Materials‐based Rtn Analysismentioning

confidence: 99%

Section: Materials‐based Rtn Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Random Telegraph Noise in Metal‐Oxide Memristors for True Random Number Generators: A Materials Study

Zanotti

Wang

et al. 2021

Adv Funct Materials

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“…Charge trapping in transistors has been demonstrated to be thermally activated by a large number of experimental investigations [25,163,164]. The observed thermal behavior can be traced back to a transition over an energy barrier in the configuration coordinate diagram.…”

Section: Vi2 Impact Of Quantum Effects On the Temperature Dependencementioning

confidence: 99%

Identification of oxide defects in semiconductor devices: A systematic approach linking DFT to rate equations and experimental evidence

Goes

Wimmer

El-Sayed

et al. 2018

Microelectronics Reliability

Self Cite

120

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It is well-established that oxide defects adversely affect functionality and reliability of a wide range of microelectronic devices. In semiconductor-insulator systems, insulator defects can capture or emit charge carriers from/to the semiconductor. These defects feature several stable configurations, which may have profound implications for the rates of the charge capture and emission processes. Recently, these complex capture/emission events have been investigated experimentally in considerable detail in Si/SiO2 devices, but their theoretical understanding still remains vague. In this paper we discuss in detail how the capture/emission processes can be simulated using the theoretical methods developed for calculating rates of charge transfer reactions between molecules and in electro-chemistry. By employing this theoretical framework we link the atomistic defect configurations to known trapping model parameters (e.g. trap levels) as well as measured capture/emission times in Si/SiO2 devices. Using density functional theory (DFT) calculations, we investigate possible atomistic configurations for various defects in amorphous (a)-SiO2 implicated in being involved in the degradation of microelectronic devices. These include the oxygen vacancy and hydrogen bridge as well as the recently proposed hydroxyl E center. In order to capture the effects of statistical defect-to-defect variations that are inevitably present in amorphous insulators, we analyze a large ensemble of defects both experimentally and theoretically. This large-scale investigation allows us to prioritize the candidates from our defect list based on their trap parameter distributions. For example, we can rule out the E center as a possible candidate. In addition, we establish realistic ranges for the trap parameters, which are useful for model calibration and increase the credibility of simulation results by avoiding artificial solutions. Furthermore, we address the effect of nuclear tunneling, which is involved according to the theory of charge transfer reactions. Based on our DFT results, we demonstrate the impact of nuclear tunneling on the capture/emission process, including their temperature and field dependence, and also give estimates for this effect in Si/SiO2 devices.

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“…Using the proposed methodology the trap bands can be extracted from the measurement data. While the focus of this study is on Si/SiO 2 devices, the methodology is possible on other technologies, given that small devices are available which are also stable enough to record RTN in a reproducible fashion [13][14][15].…”

Section: Methodsmentioning

confidence: 99%

Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors

Stampfer

Schanovsky²,

Waltl

2020

Micromachines

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Miniaturization of metal-oxide-semiconductor field effect transistors (MOSFETs) is typically beneficial for their operating characteristics, such as switching speed and power consumption, but at the same time miniaturization also leads to increased variability among nominally identical devices. Adverse effects due to oxide traps in particular become a serious issue for device performance and reliability. While the average number of defects per device is lower for scaled devices, the impact of the oxide defects is significantly more pronounced than in large area transistors. This combination enables the investigation of charge transitions of single defects. In this study, we perform random telegraph noise (RTN) measurements on about 300 devices to statistically characterize oxide defects in a Si/SiO 2 technology. To extract the noise parameters from the measurements, we make use of the Canny edge detector. From the data, we obtain distributions of the step heights of defects, i.e., their impact on the threshold voltage of the devices. Detailed measurements of a subset of the defects further allow us to extract their vertical position in the oxide and their trap level using both analytical estimations and full numerical simulations. Contrary to published literature data, we observe a bimodal distribution of step heights, while the extracted distribution of trap levels agrees well with recent studies.

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Characterization and modeling of single defects in GaN/AlGaN fin-MIS-HEMTs

Cited by 12 publications

References 10 publications

Random Telegraph Noise in Metal‐Oxide Memristors for True Random Number Generators: A Materials Study

Random Telegraph Noise in Metal‐Oxide Memristors for True Random Number Generators: A Materials Study

Identification of oxide defects in semiconductor devices: A systematic approach linking DFT to rate equations and experimental evidence

Semi-Automated Extraction of the Distribution of Single Defects for nMOS Transistors

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