This paper reports a comprehensive study on the anisotropic electrical properties of vertical (<inline-formula> <tex-math notation="LaTeX">\overline {\textsf {2}}01 </tex-math></inline-formula>) and ...(010) <inline-formula> <tex-math notation="LaTeX">\beta </tex-math></inline-formula>-Ga 2 O 3 Schottky barrier diodes (SBDs). The devices were fabricated on single-crystal substrates grown by an edge-defined film-fed growth method. The temperature-dependent current-voltage (I-V) and capacitance-voltage (C-V) characteristics were systematically measured, analyzed, and compared. The (<inline-formula> <tex-math notation="LaTeX">\overline {\textsf {2}}01 </tex-math></inline-formula>) and (010) SBDs exhibited on-resistances (<inline-formula> <tex-math notation="LaTeX">{R}_{{ \mathrm{\scriptscriptstyle ON}}} </tex-math></inline-formula>) of 0.56 and <inline-formula> <tex-math notation="LaTeX">0.77~\textsf {m}\Omega \cdot \textsf {cm}^{{\textsf {2}}} </tex-math></inline-formula>, turn- ON voltages (<inline-formula> <tex-math notation="LaTeX">{V}_{{ \mathrm{\scriptscriptstyle ON}}} </tex-math></inline-formula>) of 1.0 and 1.3 V, Schottky barrier heights (SBHs) of 1.05 and 1.20 eV, electron mobilities of 125 and 65 cm 2 /(<inline-formula> <tex-math notation="LaTeX">\textsf {V}\cdot ~\textsf {s} </tex-math></inline-formula>), respectively, with an on-current of ~1.3 kA/cm 2 and on/off ratio of ~10 9 . The (010) SBD had a larger <inline-formula> <tex-math notation="LaTeX">{V}_{{ \mathrm{\scriptscriptstyle ON}}} </tex-math></inline-formula> and SBH due to anisotropic surface properties (i.e., surface Fermi level pinning and band bending), as supported by X-ray photoelectron spectroscopy measurements. Temperature-dependent I-V also revealed the inhomogeneous nature of the SBH in both devices, where the (<inline-formula> <tex-math notation="LaTeX">\overline {\textsf {2}}01 </tex-math></inline-formula>) SBD showed a more uniform SBH distribution. The homogeneous SBH was also extracted: 1.33 eV for the (<inline-formula> <tex-math notation="LaTeX">\overline {\textsf {2}}01 </tex-math></inline-formula>) SBD and 1.53 eV for the (010) SBD. The reverse leakage current of the devices was well described by the two-step trap-assisted tunnelingmodel and the 1-D variable range hopping conduction model. The (<inline-formula> <tex-math notation="LaTeX">\overline {\textsf {2}}01 </tex-math></inline-formula>) SBD showed a larger leakage current due to its lower SBH and/or smaller activation energy, and thus a smaller breakdown voltage. These results indicate that the crystalline anisotropy of <inline-formula> <tex-math notation="LaTeX">\beta </tex-math></inline-formula>-Ga 2 O 3 can affect the electrical properties of vertical SBDs and should be taken into consideration when designing <inline-formula> <tex-math notation="LaTeX">\beta </tex-math></inline-formula>-Ga 2 O 3 electronics.
III-nitrides material systems have attracting growing interests in photovoltaic (PV) applications after huge success in optoelectronics. In this work, a semi-analytical model is used to analyze the ...PV performance of single junction InGaN solar cells. Through clarifying four basic types of loss mechanisms, including transmission loss, thermalization loss, spatial relaxation loss and recombination loss, we discover that transmission loss accounts for the primary part of efficiency loss due to the large bandgaps of III-nitride materials. As for all recombination-related losses, Shockley-Reed-Hall (SRH) recombination loss is dominant over others. By incorporating non-step-like absorptance and emittance with below-bandgap absorption, we discover that reducing SRH recombination current by improving the material quality of InGaN layers proves an efficient approach to optimize the cell performance. Furthermore, the energy conversion efficiency increases with higher material quality and larger solar concentration. Our calculations show that energy conversion efficiency of 7.35% can be achieved under one sun and maximum efficiency of 8.43% under 1000 suns. This theoretical study offers detailed guidance for the future design of high-performance thin film InGaN solar cells.
Background
Disease progression models (DPM) of Alzheimer’s disease (AD) based on non‐invasive biomarkers have received significant attention in recent years. Crucially for drug development, DPM ...promises to identify pre‐clinical stages of AD. However, traditional DPMs consider only a single canonical sequence of neurodegeneration, which may ignore important population clusters and individual variation. Addressing this, we propose a method to use individual dMRI‐based connectomes as an informative prior in AD DPM.
Method
We extracted regional cortical thickness measures and tractography‐based connectomes from T1 and diffusion MRI of 32 AD patients and 52 controls. We build a DPM using the event‐based (EBM) approach. EBM models AD staging discreetly. Every stage is identified with a neurodegenerative event, e.g. a regional thickness falling below some threshold. Disease stage is then defined by the last abnormal biomarker based on a canonical event order. The goal of the model is to find an event order specific to AD in a Baeysian setting. We replace the uninformative prior on the order with one based on the subject connectomes. Every regional biomarker pair is assigned a probability that one region degenerates following the other based on the shortest connectome path length between the regions. The idea follows closely the amyloid network diffusion hypothesis. We test the original EBM and our models on cross‐sectional data and test them on 12‐ and 24‐month follow‐up scans. Predicted patient stage and visit order are ordinally correlated to assess model performance.
Result
Our model outperforms the original EBM (Kendall tau=0.34 vs 0.49). Our model systematically assigns higher progression scores for AD subjects (Fig.1). We also compare DPM performance using predicted stage in disease classification. Our model again outperforms traditional EBM, achieving ROC AUC=0.88 (std=0.046) vs 0.816 (std=0.008).
Conclusion
We have developed an individualized neuroimaging disease progression model of AD based on the widely used EBM. Individual connectome variation allows the computational model to more finely pin‐point an individual’s specific stage of disease progression based on the observed pattern of neurodegeneration. The connectome‐based EBM shows significant improvement over standard EBM.
Abstract
Background
Disease progression models (DPM) of Alzheimer’s disease (AD) based on non‐invasive biomarkers have received significant attention in recent years. Crucially for drug development, ...DPM promises to identify pre‐clinical stages of AD. However, traditional DPMs consider only a single canonical sequence of neurodegeneration, which may ignore important population clusters and individual variation. Addressing this, we propose a method to use individual dMRI‐based connectomes as an informative prior in AD DPM.
Method
We extracted regional cortical thickness measures and tractography‐based connectomes from T1 and diffusion MRI of 32 AD patients and 52 controls. We build a DPM using the event‐based (EBM) approach. EBM models AD staging discreetly. Every stage is identified with a neurodegenerative event, e.g. a regional thickness falling below some threshold. Disease stage is then defined by the last abnormal biomarker based on a canonical event order. The goal of the model is to find an event order specific to AD in a Baeysian setting. We replace the uninformative prior on the order with one based on the subject connectomes. Every regional biomarker pair is assigned a probability that one region degenerates following the other based on the shortest connectome path length between the regions. The idea follows closely the amyloid network diffusion hypothesis. We test the original EBM and our models on cross‐sectional data and test them on 12‐ and 24‐month follow‐up scans. Predicted patient stage and visit order are ordinally correlated to assess model performance.
Result
Our model outperforms the original EBM (Kendall tau=0.34 vs 0.49). Our model systematically assigns higher progression scores for AD subjects (Fig.1). We also compare DPM performance using predicted stage in disease classification. Our model again outperforms traditional EBM, achieving ROC AUC=0.88 (std=0.046) vs 0.816 (std=0.008).
Conclusion
We have developed an individualized neuroimaging disease progression model of AD based on the widely used EBM. Individual connectome variation allows the computational model to more finely pin‐point an individual’s specific stage of disease progression based on the observed pattern of neurodegeneration. The connectome‐based EBM shows significant improvement over standard EBM.
III-nitrides and beta-phase gallium oxide (β-Ga2O3) are currently two intensively investigated wide bandgap semiconductor materials for power electronics. Due to the relatively low lattice mismatch ...between the two material systems and the availability of bulk AlN, GaN and β-Ga2O3 substrates, epitaxial growth of III-nitrides on β-Ga2O3 or vice versa has been realized. However, the design of power devices by integrating the two material systems is still lacking. Here we numerically investigate an AlN/β-Ga2O3 heterostructure by taking advantage of polarization-induced doping to realize high-performance enhancement-mode transistors. Induced by polarization effects at the AlN/β-Ga2O3 interface, a 2-dimensional electron gas concentration can reach up to 8.1 × 1019 cm−3 in the channel. On top of the channel, a p-GaN gate was introduced and eventually a normally-off AlN/β-Ga2O3 field-effect transistor with tunable positive threshold voltages was realized. Furthermore, we inserted an unintentionally doped GaN back barrier layer to suppress the drain leakage current. Eventually, the transfer and output characteristics of the proposed device with different structural parameters were further investigated and analyzed in the pursuit of high-performance III-nitrides/Ga2O3-based power devices.
We implement finite-difference time-domain (FDTD) method to simulate the optical properties of highly polarized InGaN light emitting diodes (LEDs) coupled with metallic grating structure. The Purcell ...factor (Fp), light extraction efficiency (LEE), internal quantum efficiency (IQE), external quantum efficiency (EQE), and modulation frequency are calculated for different polarized emissions. Our results show that light polarization has a strong impact on Fp and LEE of LEDs due to their coupling effects with the surface plasmons (SPs) generated by metallic grating. Fp as high as 34 and modulation frequency up to 5.4 GHz are obtained for a simulated LED structure. Furthermore, LEE, IQE and EQE can also be enhanced by tuning the coupling between polarized emission and SPs. These results can serve as guidelines for the design and fabrication of high efficiency and high speed LEDs for the applications of solid-state lighting and visible-light communication.
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