arXiv subjects

Matthias Muehle

Publications and source records attributed to Matthias Muehle.

7 recordsLinked to original sources

arXiv2026

Band alignment of grafted diamond/GaN p-n heterojunctions interfaced with ALD Al2O3 and SiNx/Al2O3

Diamond and gallium nitride are complementary semiconductors for forming p-n junctions because of their respective doping limitations. Understanding the band alignment of grafted diamond/GaN heterojunctions is therefore essential for optimizing diode performance. In this study, the band alignment of diamond/Al2O3/GaN and diamond/Al2O3/SiNx/GaN heterostructures was determined by X-ray photoelectron spectroscopy. Both structures exhibit type-II band alignment, but with different band offsets. The band offsets of the diamond/Al2O3/SiNx/GaN heterojunction are larger by 0.42 eV than those of diamond/Al2O3/GaN. This difference is attributed to a modification of the interfacial electrostatic potential, which may arise from a reduced density of positive fixed charges in the interfacial dielectric near the diamond/Al2O3 interface after insertion of the SiNx layer. These results demonstrate that interfacial-layer engineering provides an effective strategy for tailoring the band alignment of grafted diamond/GaN heterojunctions, offering guidance for the design of p-n diodes with tunable rectifying characteristics.

cond-mat.mtrl-sci↗

arXiv2025

Preliminary Demonstration of Diamond-GaN pn Diodes via Grafting

Ultrawide bandgap (UWBG) semiconductors exhibit exceptional electrical and thermal properties, offering strong potential for high power and high frequency electronics. However, efficient doping in UWBG materials is typically limited to either n type or p type, constraining their application to unipolar devices. The realization of pn junctions through heterogeneous integration of complementary UWBG or WBG semiconductors is hindered by lattice mismatch and thermal expansion differences. Here, we report the preliminary demonstration of diamond GaN heterojunction pn diodes fabricated via grafting. A single crystalline p plus diamond nanomembrane was integrated onto an epitaxially grown c plane n plus GaN substrate with an ultrathin ALD Al2O3 interlayer. The resulting diodes exhibit an ideality factor of 1.55 and a rectification ratio of over 1e4. Structural and interfacial properties were examined by AFM, XRD, Raman, and STEM, providing critical insights to guide further optimization of diamond GaN pn heterojunction devices.

cond-mat.mtrl-sci↗

arXiv2024

AI-Guided Defect Detection Techniques to Model Single Crystal Diamond Growth

From a process development perspective, diamond growth via chemical vapor deposition has made significant strides. However, challenges persist in achieving high quality and large-area material production. These difficulties include controlling conditions to maintain uniform growth rates for the entire growth surface. As growth progresses, various factors or defect states emerge, altering the uniform conditions. These changes affect the growth rate and result in the formation of crystalline defects at the microscale. However, there is a distinct lack of methods to identify these defect states and their geometry using images taken during the growth process. This paper details seminal work on defect segmentation pipeline using in-situ optical images to identify features that indicate defective states that are visible at the macroscale. Using a semantic segmentation approach as applied in our previous work, these defect states and corresponding derivative features are isolated and classified by their pixel masks. Using an annotation focused human-in-the-loop software architecture to produce training datasets, with modules for selective data labeling using active learning, data augmentations, and model-assisted labeling, our approach achieves effective annotation accuracy and drastically reduces the time and cost of labeling by orders of magnitude. On the model development front, we found that deep learning-based algorithms are the most efficient. They can accurately learn complex representations from feature-rich datasets. Our best-performing model, based on the YOLOV3 and DeeplabV3plus architectures, achieved excellent accuracy for specific features of interest. Specifically, it reached 93.35% accuracy for center defects, 92.83% for polycrystalline defects, and 91.98% for edge defects.

cs.CV↗

arXiv2024

AI-Guided Feature Segmentation Techniques to Model Features from Single Crystal Diamond Growth

Process refinement to consistently produce high-quality material over a large area of the grown crystal, enabling various applications from optics crystals to quantum detectors, has long been a goal for diamond growth. Machine learning offers a promising path toward this goal, but faces challenges such as the complexity of features within datasets, their time-dependency, and the volume of data produced per growth run. Accurate spatial feature extraction from image to image for real-time monitoring of diamond growth is crucial yet complicated due to the low-volume and high feature complexity nature of the datasets. This paper compares various traditional and machine learning-driven approaches for feature extraction in the diamond growth domain, proposing a novel deep learning-driven semantic segmentation approach to isolate and classify accurate pixel masks of geometric features like diamond, pocket holder, and background, along with their derivative features based on shape and size. Using an annotation-focused human-in-the-loop software architecture for training datasets, with modules for selective data labeling using active learning, data augmentations, and model-assisted labeling, our approach achieves effective annotation accuracy and drastically reduces labeling time and cost. Deep learning algorithms prove highly efficient in accurately learning complex representations from datasets with many features. Our top-performing model, based on the DeeplabV3plus architecture, achieves outstanding accuracy in classifying features of interest, with accuracies of 96.31% for pocket holder, 98.60% for diamond top, and 91.64% for diamond side features.

cs.CV↗

arXiv2023

Scalable Production and Supply Chain of Diamond using Microwave Plasma: a Mini-review

Discovered and reported exactly 40 years ago, microwave plasma assisted chemical vapor deposition (MPACVD) pointed out an economic technology that could potentially produce lab-grown diamond stones at scale. After this breakthrough discovery, demonstrating that diamond can be growth at low pressure and temperature, the progress quickly curbed and synthetic single crystal diamond (SCD) size and quality could not be improved toward attaining requirements critical in solid-state electronics. This led to the early promise of MPACVD to not come true and slowed the level of investments, thereby further stalling the progress in diamond syntheses. With the invention of a few novel homo- and hetero-epitaxy growth techniques, the diamond research and technology has recently reinvigorated. This mini review attempts to capture the momentum of recent progress in diamond MPACVD that could finally bring scalable manufacturing of high quality large size wafers for future electronics and optics.

physics.app-ph↗

arXiv2022

Spectral Emission Properties of a Nitrogen-doped Diamond(001) Photocathode: Hot Electron Transport and Transverse Momentum Filtering

The electron emission properties of a single-crystal nitrogen-doped diamond(001) photocathode inserted in a 10kV DC photoelectron gun are determined using a tunable (235-410nm) ultraviolet laser radiation source for photoemission from both the back nitrogen-doped substrate face and the front homo-epitaxially grown and undoped diamond crystal face. The measured spectral trends of the mean transverse energy (MTE) and quantum efficiency (QE) of the emitted electrons are both anomalous and non-monotonic, but are shown to be consistent with (i) the known physics of electron photoexcitation from the nitrogen substitution states into the conduction bands of diamond, (ii) the energy position and dispersion characteristics of the conduction bands of diamond in the (001) emission direction, (iii) the effective electron affinity of the crystal faces, (iv) the strong electron-(optical)phonon coupling in diamond, and (v) the associated hot electron transport dynamics under energy equipartition with the optical phonons. Notably, the observed hot electron emission is shown to be restricted parallel to the photocathode surface by the low transverse effective masses of the emitting band states - a transverse momentum filtering effect.

cond-mat.mtrl-sci↗

arXiv2022

The Effects of Boron Doping on the Bulk and Surface Acoustic Phonons in Single-Crystal Diamond

We report the results of the investigation of bulk and surface acoustic phonons in the undoped and boron-doped single-crystal diamond films using the Brillouin-Mandelstam light scattering spectroscopy. The evolution of the optical phonons in the same set of samples was monitored with Raman spectroscopy. It was found that the frequency and the group velocity of acoustic phonons decrease non-monotonically with the increasing boron doping concentration, revealing pronounced phonon softening. The change in the velocity of the shear horizontal and the high-frequency pseudo-longitudinal acoustic phonons in the degenerately doped diamond, as compared to the undoped diamond, was as large as ~15% and ~12%, respectively. As a result of boron doping, the velocity of the bulk longitudinal and transverse acoustic phonons decreased correspondingly. The frequency of the optical phonons was unaffected at low boron concentration but experienced a strong decrease at the high doping level. The density-functional-theory calculations of the phonon band structure for the pristine and highly-doped sample confirm the phonon softening as a result of boron doping in diamond. The obtained results have important implications for thermal transport in heavily doped diamond, which is a promising material for ultra-wide-band-gap electronics.

cond-mat.mtrl-sci↗