arXiv subjects

Zhanguo Wang

Publications and source records attributed to Zhanguo Wang.

15 recordsLinked to original sources

arXiv2025

On-Demand Growth of Semiconductor Heterostructures Guided by Physics-Informed Machine Learning

Developing tailored semiconductor heterostructures on demand represents a critical capability for addressing the escalating performance demands in electronic and optoelectronic devices. However, traditional fabrication methods remain constrained by simulation-based design and iterative trial-and-error optimization. Here, we introduce SemiEpi, a self-driving platform designed for molecular beam epitaxy (MBE) to perform multi-step semiconductor heterostructure growth through in-situ monitoring and on-the-fly feedback control. By integrating standard MBE reactors, physics-informed machine learning (ML) models, and parameter initialization, SemiEpi identifies optimal initial conditions and proposes experiments for heterostructure growth, eliminating the need for extensive expertise in MBE processes. As a proof of concept, we demonstrate the optimization of high-density InAs quantum dot (QD) growth with a target emission wavelength of 1240 nm, showcasing the power of SemiEpi. We achieve a QD density of 5 x 10^10 cm^-2, a 1.6-fold increase in photoluminescence (PL) intensity, and a reduced full width at half maximum (FWHM) of 29.13 meV, leveraging in-situ reflective high-energy electron diffraction monitoring with feedback control for adjusting growth temperatures. Taken together, our results highlight the potential of ML-guided systems to address challenges in multi-step heterostructure growth, facilitate the development of a hardware-independent framework, and enhance process repeatability and stability, even without exhaustive knowledge of growth parameters.

cond-mat.mtrl-sci↗

arXiv2024

Enhanced Radiation Hardness of InAs/GaAs Quantum Dot Lasers for Space Communication

Semiconductor lasers have great potential for space laser communication. However, excessive radiation in space can cause laser failure. In principle, quantum dot (QD) lasers are more radiation-resistant than traditional semiconductor lasers because of their superior carrier confinement and smaller active regions. However, the multifaceted nature of radiation effects on QDs resulted in ongoing controversies. Comprehensive testing under simulated space conditions is also necessary to validate their performance. In this work, we conducted radiation tests on various In(Ga)As/GaAs QD and quantum well (QW) materials and devices. Our results revealed that InAs/GaAs QDs with filling factors greater than 50% exhibit greater radiation hardness than those below 50%. Furthermore, most InAs/GaAs QDs showed superior radiation resistance compared to InGaAs/GaAs QW when exposed to low proton fluences of 1E11 and 1E12 cm-2, resulting from radiation-induced defects. The linewidth enhancement factor (LEF) of well-designed QD lasers remains remarkably stable and close to zero, even under proton irradiation at a maximum fluence of 7E13 cm-2, owing to their inherent insensitivity to irradiation-induced defects. These QD lasers demonstrate an exceptional average relative intensity noise (RIN) level of -162 dB/Hz, with only a 1 dB/Hz increase in RIN observed at the highest fluence, indicating outstanding stability. Furthermore, the lasers exhibit remarkable robustness against optical feedback, sustaining stable performance even under a feedback strength as high as -3.1 dB. These results highlight the significant potential of QD lasers for space laser communication applications, where high reliability and resilience to radiation and environmental perturbations are critical.

physics.app-ph↗

arXiv2024

In-situ Self-optimization of Quantum Dot Emission for Lasers by Machine-Learning Assisted Epitaxy

Traditional methods for optimizing light source emissions rely on a time-consuming trial-and-error approach. While in-situ optimization of light source gain media emission during growth is ideal, it has yet to be realized. In this work, we integrate in-situ reflection high-energy electron diffraction (RHEED) with machine learning (ML) to correlate the surface reconstruction with the photoluminescence (PL) of InAs/GaAs quantum dots (QDs), which serve as the active region of lasers. A lightweight ResNet-GLAM model is employed for the real-time processing of RHEED data as input, enabling effective identification of optical performance. This approach guides the dynamic optimization of growth parameters, allowing real-time feedback control to adjust the QDs emission for lasers. We successfully optimized InAs QDs on GaAs substrates, with a 3.2-fold increase in PL intensity and a reduction in full width at half maximum (FWHM) from 36.69 meV to 28.17 meV under initially suboptimal growth conditions. Our automated, in-situ self-optimized lasers with 5-layer InAs QDs achieved electrically pumped continuous-wave operation at 1240 nm with a low threshold current of 150 A/cm2 at room temperature, an excellent performance comparable to samples grown through traditional manual multi-parameter optimization methods. These results mark a significant step toward intelligent, low-cost, and reproductive light emitters production.

cond-mat.mes-hall↗

arXiv2024

Growth of two-inch free-standing heteroepitaxial diamond on Ir/YSZ/Si (001) substrates via laser-patterned templates

In this paper, 2-inch free-standing diamonds were prepared by using heteroepitaxy on composite Ir/YSZ/Si (001) substrates. To release stress, patterned templates were fabricated using laser etching after the initial growth of 50-nm-diamond. Then, the subsequent growth was completed on a patterned template. The full width at half maximum of the diamond (400) and (311) X-ray rocking curves were 313.5 and 359.3 arcsecs, respectively. Strong band-edge emission in the cathodoluminescence spectrum of the resulting diamond revealed excellent crystalline quality. Furthermore, the 2D mapping of Raman spectra was conducted on a $2 mm \times 2 mm$ area located at the center of the 2-inch sample with a thickness of $400 μm$. The result showed an average peak width of $2.85 \pm 0.36 cm^{-1}$ and residual stress of $-0.03 \pm 0.37 GPa$. The dislocation density, determined by counting etching pits generated from $ H_2/O_2$ plasma etching, was estimated to be around $2.2 \times 10^7 cm^{-2}$. These results evidence that the laser-patterned method can effectively release stress during the growth of large-size diamonds, offering a simpler and more cost-effective alternative to the traditional photolithography-patterned scheme.

cond-mat.mtrl-sci↗

arXiv2024

Epitaxial growth of high-quality GaAs on Si(001) using ultrathin buffer layers

The direct growth of III-V semiconductors on silicon holds tremendous potential for photonics applications. However, the inherent differences in their properties lead to defects in the epitaxial layer, including threading dislocations (TDs), antiphase boundaries (APBs), and thermal cracks, significantly impacting device performance. Current processes struggle to suppress these defects simultaneously, necessitating the development of methods to inhibit TDs and APBs in a thin buffer on silicon. This study introduces a GaSb buffer layer during GaAs epitaxy on a silicon (001) substrate. This approach successfully suppresses defect formation by promoting the formation of interfacial misfit dislocation (IMF) arrays at both the AlSb/Si and GaAs/GaSb interfaces. The resulting GaAs layer exhibits a step-flow surface with a rough mean square of approximately 3.8 nm and a full width at half maximum of 158 arcsec. Remarkably, the growth is achieved without any observable interfacial intermixing. Building on this platform, InAs/GaAs quantum dots (QDs) are grown with a density of 3.8E10/cm2, emitting at a wavelength of 1288 nm. This breakthrough holds immense promise for developing high-quality GaAs films with reduced defect densities on silicon for O band lasers, laying the foundation for the mass production of silicon-based integrated circuits.

cond-mat.mtrl-sci↗

arXiv2023

Universal Deoxidation of Semiconductor Substrates Assisted by Machine-Learning and Real-Time-Feedback-Control

Thin film deposition is an essential step in the semiconductor process. During preparation or loading, the substrate is exposed to the air unavoidably, which has motivated studies of the process control to remove the surface oxide before thin film deposition. Optimizing the deoxidation process in molecular beam epitaxy (MBE) for a random substrate is a multidimensional challenge and sometimes controversial. Due to variations in semiconductor materials and growth processes, the determination of substrate deoxidation temperature is highly dependent on the grower's expertise; the same substrate may yield inconsistent results when evaluated by different growers. Here, we employ a machine learning (ML) hybrid convolution and vision transformer (CNN-ViT) model. This model utilizes reflection high-energy electron diffraction (RHEED) video as input to determine the deoxidation status of the substrate as output, enabling automated substrate deoxidation under a controlled architecture. This also extends to the successful application of deoxidation processes on other substrates. Furthermore, we showcase the potential of models trained on data from a single MBE equipment to achieve high-accuracy deployment on other equipment. In contrast to traditional methods, our approach holds exceptional practical value. It standardizes deoxidation temperatures across various equipment and substrate materials, advancing the standardization research process in semiconductor preparation, a significant milestone in thin film growth technology. The concepts and methods demonstrated in this work are anticipated to revolutionize semiconductor manufacturing in optoelectronics and microelectronics industries by applying them to diverse material growth processes.

cond-mat.mes-hall↗

arXiv2023

Machine-Learning-Assisted and Real-Time-Feedback-Controlled Growth of InAs/GaAs Quantum Dots

Self-assembled InAs/GaAs quantum dots (QDs) have properties highly valuable for developing various optoelectronic devices such as QD lasers and single photon sources. The applications strongly rely on the density and quality of these dots, which has motivated studies of the growth process control to realize high-quality epi-wafers and devices. Establishing the process parameters in molecular beam epitaxy (MBE) for a specific density of QDs is a multidimensional optimization challenge, usually addressed through time-consuming and iterative trial-and-error. Here, we report a real-time feedback control method to realize the growth of QDs with arbitrary density, which is fully automated and intelligent. We developed a machine learning (ML) model named 3D ResNet 50 trained using reflection high-energy electron diffraction (RHEED) videos as input instead of static images and providing real-time feedback on surface morphologies for process control. As a result, we demonstrated that ML from previous growth could predict the post-growth density of QDs, by successfully tuning the QD densities in near-real time from 1.5E10 cm-2 down to 3.8E8 cm-2 or up to 1.4E11 cm-2. Compared to traditional methods, our approach, with in situ tuning capabilities and excellent reliability, can dramatically expedite the material optimization process and improve the reproducibility of MBE, constituting significant progress for thin film growth techniques. The concepts and methodologies proved feasible in this work are promising to be applied to a variety of material growth processes, which will revolutionize semiconductor manufacturing for optoelectronic and microelectronic industries.

cond-mat.mes-hall↗

arXiv2020

Spin-injection and spin-relaxation in p-doped InGaAs/GaAs quantum-dot spin light emitting diode at zero magnetic field

We report on efficient spin injection in p-doped InGaAs/GaAs quantum-dot (QD) spin light emitting diode (spin-LED) under zero applied magnetic field. A high degree of electroluminescence circular polarization (Pc) ~19% is measured in remanence up to 100K. This result is obtained thanks to the combination of a perpendicularly magnetized CoFeB/MgO spin injector allowing efficient spin injection and an appropriate p-doped InGaAs/GaAs QD layer in the active region. By analyzing the bias and temperature dependence of the electroluminescence circular polarization, we have evidenced a two-step spin relaxation process. The first step occurs when electrons tunnel through the MgO barrier and travel across the GaAs depletion layer. The spin relaxation is dominated by the Dyakonov-Perel mechanism related to the kinetic energy of electrons, which is characterized by a bias dependent Pc. The second step occurs when electrons are captured into QDs prior to their radiative recombination with holes. The temperature dependence of Pc reflects the temperature induced modification of the QDs doping, together with the variation of the ratio between the charge carrier lifetime and the spin relaxation time inside the QDs. The understanding of these spin relaxation mechanisms is essential to improve the performance of spin LED for future spin optoelectronic applications at room temperature under zero applied magnetic field.

cond-mat.mtrl-sci↗

arXiv2020

Electrical Detection of Light Helicity using a Quantum Dots based Hybrid Device at Zero Magnetic Field

Photon helicity-dependent photocurrent is measured at zero magnetic field on a device based on an ensemble of InGaAs/GaAs quantum dots that are embedded into a GaAs-based p-i-n diode. Our main goal is to take advantage of the long electron spin relaxation time expected in these nano-objects. In these experiments, no external magnetic field is required thanks to the use of an ultrathin magnetic CoFeB/MgO electrode, presenting perpendicular magnetic anisotropy (PMA). We observe a clear asymmetry of the photocurrent measured under respective right and left polarized light that follows the hysteresis of the magnetic layer. The amplitude of this asymmetry at zero magnetic field decreases with increasing temperatures and can be controlled with the bias. Polarization-resolved photoluminescence is detected in parallel while the device is operated as a photodetector. This demonstrates the multifunctional capabilities of the device and gives valuable insights into the spin relaxation of the electrons in the quantum dots.

physics.app-ph↗

arXiv2015

Possible atomic structures for the sub-bandgap absorption of chalcogen hyperdoped silicon

Single-crystal silicon wafers were hyperdoped respectively by sulfur, selenium, and tellurium element using ion implantation and nanosecond laser melting. The hyperdoping of such chalcogen elements endowed the treated silicon with a strong and wide sub-bandgap light absorptance. When these hyperdoped silicons were thermally annealed even at low temperatures (such as 200~400 oC), however, this extra sub-bandgap absorptance began to attenuate. In order to explain this attenuation of absorptance, alternatively, we consider it corresponding to a chemical decomposition reaction from optically absorbing structure to non-absorbing structure, and obtain a very good fitting to the attenuated absorptances by using Arrhenius equation. Further, we extract the reaction activation energies from the fittings and they are 0.343(+/- 0.031) eV for S-, 0.426(+/-0.042) eV for Se-, and 0.317(+/-0.033) eV for Te-hyperdoped silicon, respectively. We discuss these activation energies in term of the bond energies of chalcogen-Si metastable bonds, and finally suggest that several high-energy interstitial sites instead of the substitutional site, are very possibly the atomic structures that are responsible for the sub-bandgap absorptance of chalcogen hyperdoped silicon.

cond-mat.mtrl-sci↗

arXiv2014

Optical and electrical properties of textured sulfur hyperdoped silicon: a thermal annealing study

When the sulfur element is hyperdoped into crystalline silicon to a supersaturated density of 1020 cm-3, it can enhance the sub-bandgap light absorption of silicon from 0 to 70%, with the antireflection of surface dome structures. On the other hand, the local Si: S configuration that can contribute to the strong sub-bandgap absorption is still unknown. In order to find more characteristics of this local Si:S configuration, we thermally annealed the textured sulfur hyperdoped silicon, and analyzed the changes of its optical and electrical properties. We find that the imaginary part of the complex dielectric constant of this Si:S configuration is almost constant in the wavelength range from 1250 nm to 2500 nm ...

cond-mat.mtrl-sci↗

arXiv2012

Wetting layer evolution and its temperature dependence during self assembly of InAs/GaAs quantum dots

For InAs/GaAs(001) quantum dot (QD) system, the wetting layer (WL) evolution and its temperature dependence were studied using reflectance difference spectroscopy (RDS) and analyzed with a rate equation model. The WL thicknesses showed a monotonic increase at relatively low growth temperatures but a first increase and then decrease at higher temperatures, which were unexpected from the thermodynamic understanding. By adopting a rate equation model, the temperature dependence of QD growth was assigned as the origin of different WL evolutions. A brief discussion on the indium desorption was also given. Those results gave hints of the kinetic aspects of QD self-assembly.

cond-mat.mes-hall↗

arXiv2007

Room temperature observation of electron resonant tunneling through InAs/AlAs quantum dots

Molecular beam epitaxy is employed to manufacture self-assembled InAs/AlAs quantum-dot resonant tunneling diodes. Resonant tunneling current is superimposed on the thermal current, and they make up the total electron transport in devices. Steps in current-voltage characteristics and peaks in capacitance-voltage characteristics are explained as electron resonant tunneling via quantum dots at 77K or 300K, and this is the first time that resonant tunneling is observed at room temperature in III-V quantum-dot materials. Hysteresis loops in the curves are attributed to hot electron injection/emission process of quantum dots, which indicates the concomitant charging/discharging effect.

cond-mat.mes-hall↗

arXiv2007

Electron resonant tunneling through InAs/GaAs quantum dots embedded in a Schottky diode with an AlAs insertion layer

Molecular beam epitaxy is employed to manufacture self-assembled InAs/GaAs quantum dot Schottky resonant tunneling diodes. By virtue of a thin AlAs insertion barrier, the thermal current is effectively reduced and electron resonant tunneling through quantum dots under both forward and reverse biased conditions is observed at relatively high temperature of 77K. The ground states of quantum dots are found to be at ~0.19eV below the conduction band of GaAs matrix. The theoretical computations are in conformity with experimental data.

cond-mat.mes-hall↗

arXiv2007

Research progress of electronic properties of self-assembled semiconductor quantum dots

Self-assembled semiconductor quantum dot is a new type of artificially designed and grown function material which exhibits quantum size effect, quantum interference effect, surface effect, quantum tunneling-Coulumb-blockade effect and nonlinear optical effect. Due to advantages like less crystal defects and relatively simpler fabrication technology, that material may be of important value in future nanoelectronic device researches. In the order of vertical transport, lateral transport and charge storage, this paper gives a brief introduction of recent advances in the electronic properties of that material and an analysis of problems and perspectives.

cond-mat.mes-hall↗