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Boron arsenide (BAs) is a covalent semiconductor with a theoretical intrinsic thermal conductivity approaching 1300 W/m K. The existence of defects not only limits the thermal conductivity of BAs significantly but also changes its pressure-dependent thermal transport behavior. Using both picosecond transient thermoreflectance and femtosecond time-domain thermoreflectance techniques, we observed a non-monotonic dependence of thermal conductivity on pressure. This trend is not caused by the pressure-modulated phonon–phonon scattering, which was predicted to only change the thermal conductivity by 10%–20%, but a result of several competing effects, including defect–phonon scattering and modification of structural defects under high pressure. Our findings reveal the complexity of the defect-modulated thermal behavior under pressure. [ABSTRACT FROM AUTHOR]

The silicon wafer is one of the raw materials used to make semiconductor chipsets. Semiconductor failure or dysfunction could be the result of defects in the layers of this material. As a result, it is essential to work toward the development of a system that is both quick and precise in identifying and classifying wafer defects. Wafer map analysis is necessary for the quality control and analysis of the semiconductor manufacturing process. There are some failure patterns that can be displayed by wafer maps. These patterns can provide essential details that can assist engineers in determining the reason of wafer failures. In this research, a deep-learning-based silicon wafer defect identification and classification model is proposed. The main objective of this research is to identify and classify the silicon wafer defects using the wafer map images. This proposed model identifies and classifies the defects based on the wafer map images from the WM-811K dataset. The proposed model is composed of a pretrained deep transfer learning model called ShuffleNet-v2 with convolutional neural network (CNN) architecture. This ShuffleNet-v2-CNN performs the defects identification and classification process following the workflow of data preprocessing, data augmentation, feature extraction, and classification. For performance evaluation, the proposed ShuffleNet-v2-CNN is evaluated with performance metrics like accuracy, recall, precision, and f1-score. The proposed model has obtained an overall accuracy of 96.93%, 95.40% precision, 96.26% recall, and 95.75% F1-score in classifying the silicon wafer defects based on the wafer map images. [ABSTRACT FROM AUTHOR]

We demonstrate spatial modification of the optical properties of thin-film metal oxides, zinc oxide (ZnO) and vanadium dioxide (VO2) as representatives, using a commercial focused ion beam (FIB) system. Using a Ga+ FIB and thermal annealing, we demonstrated variable doping of a wide-bandgap semiconductor, ZnO, achieving carrier concentrations from 1018 cm−3 to 1020 cm−3. Using the same FIB without subsequent thermal annealing, we defect-engineered a correlated semiconductor, VO2, locally modifying its insulator-to-metal transition (IMT) temperature by up to ∼25 °C. Such area-selective modification of metal oxides by direct writing using a FIB provides a simple, mask-less route to the fabrication of optical structures, especially when multiple or continuous levels of doping or defect density are required. [ABSTRACT FROM AUTHOR]

Contacting two-dimensional (2D) semiconductors with van der Waals semimetals significantly reduces the contact resistance and Fermi level pinning due to defect-free interfaces. However, depending on the band alignment, a Schottky barrier remains. Here we study the evolution of the valence and conduction band edges in pristine and heavily vanadium (0.44%), i.e., p-type, doped epitaxial WSe2 on quasi-freestanding graphene (QFEG) on silicon carbide as a function of thickness. We find that with increasing number of layers the Fermi level of the doped WSe2 gets pinned at the highest dopant level for three or more monolayers. This implies a charge depletion region of about 1.6 nm. Consequently, V dopants in the first and second WSe2 layer on QFEG/SiC are ionized (negatively charged) whereas they are charge neutral beyond the second layer. [ABSTRACT FROM AUTHOR]

Photonic integrated circuits (PICs) based on lithographically patterned waveguides provide a scalable approach for manipulating photonic bits, enabling seminal demonstrations of a wide range of photonic technologies with desired complexity and stability. While the next generation of applications such as ultra-high speed optical transceivers, neuromorphic computing and terabit-scale communications demand further lower power consumption and higher operating frequency. Complementing the leading silicon-based material platforms, the third-generation semiconductor, silicon carbide (SiC), offers a significant opportunity toward the advanced development of PICs in terms of its broadest range of functionalities, including wide bandgap, high optical nonlinearities, high refractive index, controllable artificial spin defects and complementary metal oxide semiconductor-compatible fabrication process. The superior properties of SiC have enabled a plethora of nano-photonic explorations, such as waveguides, micro-cavities, nonlinear frequency converters and optically-active spin defects. This remarkable progress has prompted the rapid development of advanced SiC PICs for both classical and quantum applications. Here, we provide an overview of SiC-based integrated photonics, presenting the latest progress on investigating its basic optoelectronic properties, as well as the recent developments in the fabrication of several typical approaches for light confinement structures that form the basic building blocks for low-loss, multi-functional and industry-compatible integrated photonic platform. Moreover, recent works employing SiC as optically-readable spin hosts for quantum information applications are also summarized and highlighted. As a still-developing integrated photonic platform, prospects and challenges of utilizing SiC material platforms in the field of integrated photonics are also discussed. [ABSTRACT FROM AUTHOR]

The electronic structures of charged point defects influence electrical and optical properties of semiconductors. Understanding the orbital interactions responsible for the electronic structures of defects therefore promotes a chemical intuition for defect‐driven mechanisms in semiconductors. In this tutorial, we discuss a molecular orbital theory‐based framework for understanding defect‐induced electronic states based on local chemical interactions between the defect and the atoms surrounding the defect site. By using Mg2Si as a case study, we show how both the chemical interactions and molecular orbitals (i. e., wave functions) responsible for the charge state(s) of a defect can be understood from the bonding symmetry of the defect site. We anticipate that a chemistry‐based perspective of charged defects will enrich defect engineering efforts for electronic and optical materials. [ABSTRACT FROM AUTHOR]

Tactile perception enabled by somatosensory system in human is essential for dexterous tool usage, communication, and interaction. Imparting tactile recognition functions to advanced robots and interactive systems can potentially improve their cognition and intelligence. Here, a flexible artificial sensory nerve that mimics the tactile sensing, neural coding, and synaptic processing functions in human sensory nerve is developed to achieve neuromorphic tactile recognition at device level without relying on algorithms or computing resources. An interfacial self‐assembly technique, which produces uniform and defect‐less thin film of semiconductor nanoparticles on arbitrary substrates, is employed to prepare the flexible synaptic device. The neural facilitation and sensory memory characteristics of the proton‐gating synaptic device enable this system to identify material hardness during robotic grasping and recognize tapping patterns during tactile interaction in a continuous, real‐time, high‐accuracy manner, demonstrating neuromorphic intelligence and recognition capabilities. This artificial sensory nerve produced in wearable and portable form can be readily integrated with advanced robots and smart human–machine interfaces for implementing human‐like tactile cognition in neuromorphic electronics toward robotic and wearable applications. [ABSTRACT FROM AUTHOR]

β-Ga2O3 is an emerging ultra-wide bandgap semiconductor, holding a tremendous potential for power-switching devices for next-generation high power electronics. The performance of such devices strongly relies on the precise control of electrical properties of β-Ga2O3, which can be achieved by implantation of dopant ions. However, a detailed understanding of the impact of ion implantation on the structure of β-Ga2O3 remains elusive. Here, using aberration-corrected scanning transmission electron microscopy, we investigate the nature of structural damage in ion-implanted β-Ga2O3 and its recovery upon heat treatment with the atomic-scale spatial resolution. We reveal that upon Sn ion implantation, Ga2O3 films undergo a phase transformation from the monoclinic β-phase to the defective cubic spinel γ -phase, which contains high-density antiphase boundaries. Using the planar defect models proposed for the γ -Al2O3, which has the same space group as β-Ga2O3, and atomic-resolution microscopy images, we identify that the observed antiphase boundaries are the {100}1/4 ⟨110⟩ type in cubic structure. We show that post-implantation annealing at 1100 °C under the N2 atmosphere effectively recovers the β-phase; however, nano-sized voids retained within the β-phase structure and a γ -phase surface layer are identified as remanent damage. Our results offer an atomic-scale insight into the structural evolution of β-Ga2O3 under ion implantation and high-temperature annealing, which is key to the optimization of semiconductor processing conditions for relevant device design and the theoretical understanding of defect formation and phase stability. [ABSTRACT FROM AUTHOR]

β-Ga2O3 is an emerging ultra-wide bandgap semiconductor, holding a tremendous potential for power-switching devices for next-generation high power electronics. The performance of such devices strongly relies on the precise control of electrical properties of β-Ga2O3, which can be achieved by implantation of dopant ions. However, a detailed understanding of the impact of ion implantation on the structure of β-Ga2O3 remains elusive. Here, using aberration-corrected scanning transmission electron microscopy, we investigate the nature of structural damage in ion-implanted β-Ga2O3 and its recovery upon heat treatment with the atomic-scale spatial resolution. We reveal that upon Sn ion implantation, Ga2O3 films undergo a phase transformation from the monoclinic β-phase to the defective cubic spinel γ -phase, which contains high-density antiphase boundaries. Using the planar defect models proposed for the γ -Al2O3, which has the same space group as β-Ga2O3, and atomic-resolution microscopy images, we identify that the observed antiphase boundaries are the {100}1/4 ⟨110⟩ type in cubic structure. We show that post-implantation annealing at 1100 °C under the N2 atmosphere effectively recovers the β-phase; however, nano-sized voids retained within the β-phase structure and a γ -phase surface layer are identified as remanent damage. Our results offer an atomic-scale insight into the structural evolution of β-Ga2O3 under ion implantation and high-temperature annealing, which is key to the optimization of semiconductor processing conditions for relevant device design and the theoretical understanding of defect formation and phase stability. [ABSTRACT FROM AUTHOR]

The optoelectronic performance of wide-bandgap semiconductors often cannot compete with that of their defect-tolerant small-bandgap counterpart. Here, the authors outline three main challenges to overcome for mitigating the impact of defects in wide-bandgap semiconductors. [ABSTRACT FROM AUTHOR]

The undesirable impacts of solder void defects on the reliability of die packages have prompted stringent requirements on solder void size control in the semiconductor packaging industry. Vacuum reflow process using Pb95Sn5 solder was studied, where critical process parameters within temperature and pressure profiles were varied for enhanced solder void size reduction, in comparison to conventional reflow process. Higher reflow temperature profile, faster pressure pump-down rate, and longer vacuum dwell time above threshold levels are critical conditions required for consistently achieving minimum solder void sizes well below the industry criteria. Application of threshold conditions using large volume reflow oven with industrial settings has achieved the single and the total solder void size over die size well below the standard 2.5% and 5% requirements, respectively, with majority of the samples attained the single and the total solder void size over die size below 1% and 2%, respectively. Solder bond line thickness exhibited a significant influence on the solder void size reduction and thus needs to be administered appropriately during die packaging assembly to achieve the maximum solder void size reduction. [ABSTRACT FROM AUTHOR]

Microstructural control during the solution processing of small-molecule semiconductors (namely, soluble acene) is important for enhancing the performance of field-effect transistors (FET) and sensors. This focused review introduces strategies to enhance the gas-sensing properties (sensitivity, recovery, selectivity, and stability) of soluble acene FET sensors by considering their sensing mechanism. Defects, such as grain boundaries and crystal edges, provide diffusion pathways for target gas molecules to reach the semiconductor-dielectric interface, thereby enhancing sensitivity and recovery. Representative studies on grain boundary engineering, patterning, and pore generation in the formation of soluble acene crystals are reviewed. The phase separation and microstructure of soluble acene/polymer blends for enhancing gas-sensing performance are also reviewed. Finally, flexible gas sensors using soluble acenes and soluble acene/polymer blends are introduced, and future research perspectives in this field are suggested. [ABSTRACT FROM AUTHOR]

Spatial defect patterns on semiconductor wafer bin maps can provide valuable information on the root causes of process abnormalities. Thus, the identification of these patterns is important for quality management and yield improvement. To date, most research has focused on the case of a single defect pattern. The recognition of mixed-type patterns is challenging as the patterns need to be separated into clusters and each cluster classified as a predefined type of defect pattern. In this study, we propose a novel method for mixed-type defect pattern detection and recognition in wafer bin maps. We separate mixed-type defect patterns into clusters using tensor voting. Marching algorithms are then developed to extract region and curve patterns based on the structural saliency information of the voting process. Our method is inherently robust against noise and sufficiently flexible to deal with complex defect patterns. The results obtained using real and simulated data demonstrate the effectiveness of the proposed method in the detection and recognition of both single and mixed-type defect patterns. [ABSTRACT FROM AUTHOR]

Powder-type semiconductor photocatalysts are widely applicable but their defects (e.g. easy agglomeration during preparation and recyclability in the suspension system) limit their practical application. In the current study, perovskite oxide photocatalytic material was loaded onto a muscovite substrate to overcome the problems of low stability, easy agglomeration, and difficult recovery. A photocatalytically active LaNi0.95Fe0.05O3/muscovite composite material was synthesized by a sol-gel impregnation method. Phase composition, morphology, and interfacial interaction of the composites, denoted as LNFBY-x (x: mass ratio of LNF to muscovite), were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and other analytical methods. According to the results, the particle size of LNF nanoparticles was regulated effectively by compounding with muscovite, and the agglomeration of LNF decreased. LNF nanoparticles were distributed evenly and attached in dense fashion to the surface of muscovite, thereby increasing the contact area with the reaction medium. The nanoparticles were connected to the silicon-oxygen tetrahedral sheet of the muscovite via Si–O–La, Si–O–Ni, and Si–O–Fe bonds, which increased the bonding strength between the composite components and expedited the transfer of photogenerated charge. More highly active oxygen species were produced, and a growing number of chemically active moieties (٠O2- and ٠OH) was generated in the photocatalytic reaction. LNFBY-1.00 demonstrated the best photocatalytic activity. A degradation rate of methyl orange of 99.03% was achieved after visible-light irradiation for 120 min, which decreased to 75.75% after five repeated uses, thereby indicating high stability and recycling ability. The photocatalytic LaNi0.95Fe0.05O3/muscovite composite material exhibited potential for application in environmental remediation practices. [ABSTRACT FROM AUTHOR]

The 1.24 eV bandgap, 18.8% power conversion efficiency Ag‐alloyed chalcopyrite (Ag,Cu)(In,Ga)Se2 (ACIGS) solar cells are characterized to relate voltage and efficiency improvements to electro‐optical (EO) characteristics. Shockley–Read–Hall recombination center defect density, identified and characterized through deep level transient spectroscopy and time‐resolved photoluminescence (TRPL), is reduced through potassium and copper treatment optimization. Concomitantly, longer minority carrier lifetimes are achieved, which increases open‐circuit voltage (VOC). Near‐conduction band defects associated in earlier studies with light‐induced current instability are also mitigated. Analysis of charge‐carrier dynamics after single‐ and two‐photon excitation is used to separate recombination at the front interface and in the absorber bulk. From TRPL decay simulations, the authors estimate ranges of key solar cell material characteristics: bulk carrier lifetime τbulk = 110–210 ns, charge‐carrier mobility μ = 110–160 cm2 V−1 s−1, and front interface recombination velocity Sfront = 700–1050 cm s−1. This lowest‐reported Sfront for ACIGS absorbers originates from the notched conduction band grading, which also makes the impact of the back interface recombination negligible. It is suggested in the results that solar cell performance enhancements can be made most readily with two distinct strategies: improving device architecture and reducing semiconductor defect densities. Using these approaches, power conversion efficiency in large‐area solar cells is improved by 1.1% absolute. [ABSTRACT FROM AUTHOR]

A thin, lightweight, flexible solar cell is developed that maximizes the power‐to‐mass ratio under AM0 illumination and has a competitive efficiency after typical high energy electron irradiation. The inverted metamorphic triple junction (IMM3J) solar cells with Ga0.51In0.49P/GaAs/Ga0.73In0.27As subcells are grown on GaAs substrates and have a total epitaxy thickness of about 10 μm. After epitaxial growth, the inverted layer stack is metallized, with the metal serving as back‐contact, back reflector and support layer for the ultra‐thin solar cells before the GaAs substrate is separated by an epitaxial lift‐off (ELO) process. The nondestructive nature of the ELO process makes multiple reuses of the GaAs substrate possible. The solar cell structure is optimized for maximum EOL efficiency, that is, after 1‐MeV electron irradiation with a fluence of 1 × 1015 cm−2, by means of simulations that include the irradiation induced defects in the various semiconductor alloys. Assuming realistic charge carrier lifetime in the materials, we predict a near‐term efficiency potential for the IMM3J ELO of 30.9% under AM0 illumination before and 26.7% after irradiation. Several IMM3J ELO solar cells with an area of approximately 20 cm2 from different development stages were tested under AM0 illumination. The newest solar cells (generation III) with a mass density of only 13.2 mg/cm2 reach conversion efficiencies of 30.2% at 25°C. The resulting power‐to‐mass ratio of 3.0 W/g for the bare solar cell is one of the highest published ratios. After irradiation, a conversion efficiency of 25.4% was measured for "generation II" devices under AM0 illumination, which corresponds to a power‐to‐mass ratio of 2.6 W/g. IMM3J ELO solar cells from "generation I" were also tested for mechanical stability as "de‐risking" test of this new cell technology. No degradation of the cell performance was found after dipping the cell in liquid N2 and then heating up to 25°C for five times, despite of strong deformation of the flexible cell during the temperature cycle. [ABSTRACT FROM AUTHOR]

ZnWO4 nanomaterials are gaining attention as a kind of multifunctional material in the field of electrochemical energy storage and photocatalysis. However, the controllable adjustment of their nanomorphology and bandgap width limit their wide application. So the nanostructured bifunctional Zn1−xCexWO4 (x = 0.020, 0.022, 0.030) with tunable nanomorphology and bandgap width were prepared by a simple one-step hydrothermal method in this work. On the one hand, the microscopic morphology of the Zn1−xCexWO4 was changed from clusters to nanosheets with the addition of Ce4+. On the other hand, the doping of Ce4+ generated oxygen vacancies and formed defect states in the ZnWO4 semiconductor, reducing the energy bandgap width. Zn1−xCexWO4 (x = 0.022) with the optimal doping ratio (nCe/(nCe + nZn) = 0.022) obtained a specific capacitance of 267.091 F g−1 at a current density of 1 A g−1 and an electrolyte of 6 M KOH, which is 3.7 times as great as the specific capacitance of ZnWO4 (70.545 F g−1). In addition, the catalytic efficiency of Zn1−xCexWO4 (x = 0.022) for Rhodamine B (RhB) reached 99.541% in 4.5 h. The doping of Ce4+ can achieve the dual modulation of the morphology and bandgap width of ZnWO4, thus enhancing the electrochemical performance and photocatalytic degradation performance of ZnWO4. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) semiconducting monolayers such as transition metal dichalcogenides (TMDs) are promising channel materials to extend Moore's Law in advanced electronics. Synthetic TMD layers from chemical vapor deposition (CVD) are scalable for fabrication but notorious for their high defect densities. Therefore, innovative endeavors on growth reaction to enhance their quality are urgently needed. Here, we report that the hydroxide W species, an extremely pure vapor phase metal precursor form, is very efficient for sulfurization, leading to about one order of magnitude lower defect density compared to those from conventional CVD methods. The field-effect transistor (FET) devices based on the proposed growth reach a peak electron mobility ~200 cm2/Vs (~800 cm2/Vs) at room temperature (15 K), comparable to those from exfoliated flakes. The FET device with a channel length of 100 nm displays a high on-state current of ~400 µA/µm, encouraging the industrialization of 2D materials. Chemical vapor deposition enables the scalable production of 2D semiconductors, but the grown materials are usually affected by high defect densities. Here, the authors report a hydroxide vapour phase deposition method to synthesize wafer-scale monolayer WS2 with reduced defect density and electrical properties comparable to those of exfoliated flakes. [ABSTRACT FROM AUTHOR]

Ion implantation is usually used for semiconductor doping and isolation, which creates defects in semiconductors. ZnO is a promising semiconductor and has a variety of applications, such as for use in transparent electronics, optoelectronics, chemical and biological sensors, etc. In this work, ZnO nanorods were grown on Si (100) substrates by the process of chemical bath deposition and then annealed in an O2 atmosphere at 350 and 600 °C for 1 h to introduce different kinds of defects. The as-grown nanorods and the nanorods that annealed were irradiated simultaneously by 180 keV H+ ions at room temperature with a total dose of 8.0 × 10 15   ions / cm 2 . The radiation effects of the H+ ions, effects of the pre-existed defects on the radiation resistance, and the related mechanisms under irradiation were investigated. The crystal and optical properties of the ZnO nanorods after H+ ion irradiation were found to depend upon the pre-existed defects in the nanorods. The existence of the appropriate concentration of oxygen interstitials in the ZnO nanorods caused them to have good radiation resistance. The thermal effects of irradiation played an important role in the property variation of nanorods. The temperature of the nanorods under 180 keV H+ ion bombardment was around 350 °C. [ABSTRACT FROM AUTHOR]

[Display omitted] • ZnIn 2 S 4 with strongly coupled interface was prepared by a hydrothermal method for piezoelectric photoelectrochemical reactions. • The coupled interfaces provides more active sites, which enhances the piezoelectrically polarized electric field strength. • The ultrasonic vibration enhanced ZnIn 2 S 4 nanoflowers are beneficial to carrier transport and transfer. • The photocurrent density of ZnIn 2 S 4 with strongly coupled interfaces reaches 0.46 mA/cm2 under ultrasonic conditions. In the process of photoelectrochemical (PEC) hydrodecomposition, it is important to design photoelectrode materials with low cost, high charge separation efficiency and low charge recombination rate. Herein, 2D-3D strongly coupled ZnIn 2 S 4 /β-CdS nanocomposites were prepared by a two-step hydrothermal method. Meanwhile, the piezoelectric polarization was used to induce its generation of built-in electric field, which suppressed the secondary compounding of photogenerated charge carriers caused by the interfacial structural defects of the semiconductor heterojunction. The results show that ZnIn 2 S 4 /β-CdS has better photoelectrochemical decomposition ability of water under ultrasound, and its photocurrent density increases with the increase of ultrasound frequency, reaching a maximum value of 0.46 mA·cm−2 at 1.23 V RHE , which is 3.5 times higher than that before ultrasound. In addition, by comparing the significant increase of photocurrent conversion efficiency under the applied bias voltage before and after ultrasound, it can be concluded that the enhanced catalytic activity of ZnIn 2 S 4 /β-CdS is attributed to the efficient coupling effect between ZnIn 2 S 4 and β-CdS under ultrasound conditions. This coupling effect enables the fast electron transfer at the interface between ZnIn 2 S 4 and β-CdS. Consequently, this strongly coupled nanocomposite will provide inspiration for further construction of nanocomposites for photocatalytic decomposition of water. [ABSTRACT FROM AUTHOR]

Reverse biasing triple-junction GaInP/Ga(In)As/Ge solar cells may affect their performance by the formation of permanent shunts even if the reverse breakdown voltage is not reached. In previous works, it was observed that, amid the three components, GaInP subcells are more prone to degrade when reverse biased suffering permanent damage, although they present an initial good performance. The aim of this work is, firstly, to study the characteristics of the defects that cause the catastrophic failure of the devices. For this, GaInP isotype solar cells were analysed by visual inspection and electroluminescence maps and submitted to reverse bias stress test. We find that specific growth defects (i.e. hillocks), when covered with metal, cause the degradation in the cells. SEM cross-section imaging and EDX compositional analysis of these defects reveal their complex structures, which in essence consist of material abnormally grown on and around particles present on the wafer surface before growth. The reverse bias stress test is proposed as a screening method to spot defects hidden under the metal that may not be detected by conventional screening methods. By applying a quick reverse bias stress test, we can detect those defects that cause the degradation of devices at voltages below the breakdown voltage and that may also affect their long-term reliability. • Application of reverse bias stress tests to GaInP isotype solar cells. • Degradation of devices that seem to be healthy according to their initial I-V curve. • Detection of the type of defect responsible for the degradation at reverse bias. • Physical explanation of the possible failure mechanism at the defects. • A reverse bias stress test is proposed as a screening process to spot these defects. [ABSTRACT FROM AUTHOR]

In wafer map defect pattern recognition, deep learning methods are predominantly used. These models autonomously learn features without explicit human intervention due to their black-box type network architectures. While preceding feature extraction and modality representation may seem neglected in deep learning for wafer map defect pattern recognition, we addressed this question by proposing an innovative approach. Our proposed method employs an antecedent feature learning module to create a more compact and informative hash modality representation from input wafer maps. The method exceeds in achieving high recall, crucial for identifying actual defective wafers as much as possible in semiconductor manufacturing, where defects can impact integrated circuit functionality and reliability. Smaller-sized hash modalities against larger wafer maps allow the same model to speed up the process and require fewer computational resources. [ABSTRACT FROM AUTHOR]

[Display omitted] Precisely manipulating defects in semiconductor is an effective way to improve their photocatalytic activity. In this work, bismuth oxychloride (BiOCl)/reduced graphene oxide (RGO) nanocomposites with abundant oxygen vacancies (OVs) are successfully constructed by a facile solvothermal method. BiOCl nanosheets are uniformly distributed on the RGO with superior conductivity. The RGO served as a pivotal charge transmission bridge substantially accelerates the transfer of photogenerated charge carriers, resulting in the improvement of the charge separation efficiency. The abundant oxygen vacancies in BiOCl/RGO nanocomposites increase light harvesting and enhance the adsorption of O 2 to promote the formation of superoxide free radicals (·O 2 −). By virtue of these merits, the unique BiOCl/RGO nanocomposite shows excellent degradation efficiency. When the mass ratio of RGO was 2 %, 99.07 % of 20 mg/L(100 mL) methyl orange (MO) was removed after 80 min, which was much higher than that of pure BiOCl. [ABSTRACT FROM AUTHOR]

With increasing importance of germanium (Ge) for semiconductor quantum technologies, the necessity of growing defect-free Ge films has become crucial. Here, Ge homoepitaxial growth experiments were conducted using molecular beam epitaxy (MBE). This requires a smooth ( σ r m s ≤ 10 Å) and contamination-free substrate surface. We have shown that common ex-situ wet chemical cleaning methods are not sufficient. Foreign atoms like carbon stick to the substrate surface and tend to form clusters which results in macroscopic growth defects which are referred here as pits. The density of such pits is in the range of 1 0 6 to 1 0 9 cm−2. The formation and characteristics of the pits have been investigated. Pits emerge after a growth at 370 °C with a thickness of above 5 nm. At growth temperatures lower than 300 °C, the density of pits increases, while it decreases at temperatures higher than 400 °C. Pits can be faceted with the main facets being {1 1 3} and {3 15 23}. Furthermore, a procedure is presented involving a Ge buffer growth at room temperature with a high growth rate (0.02 nm/s). This leads to a coverage of present contamination and the formation of a new substrate surface which prevent pit formation. [Display omitted] • Molecular beam epitaxy of defect-free germanium homoepitaxial layers. • Investigation of wet chemical surface cleaning methods of germanium. • Characterization of size and facets of macroscopic growth defects such as pits. • Mechanism of pit formation based on AFM, SEM, and SIMS investigations. [ABSTRACT FROM AUTHOR]

The Point Defect Model was successfully developed to study the passivation of 316LN. Steel's passive film exhibits n-type semi-conductivity with interstitial cations as the dominant point defect. The transfer coefficients α i and rate constants k i are independent of the applied potential but vary with temperature. The electronic structure of the barrier layer (bl) is discussed as a degenerate defect semiconductor in which the bl comprises essentially the depletion zone with the electronic charge and the electron-hole charge being concentrated at the metal/bl and the bl/solution interfaces, respectively. The closest classical analog is postulated to be a tunnel diode. • The Point defect model (PDM) is successfully applied to studying the passivation of 316LN in synthetic seawater. • The dominant point defect within the passive film of 316LN is the interstitial cation. • The rate constants of defect reactions for 316LN are independent of the applied potential. • The near-normal distribution of breakdown potential of 316LN is consistent with the PDM calculation. [ABSTRACT FROM AUTHOR]

Introducing defects is an effective strategy to improve the sensitivity of sulfide semiconductor sensors. In this study, ZnO obtained by calcining ZIF-8 was used as the core, and ZnIn 2 S 4 flakes were grown in situ on the outer surface of ZnO to construct a flower-cluster ZnO@ZnIn 2 S 4 composite material with an internal rich S-vacancy. The prepared ZnO@ZnIn 2 S 4 has a well-contacted ІІ-type heterojunction. Compared with ZnIn 2 S 4 , the response value of ZnO@ZnIn 2 S 4 to triethylamine gas was increased by 4.9 times, and the response recovery time was shortened from 932 s to 100 s. At a working temperature of 180°C, ZnO@ZnIn 2 S 4 exhibits a response to triethylamine that is 47.2 times higher than the response to other gases, demonstrating its specific selective response to triethylamine molecules. ZnO@ZnIn 2 S 4 can maintain a stable response to triethylamine molecules for a long time in a complex humidity environment. The selective mechanism of material selection was analyzed from the perspectives of molecular attack, molecular polarity differences, and spatial size matching. They are using calcined MOF materials as the core has excellent potential for improving the gas-sensitive response performance of materials. The explanation of the specific selectivity mechanism is positively inspiring for the construction and performance optimization of high-performance triethylamine response materials. • A flower-like structured ZnO@ZnIn 2 S 4 composite semiconductor material with a rich S vacancy was prepared. • Inducing Zn-S bond breakage creates a large number of S vacancies within ZnIn 2 S 4 structure. • At a working temperature of 180°C, ZnO@ZnIn 2 S 4 exhibited excellent selectivity towards triethylamine gas in gas tests. • Under long-term high humidity conditions, ZnO@ZnIn 2 S 4 maintained a stable response to triethylamine. • The specific selectivity mechanism of the material was explained from multiple perspectives. [ABSTRACT FROM AUTHOR]

We propose a dielectric-screening-enhancement effect for perovskite defects by using high dielectric constant organic semiconductors, thus considerably suppressing nonradiative recombination beyond defect passivation. More importantly, organic–inorganic hybrid pero-SCs with robust stabilities exhibited boosted PCEs of 23.35% (0.062 cm2) and 21.93% (1 cm2), showing less dependence. [Display omitted] Perovskite solar cells (pero-SCs) performance is essentially limited by severe non-radiative losses and ion migration. Although numerous strategies have been proposed, challenges remain in the basic understanding of their origins. Here, we report a dielectric-screening-enhancement effect for perovskite defects by using organic semiconductors with finely tuned molecular structures from the atoms level. Our method produced various perovskite films with high dielectric constant values, reduced charge capture regions, suppressed ion migration, and it provides an efficient charge transport pathway for suppressing non-radiative recombination beyond the passivation effect. The resulting pero-SCs showed a promising power conversion efficiency (PCE) of 23.35% with a high open-circuit voltage (1.22 V); and the 1-cm2 pero-SCs maintained an excellent PCE (21.93%), showing feasibility for scalable fabrication. The robust operational and thermal stabilities revealed that this method paved a new way to understand the degradation mechanism of pero-SCs, promoting the efficiency, stability and scaled fabrication of the pero-SCs. [ABSTRACT FROM AUTHOR]

Machine-learning force fields (MLFF) should be accurate, computationally and data efficient, and applicable to molecules, materials, and interfaces thereof. Currently, MLFFs often introduce tradeoffs that restrict their practical applicability to small subsets of chemical space or require exhaustive datasets for training. Here, we introduce the Bravais-Inspired Gradient-Domain Machine Learning (BIGDML) approach and demonstrate its ability to construct reliable force fields using a training set with just 10–200 geometries for materials including pristine and defect-containing 2D and 3D semiconductors and metals, as well as chemisorbed and physisorbed atomic and molecular adsorbates on surfaces. The BIGDML model employs the full relevant symmetry group for a given material, does not assume artificial atom types or localization of atomic interactions and exhibits high data efficiency and state-of-the-art energy accuracies (errors substantially below 1 meV per atom) for an extended set of materials. Extensive path-integral molecular dynamics carried out with BIGDML models demonstrate the counterintuitive localization of benzene–graphene dynamics induced by nuclear quantum effects and their strong contributions to the hydrogen diffusion coefficient in a Pd crystal for a wide range of temperatures. Most machine-learning force fields dismiss long-range interactions. Here the authors demonstrate the BIGDML approach for building materials' potential energy surfaces that enables a broad range of materials simulations within accuracies better than 1 meV/atom using just 10–200 structures for training. [ABSTRACT FROM AUTHOR]

The effect of a weak magnetic field (B = 0.17 T) and X-irradiation (D < 520 Gy) on the rearrangement of the defective structure of near-surface p-type silicon layers was studied. It was established that the effect of these external fields increases the positive accumulated charge in the region of spatial charge (RSC) and in the SiO2 dielectric layer. This can be caused by both defects in the near-surface layer of the semiconductor and impurities contained in the dielectric layer, which can generate charge carriers. It was found that the near-surface layers of the barrier structures contain only one deep level in the silicon band gap, with an activation energy of Ev + 0.38 eV. This energy level corresponds to a complex of silicon interstitial atoms SiI+SiI. When X-irradiated with a dose of 520 Gy, a new level with the energy of Ev + 0.45 eV was observed. This level corresponds to a point boron radiation defect in the interstitial site (BI). These two types of defect are effective in obtaining charge carriers, and cause deterioration of the rectifier properties of the silicon barrier structures. It was established that the silicon surface is quite active, and adsorbs organic atoms and molecules from the atmosphere, forming bonds. It was shown that the effect of a magnetic field causes the decay of adsorbed complexes at the Si–SiO2 interface. The released hydrogen is captured by acceptor levels and, as a result, the concentration of more complex Si–H3 complexes increases that of O3–Si–H. [ABSTRACT FROM AUTHOR]

Development of highly efficient and stable lateral organic circularly polarized light photodetector is a fundamental prerequisite for realization of circularly polarized light integrated applications. However, chiral semiconductors with helical structure are usually found with intrinsically low field-effect mobilities, which becomes a bottleneck for high-performance and multi-wavelength circularly polarized light detection. To address this problem, here we demonstrate a novel strategy to fabricate multi-wavelength circularly polarized light photodetector based on the donor-acceptor heterojunction, where efficient exciton separation enables chiral acceptor layer to provide differentiated concentration of holes to the channel of organic field-effect transistors. Benefitting from the low defect density at the semiconductor/dielectric interface, the photodetectors exhibit excellent stability, enabling current roll-off of about 3–4% over 500 cycles. The photocurrent dissymmetry value and responsivity for circularly polarized light photodetector in air are 0.24 and 0.28 A W−1, respectively. We further demonstrate circularly polarized light communication based on a real-time circularly polarized light detector by decoding the light signal. As the proof-of-concept, the results hold the promise of large-scale circularly polarized light integrated photonic applications. Here, the authors report a strategy to fabricate multi-wavelength circularly polarized light photodetectors consisting of bilayer donor-acceptor heterojunctions with chiral active layers. [ABSTRACT FROM AUTHOR]

Once the optical, electronic, or photocatalytic properties of a semiconductor are set by adjusting composition, crystal phase, and morphology, one cannot change them anymore, respectively, on demand. Materials enabling postsynthetic and reversible switching of features such as absorption coefficient, bandgap, or charge carrier dynamics are highly desired. Hybrid perovskites facilitate exceptional possibilities for progress in the field of smart semiconductors because active organic molecules become an integral constituent of the crystalline structure. This paper reports the integration of ferrocene ligands into semiconducting 2D phases based on lead bromide. The complex crystal structures of the resulting, novel ferrovskite (≃ ferrocene perovskite) phases are determined by 3D electron diffraction. The ferrocene ligands exhibit strong structure‐directing effects on the 2D hybrid phases, which is why the formation of exotic types of face‐ and edge‐sharing lead bromide octahedra is observed. The bandgap of the materials ranges from 3.06 up to 3.51 eV, depending on the connectivity of the octahedra. By deploying the redox features of ferrocene, one can create defect states or even a defect band leading to control over the direction of exciton migration and energy transport in the semiconductor, enabling fluorescence via indirect to direct gap transition. [ABSTRACT FROM AUTHOR]

Featured Application: Deep-level transient spectroscopy; any applications requiring extraction of rate and initial value of decaying exponentials. A mathematical method is presented for the extraction of defect parameters from the multiexponential decays generated during deep-level transient spectroscopy experiments. Such transient phenomenon results from the ionization of charge trapped in defects located in the depletion width of a semiconductor diode. From digitized transients acquired at fixed temperatures, this method produces a rate–domain spectral signature associated with all defects in the semiconductor. For signal-to-noise ratio of 1000, defect levels with carrier emission rates differing by as little as 1.5 times may be distinguished. [ABSTRACT FROM AUTHOR]

Organic-inorganic metal halide perovskites have attracted a considerable interest in the photovoltaic scientific community demonstrating a rapid and unprecedented increase in conversion efficiency in the last decade. Besides the stunning progress in performance, the understanding of the physical mechanisms and limitations that govern perovskite solar cells are far to be completely unravelled. In this work, we study the origin of their hysteretic behaviour from the standpoint of fundamental semiconductor physics by means of technology computer aided design electrical simulations. Our findings identify that the density of shallow interface defects at the interfaces between perovskite and transport layers plays a key role in hysteresis phenomena. Then, by comparing the defect distributions in both spatial and energetic domains for different bias conditions and using fundamental semiconductor equations, we can identify the driving force of hysteresis in terms of slow recombination processes and charge distributions. [ABSTRACT FROM AUTHOR]

Expressions are obtained for the electron current density distribution over the thickness of the base of a three-layer semiconductor double-injection diode made of semiconductors with deep impurity levels, which is associated with an increase in the bipolar drift mobility of current-carrying carriers. Analytical expressions for the voltage -- current characteristics of such diodes are obtained. The minimum voltage at the base of the diode is determined. [ABSTRACT FROM AUTHOR]

Analytical expressions are obtained for the dependence of the concentration of nonequilibrium current carriers on the parameters of deep impurities in compensated semiconductors, where the capture of carriers to deep impurity levels is taken into account. It is pointed out that the relationship between the concentration of nonequilibrium carriers is greatly complicated due to the variety of recombination processes and the generation of current carriers through multiply charged impurities. In this connection, below we analyze the dependences of nonequilibrium electrons and holes on the parameters of deep impurity centers. [ABSTRACT FROM AUTHOR]

Semiconductors are essential components in many electronic devices. Because wafers are produced quickly and in large quantities, defects occur that adversely affect semiconductor properties. This makes it necessary to install powerful and robust inspection systems which use artificial intelligence techniques in the early stages of the manufacturing chain in order to detect and classify those defects. This paper proposes a method for defect detection and classification on images of semiconductor wafer materials obtained by means of a scanning electron microscope based in the following stages: (i) use of computer vision techniques to isolate the defect from the background; (ii) use of several descriptors based on shape, size, texture, histogram, and key-points to create a feature vector for the characterization of the defect; (iii) application of an exhaustive search as a feature selection method to determine the optimal subset of feature descriptors; and (iv) evaluation of the feature descriptors by using a support vector machine classifier providing the optimal set with highest F1-score metrics. Finally, the effectiveness of the proposed approach is compared with five popular feature selection methods, reporting better classification results than the latter. [ABSTRACT FROM AUTHOR]

Schottky barrier diodes, developed by low-cost techniques and low temperature processes (LTP-SBD), have gained attention for different kinds of novel applications, including flexible electronic fabrication. This work analyzes the behavior of the I–V characteristic of solution processed, ZnO Schottky barrier diodes, fabricated at a low temperature. It is shown that the use of standard extraction methods to determine diode parameters in these devices produce significant dispersion of the ideality factor with values from 2.2 to 4.1, as well as a dependence on the diode area without physical meaning. The analysis of simulated I–V characteristic of LTP-SBD, and its comparison with experimental measurements, confirmed that it is necessary to consider the presence of a density of states (DOS) in the semiconductor gap, to understand specific changes observed in their performance, with respect to standard SBDs. These changes include increased values of Rs, as well as its dependence on bias, an important reduction of the diode current and small rectification values (RR). Additionally, it is shown that the standard extraction methodologies cannot be used to obtain diode parameters of LTP-SBD, as it is necessary to develop adequate parameter extraction methodologies for them. [ABSTRACT FROM AUTHOR]

Charge carrier transport and accumulation in silicon carbide (SiC) wide bandgap semiconductors caused by the defect and impurity are likely to lead to serious performance degradation and failure of the semiconductor materials, and the high temperature effect makes the charge behaviors more complex. In this paper, charge carrier transport and accumulation in semi-insulating vanadium doped 4H–SiC crystal materials and the correlated temperature effect were investigated. Attempts were made to address the effect of deep trap levels on carrier transport. A combination of pulsed electro-acoustic direct space charge probing, an electrical conduction·current experiment, and x-ray diffraction measurement was employed. Space charge quantities including trap depth and trap density were extracted. The results show hetero-charge accumulation at adjacent electrode interfaces under a moderate electrical stress region (5–10 kV/mm). The charge carrier transports along the SiC bulk and is captured by the deep traps near the electrode interfaces. The deep trap energy levels originating from the vanadium dopant in SiC crystals are critical to carrier transport, providing carrier trapping sites for charges. This paper could promote the understandings of the carrier transport dynamic and trap energy level characteristic of SiC crystal materials. [ABSTRACT FROM AUTHOR]

In semiconductor manufacturing, surface defects on wafers must be classified accurately for better yield management. To manage the increasing chip demand in speed and scale, automatic defect classification (ADC) system has been introduced. Most existing ADC systems utilize machine learning-based algorithms that require manual feature extractions and manual intervention such as human-based classification for accuracy and consistency. These methods are labour-intensive, unreliable, and highly prone to human error. Therefore, by leveraging on deep learning technologies, this paper proposes DLADC - an ADC system using a deep convolutional neural network (CNN) architecture for detecting and classifying semiconductor wafer surface defects. The proposed system takes Scanning Electron Microscope (SEM) images as input and outputs the defect's class and location. The proposed system also sub-classifies particle-type defects into various sizing groups. Identification of defect types that occurred on wafer surfaces allows for better defect root cause analysis, and the additional information of defect size further serves as an essential indication of the origin of machine failure. The proposed DLADC promotes 2x time saving while achieving an improved accuracy of 93.69% based on experimental results with a real semiconductor defect dataset. Not only does DLADC outperforms the 70% classification performance of trained operators, but it also surpasses the 90% classification performance of industrially pragmatic defect classification. [ABSTRACT FROM AUTHOR]

Doping transition metal impurities in semiconductor quantum dots (QDs) has been shown to offer an effective handle over their electronic, optical and magnetic properties. Incorporation of more than one type of transition ions in same QDs is nontrivial due to different thermodynamic constraints, however, it can provide attractive properties and insights to meet recent challenges in the field of luminescent and magnetic materials. Herein, we present a solution‐processed controlled synthesis of Mn and Ni codoped CdS colloidal QDs which show dual emission due to two different impurities. Controlled doping helps to understand the decay dynamics of exciton through various decay channels. Based on the competition between Mn and Ni dopant states, we observe reliable signatures for the short‐lived transient charge transfer of the photogenerated hole to the excited state of Mn and then to the Ni state. Along with the interesting excitonic dynamics, we also observe significant enhancement of magnetization due to the codoping. [ABSTRACT FROM AUTHOR]

Researchers commonly anneal metals, alloys, and semiconductors to repair defects and improve microstructures via recrystallization. Theoretical studies indicate that simulated annealing on biological macromolecules helps predict the final structures with minimum free energy. Experimental validation of this homogenizing effect and further exploration of its applications are fascinating scientific questions that remain elusive. Here, we chose the apo-state 70S ribosome from Escherichia coli as a model, wherein the 30S subunit undergoes a thermally driven intersubunit rotation and exhibits substantial structural flexibility as well as distinct free energy. We experimentally demonstrate that annealing at a fast cooling rate enhances the 70S ribosome homogeneity and improves local resolution on the 30S subunit. After annealing, the 70S ribosome is in a nonrotated state with respect to corresponding intermediate structures in unannealed or heated ribosomes. Manifold-based analysis further indicates that the annealed 70S ribosome takes a narrow conformational distribution and exhibits a minimum- energy state in the free-energy landscape. Our experimental results offer a facile yet robust approach to enhance protein stability, which is ideal for high-resolution cryogenic electron micros- copy. Beyond structure determination, annealing shows great potential for synchronizing proteins on a single-molecule level and can be extended to study protein folding and explore conformational and energy landscapes. [ABSTRACT FROM AUTHOR]

Detecting defect patterns in semiconductors is very important for discovering the fundamental causes of production defects. In particular, because mixed defects have become more likely with the development of technology, finding them has become more complex than can be performed by conventional wafer defect detection. In this paper, we propose an improved U-Net model using a residual attention block that combines an attention mechanism with a residual block to segment a mixed defect. By using the proposed method, we can extract an improved feature map by suppressing irrelevant features and paying attention to the defect to be found. Experimental results show that the proposed model outperforms those in the existing studies. [ABSTRACT FROM AUTHOR]

Creating and manipulating multiple charge states of solitary defects in semiconductors is of essential importance for solitary defect electronics, but is fundamentally limited by Coulomb's law. Achieving this objective is challenging, due to the conflicting requirements of the localization necessary for the sizable band gap and delocalization necessary for a low charging energy. Here, using scanning tunneling microscopy/spectroscopy experiments and first-principles calculations, we realized exotic quinary charge states of solitary defects in two-dimensional intermetallic semiconductor Sn2Bi. We also observed an ultralow defect charging energy that increases sublinearly with charge number rather than displaying the usual quadratic behavior. Our work suggests a promising route for constructing multiple defect-charge states by designing intermetallic semiconductors, and opens new opportunities for developing quantum devices with charge-based quantum states. [ABSTRACT FROM AUTHOR]

Semiconductor manufacturing is on the cusp of a revolution – the Internet of Things (IoT). With IoT we can connect all the equipment and feed information back to the factory so that quality issues can be detected. In this situation, more and more edge devices are used in wafer inspection equipment. This edge device must have the ability to quickly detect defects. Therefore, how to develop a high-efficiency architecture for automatic defect classification to be suitable for edge devices is the primary task. In this paper, we present a novel architecture that can perform defect classification in a more efficient way. The first function is self-proliferation, using a series of linear transformations to generate more feature maps at a cheaper cost. The second function is self-attention, capturing the long-range dependencies of feature map by the channel-wise and spatial-wise attention mechanism. We named this method as self-proliferation-and-attention neural network (SP&A-Net). This method has been successfully applied to various defect pattern classification tasks. Compared with other latest methods, SP&A-Net has higher accuracy and lower computation cost in many defect inspection tasks. [ABSTRACT FROM AUTHOR]

This paper presents an automated high-speed die edge detection framework, based on improved K-Mean and landscape analysis, that is highly suitable to be implemented in precision engineering for optical non-destructive testing of die-level defects inspection in the semiconductor industry. This paper specifically aims to achieve high accuracy (or yield) of greater than 99.95% with stable performance within a short computation time (i.e. less than 20 ms). To demonstrate the applicability of the proposed framework, it is validated using three production units (i.e. Production unit A: 6000 units; Production unit B: 3500 units; Production unit C: 4000 units) and is benchmarked to two baseline edge detection methods, namely cross-correlation and normalised cross-correlation methods, as well as state-of-the-art vision libraries, recent works, and several conventional edge detection methods. The results obtained show that the proposed framework is capable of performing die edge detection with promising accuracy and stable performance by achieving 100.0% yield in all three production units, having outperformed the benchmarking methods. Also, the overall computation time (considering die edge detection and die rotation) of the proposed framework is short, at approximately 15 ms. [ABSTRACT FROM AUTHOR]

Ion implantation is widely used in the semiconductor industry as an important method of controlling the performance of semiconductor materials. As a 2D material with fantastic physical characteristics, MoS2 has been receiving extensive attention for its potential applications in electronic devices. N element is an impurity objectively existing in semiconductors. It may come from the semiconductor manufacturing process or the environment. Therefore, the effect of N element implantation on the material, electrical, and photoelectronic properties of MoS2 field effect transistor (FET) is reported. The results of Raman and photoluminescence (PL) shows that N‐ion implant caused the expansion of the MoS2 lattice and the disappearance of the characteristic peaks of PL. The prepared MoS2 FET exhibits a slow photoelectric response to 254 nm UV, and a fast photoelectric response to 650 and 532 nm lasers. After ion implant and annealing, the electrical performance and photocurrent of the MoS2 FET are significantly degraded. The research has a guiding role in impurity control in the semiconductor manufacturing process. [ABSTRACT FROM AUTHOR]

The dynamics of impurities that walk along a semiconductor layer assisted by thermal noise strength and quartic potential is explored analytically and numerically. Applying two cold spots in the vicinity of the quartic potential forces the system to undergo a phase transition from a single-well to a double-well effective potential. This also implies that the impurities (the positively charged particles) trapped by the quartic potential diffuses away from the central region and assemble around two peripheral regions (around local minima) of the semiconductor layer once the two cold spots are applied. The electrons, on the other hand, stay around the potential maxima where they occupy before cold spots are applied. The resulting charge distribution forms series of N–P–N junctions, indicating that our theoretical work gives a clue on how to fabricate artificial semiconductor layers. Moreover, the dynamics of these impurities as a function of model parameters is explored both analytically and with Monte Carlo simulation methods. In this work, not only we propose the ways of mobilizing (eradicating) unwanted dopants along the semiconductor layer but also we study the stochastic resonance for the impurity dynamics in the presence of a time-varying signal. Via Monte Carlo simulation approaches, we study how the signal-to-noise ratio as well as the spectral amplification depends on the model parameters. [ABSTRACT FROM AUTHOR]

A criterion for the stability of defects in semiconductor structures to the action of magnetic and electric fields, electromagnetic radiation, acoustic waves, mechanical stresses has been formulated. Analytical relations have been obtained for the threshold parameters of external fields, at which transformation of defects was observed. The results of calculations of the threshold values for the magnetic field induction that cause a change in the state of dislocations and defect clusters in semiconductor crystals have been presented. [ABSTRACT FROM AUTHOR]

In order to expand the technology of III-V semiconductor devices with quantum structures to both terrestrial and space use, radiation induced defects as well as native defects generated in the quantum structures should be clarified. Electrically active defects in GaAs p+n diodes with embedded ten layers of InAs quantum dots (QDs) are investigated using Deep Level Transient Fourier Spectroscopy. Both majority carrier (electron) and minority carrier (hole) traps are characterized. In the devices of this study, GaP layers are embedded in between the QD layers to offset the compressive stress introduced during growth of InAs QDs. Devices are irradiated with high energy protons for three different fluences at room temperature in order to characterize radiation induced defects. Seven majority electron traps and one minority hole trap are found after proton irradiation. It is shown that four electron traps induced by proton irradiation increase in proportion to the fluence, whereas the EL2 trap, which appears before irradiation, is not affected by irradiation. These defects correspond to electron traps previously identified in GaAs. In addition, a 0.53 eV electron trap and a 0.14 eV hole trap are found in the QD layers before proton irradiation. It is shown that these native traps are also unaffected by irradiation. The nature of the 0.14 eV hole trap is thought to be Ga-vacancies in the GaP strain balancing layers. [ABSTRACT FROM AUTHOR]

Point defects affect or even completely determine physical and chemical properties of semiconductors. Characterization of point defects based on experimental techniques alone is often inconclusive. In such cases, the combination of experiment and theory is crucial to gain understanding of the system studied. In this tutorial, we explain how and when such comparison provides new understanding of the defect physics. More specifically, we focus on processes that can be analyzed or understood in terms of configuration coordinate diagrams of defects in their different charge states. These processes include light absorption, luminescence, and nonradiative capture of charge carriers. Recent theoretical developments to describe these processes are reviewed. [ABSTRACT FROM AUTHOR]