Metalorganic Chemical Vapor Deposition Gallium Nitride with Fast Growth Rate for Vertical Power Device Applications
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Thermoluminescence (TL) or thermally stimulated luminescence (TSL) spectroscopy is based on liberating charge carriers from traps in the bandgap by providing enough thermal energy to overcome the potential barrier of the traps. It provides a powerful tool to measure the positions of the localized states/traps in the bandgap. Despite that, its applications in semiconductors are very limited. Herein, the basics of TL spectroscopy and the recent advances in the technique with focus on cryogenic thermally stimulated photoemission spectroscopy (C‐TSPS) which extends TL measurements to cryogenic regime and allows the detection of very low concentrations of shallow and deep localized states is discussed. One goal herein is to introduce the reader to the use of TL and C‐TSPS in the characterization of semiconductors, explaining how it can be applied and demonstrating its advantages as a powerful tool for measuring shallow donor/acceptor ionization energies in semiconductors and as a method for characterizing compensating defects. The article also discusses interesting potential applications of C‐TSPS in new research areas such as corrosion and formation of oxide layers on metal surfaces.
Most electrical characterization of radiation damage to semiconductors is conducted on full devices or on low‐doped material. However, evaluating the radiation hardness is challenging in less mature semiconductor systems where low‐doped material is unavailable and full devices are difficult to realize. Herein, temperature‐dependent Hall effect measurements are used to demonstrate α particle‐induced radiation effects in p‐type 4H‐SiC with a room temperature hole concentration of . The 4H‐SiC is irradiated by α particles from a 210 Po source over a fluence of –. Modeling the hole concentration as a function of temperature shows that α radiation causes hole compensation through the introduction of hole traps. The radiation also induces a reduction in hole mobility due to an increase in defect‐related scattering centers. At low temperatures and increasingly higher fluences, the conduction mechanism changes from band conduction to another mechanism.
Abstract In complex systems with multiple variables monitored at high‐frequency, variables are not only temporally autocorrelated, but they may also be nonlinearly related or exhibit nonstationarity as the inputs or operation changes. One approach to handling such variables is to detrend them prior to monitoring and then apply control charts that assume independence and stationarity to the residuals. Monitoring controlled systems is even more challenging because the control strategy seeks to maintain variables at prespecified mean levels, and to compensate, correlations among variables may change, making monitoring the covariance essential. In this paper, a vector autoregressive model (VAR) is compared with a multivariate random forest (MRF) and a neural network (NN) for detrending multivariate time series prior to monitoring the covariance of the residuals using a multivariate exponentially weighted moving average (MEWMA) control chart. Machine learning models have an advantage when the data's structure is unknown or may change. We design a novel simulation study with nonlinear, nonstationary, and autocorrelated data to compare the different detrending models and subsequent covariance monitoring. The machine learning models have superior performance for nonlinear and strongly autocorrelated data and similar performance for linear data. An illustration with data from a reverse osmosis process is given.
This article synthesizes a filtering adaptive output feedback controller for multivariable nonlinear systems with mismatched uncertainties and unmodeled dynamics. The multivariable nonlinear systems under consideration have both matched and mismatched uncertainties, which satisfy the semiglobal Lipschitz condition. The unmodeled dynamics are bounded-input bounded-output stable. By adopting an estimation/cancellation strategy, a piecewise constant adaptive law drives the estimation error to zero at every time instant, which yields the adaptive parameters; a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters. The matched uncertainties are cancelled directly by adopting their opposite in the control signal, while a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. A feedforward control law is designed to track a given command. Since the virtual reference system defines the best performance that can be achieved by the closed-loop system, the uniform performance bounds are derived for the states and control signals via comparison. Both numerical and practical examples are provided to illustrate the effectiveness of the proposed filtering adaptive output feedback control architecture, comparisons with the model reference adaptive control demonstrates the superiority of the proposed control method.
Abstract Nuclear data are fundamental inputs to radiation transport codes used for reactor design and criticality safety. The design of experiments to reduce nuclear data uncertainty has been a challenge for many years, but advances in the sensitivity calculations of radiation transport codes within the last two decades have made optimal experimental design possible. The design of integral nuclear experiments poses numerous challenges not emphasized in classical optimal design, in particular, constrained design spaces (in both a statistical and engineering sense), severely under‐determined systems, and optimality uncertainty. We present a design pipeline to optimize critical experiments that uses constrained Bayesian optimization within an iterative expert‐in‐the‐loop framework. We show a successfully completed experiment campaign designed with this framework that involved two critical configurations and multiple measurements that targeted compensating errors in 239 Pu nuclear data.
Complex oxide films stabilized by epitaxial growth can exhibit large populations of point defects which have important effects on their properties. The site occupancy of pulsed laser-deposited epitaxial terbium iron garnet (TbIG) films with excess terbium (Tb) is analyzed, in which the terbium:iron (Tb:Fe)ratio is 0.86 compared to the stoichiometric value of 0.6. The magnetic properties of the TbIG are sensitive to site occupancy, exhibiting a higher compensation temperature (by 90 K) and a lower Curie temperature (by 40 K) than the bulk Tb 3 Fe 5 O 12 garnet. Data derived from X-ray core-level spectroscopy, magnetometry, and molecular field coefficient modeling are consistent with occupancy of the dodecahedral sites by Tb 3+ , the octahedral sites by Fe 3+ , Tb 3+ and vacancies, and the tetrahedral sites by Fe 3+ and vacancies. Energy dispersive X-ray spectroscopy in a scanning transmission electron microscope provides direct evidence of Tb Fe antisites. A small fraction of Fe 2+ is present, and oxygen vacancies are inferred to be present to maintain charge neutrality. In conclusion, variation of the site occupancies provides a path to considerable manipulation of the magnetic properties of epitaxial iron garnet films and other complex oxides, which readily accommodate stoichiometries not found in their bulk counterparts.
The optical properties of lead halide perovskite semiconductors in vicinity of the bandgap are controlled by excitons, so that investigation of their fundamental properties is of critical importance. The exciton Landé or g-factor g X is the key parameter, determining the exciton Zeeman spin splitting in magnetic fields. The exciton, electron, and hole carrier g-factors provide information on the band structure, including its anisotropy, and the parameters contributing to the electron and hole effective masses. Here, g X is measured by reflectivity in magnetic fields up to 60 T for lead halide perovskite crystals. The materials band gap energies at a liquid helium temperature vary widely across the visible spectral range from 1.520 up to 3.213 eV in hybrid organic–inorganic and fully inorganic perovskites with different cations and halogens: FA 0.9 Cs 0.1 PbI 2.8 Br 0.2 , MAPbI 3 , FAPbBr 3 , CsPbBr 3 , and MAPb(Br 0.05 Cl 0.95 ) 3 . The exciton g-factors are found to be nearly constant, ranging from +2.3 to +2.7. Thus, the strong dependences of the electron and hole g-factors on the bandgap roughly compensate each other when combining to the exciton g-factor. The same is true for the anisotropies of the carrier g-factors, resulting in a nearly isotropic exciton g-factor. The experimental data are compared favorably with model calculation results.
The inhomogeneous nucleation and growth of Li dendrite combined with the spontaneous side reactions with the electrolytes dramatically challenge the stability and safety of Li metal anode (LMA). Despite tremendous endeavors, current success relies on the use of significant excess of Li to compensate the loss of active Li during cycling. Herein, a near-surface Li + irrigation strategy is developed to regulate the inhomogeneous Li deposition behavior and suppress the consequent side reactions under limited Li excess condition. The conformal polypyrrole (PPy) coating layer on Cu surface via oxidative chemical vapor deposition technique can induce the migration of Li + to the interregional space between PPy and Cu, creating a near-surface Li + -rich region to smooth diffusion of ion flux and uniform the deposition. Moreover, as evidenced by multiscale characterizations including synchrotron high-energy X-ray diffraction scanning, a robust N-rich solid-electrolyte interface (SEI) is formed on the PPy skeleton to effectively suppress the undesired SEI formation/dissolution process. Strikingly, stable Li metal cycling performance under a high areal capacity of 10 mAh cm -2 at 2.0 mA cm -2 with merely 0.5 × Li excess is achieved. The findings not only resolve the long-standing poor LMA stability/safety issues, but also deepen the mechanism understanding of Li deposition process.
Abstract Application of biochar amendments in agricultural systems has received much attention in recent years. In this study, we assess the 5‐year impacts of biochar application on soil water and plant interactions for an irrigated fresh market tomato ( Solanum lycopersicum ) and a rainfed pasture ( Poaceae ) cropping system. In particular, we focus on three varieties of locally produced biochar from agricultural waste materials—almond shell, walnut shell, and almond pruning residues that are pyrolyzed using a mobile pyrolysis unit. We used the soil hydrological model HYDRUS‐1D to explicitly track seasonal and annual soil water fluxes through changes in water retention, drainage, evaporation, and plant water uptake under biochar application. Modeling results show that the application of biochar at 5% increased soil water availability within the top 20 cm for a rainfed system, irrespective of biochar amendment type. This is clearly indicative of higher plant water uptake and greater water use efficiency (WUE) under biochar application. In contrast, a similar biochar amendment for the irrigated system did not affect WUE, instead reducing seasonal soil evaporation loss and thereby reducing irrigation demand. In both cropping systems, year‐to‐year variability in precipitation significantly impacted the total amount of water saved under biochar application with certain amendments retaining more water than others. Given that biochar application increased water retention irrespective of cropping systems, we further used a simple approach to determine yield trade‐off, if any, between control and biochar treatments. Our economic balance clearly demonstrates that the water saved by amending soil with biochar does not offset the yield disparity if compensated with carbon credits and therefore, application of biochar should be actively considered for both its direct and indirect benefits to potential greenhouse gas mitigation (e.g., diverting orchard waste from open burning), water savings, and soil health.
We point out that neutrinos can have enhanced couplings to photons, if light (pseudo)scalar mediators are present, resulting in a potentially measurable neutrino polarizability. We show that the expected suppression from small neutrino masses can be compensated by the light mediator mass, generating dimension 7 Rayleigh operators at low scales. We explore the rich phenomenology of such models, computing in detail the constraints on the viable parameter space, spanned by the couplings of the mediator to neutrinos and photons. Finally, we build several explicit models that lead to an enhanced neutrino polarizability by modifying the inverse see-saw majoron, i.e., the pseudo-Nambu-Goldstone boson of the U(1) L global lepton number responsible for generating small neutrino masses.
Large primordial lepton flavor asymmetries with almost vanishing total baryon-minus-lepton number can evade the usual BBN and CMB constraints if neutrino oscillations lead to perfect flavor equilibration. Solving the momentum averaged quantum kinetic equations (QKEs) describing neutrino oscillations and interactions, we perform the first systematic investigation of this scenario, uncovering a rich flavor structure in stark contradiction to the assumption of simple flavor equilibration. We find (i) a particular direction in flavor space, ∆ne ≃ – 2/3 (– 1)∆n μ for normal (inverted) neutrino mass hierarchy, in which the flavor equilibration is efficient and primordial asymmetries are essentially unconstrained, (ii) a minimal washout factor, ∆$n_{e}^{2}$| BBN ≤ 0.03 (0.016) ∑ α ∆$n_{α}^{2}$| ini yielding a conservative estimate for the allowed primordial asymmetries in a generic flavor direction, and (iii) particularly strong or weak washout if one of the initial flavor asymmetries vanishes due to non-adiabatic muon- or electron-driven MSW transitions. These results open up the possibility of a first-order QCD phase transition facilitated by large lepton asymmetries as well as baryogenesis from large and compensated ∆n e = ∆n μ asymmetries. Our systematic approach of deriving momentum averaged QKEs includes collision terms beyond the damping approximation, energy transfer between the neutrino and electron-photon plasma, and provides a fast and reliable way to investigate the impact of primordial lepton asymmetries at the time of BBN. We publicly release the Mathematica code COFLASY-M on https://github.com/mariofnavarro/COFLASY which solves the QKEs numerically.
We propose a search at Mu3e for lepton flavor violating axion(-like) particles in μ → 3e + a decays. By requiring an additional e+e− pair from internal conversion, one can circumvent the calibration challenges which plague the μ → e + a channel for axions lighter than 20 MeV. Crucially, the corresponding reduction in signal rate is to a large extent compensated for by Mu3e’s ability to resolve highly collimated tracks. For phase I of Mu3e, we project a sensitivity to decay constants as high as 6 × 109 GeV which probes uncharted parameter space in scenarios of axion dark matter. The sensitivity to axions which couple primarily to right-handed leptons can be further improved by leveraging the polarisation of the muon beam.
We propose a new mechanism where asymmetric dark matter (ADM) and the baryon asymmetry are both generated in the same decay chain of a metastable weakly interacting massive particle (WIMP) after its thermal freezeout. Dark matter and baryons are connected by a generalized baryon number that is conserved, while the DM asymmetry and baryon asymmetry compensate each other. This unified framework addresses the DM-baryon coincidence while inheriting the merit of the conventional WIMP miracle in predicting relic abundances of matter. Examples of renormalizable models realizing this scenario are presented. These models generically predict ADM with sub-GeV to GeV-scale mass that interacts with Standard Model quarks or leptons, thus rendering potential signatures at direct detection experiments sensitive to low mass DM. Other interesting phenomenological predictions are also discussed, including: LHC signatures of new intermediate particles with color or electroweak charge and DM induced nucleon decay; the long-lived WIMP may be within reach of future high energy collider experiments.
Analogs of present-day rapid ice melt can be found in episodic discharges of icebergs that occurred during glacial periods called Heinrich events. This introduces excess meltwater into the North Atlantic and weakens the Atlantic thermohaline circulation (AMOC), triggering a hydrologic cycle–AMOC collapse feedback as the atmospheric energy transport compensates for reduced northward heat transport. Here we employ a novel series of 100-year North Atlantic “hosing” simulations to investigate atmospheric and oceanic energy transport response from freshwater forcing, focusing in particular on the role of atmospheric rivers (ARs) within atmospheric energy transport. Importantly, we use an “overwriting” methodology that allow us to attribute AMOC weakening to added North Atlantic meltwater and subsequent hydrologic cycle responses, respectively. In contrast to far-reaching response of transient eddies, our results show a substantial increase in moisture convergence from ARs that is geographically constrained to the North Atlantic midlatitudes. Such AR changes nevertheless comprise an important component of net precipitation changes over the Euro-Atlantic sector, with the amount being comparable to that from transient eddies over the subpolar Atlantic. Over the course of the century-long simulations, we demonstrate that hydrologic cycle responses to North Atlantic freshening and subsequent feedbacks, including those from ARs, account for approximately half of the simulated AMOC collapse. Furthermore, our work highlights the dynamics of atmospheric moisture transport response to North Atlantic freshening events and elucidates how intensifying moisture transport may accelerate AMOC collapse in the future.
ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.
Motor systems show an overall robustness, but because they are highly nonlinear, understanding how they achieve robustness is difficult. In many rhythmic systems, robustness against perturbations involves response of both the shape and the timing of the trajectory. This makes the study of robustness even more challenging. To understand how a motor system produces robust behaviors in a variable environment, we consider a neuromechanical model of motor patterns in the feeding apparatus of the marine mollusk Aplysia californica (Shaw et al. in J Comput Neurosci 38(1):25–51, 2015; Lyttle et al. in Biol Cybern 111(1):25–47, 2017). We established in (Wang et al. in SIAM J Appl Dyn Syst 20(2):701–744, 2021. https://doi.org/10.1137/20M1344974) the tools for studying combined shape and timing responses of limit cycle systems under sustained perturbations and here apply them to study robustness of the neuromechanical model against increased mechanical load during swallowing. Interestingly, we discover that nonlinear biomechanical properties confer resilience by immediately increasing resistance to applied loads. In contrast, the effect of changed sensory feedback signal is significantly delayed by the firing rates’ hard boundary properties. Our analysis suggests that sensory feedback contributes to robustness in swallowing primarily by shifting the timing of neural activation involved in the power stroke of the motor cycle (retraction). This effect enables the system to generate stronger retractor muscle forces to compensate for the increased load, and hence achieve strong robustness. The approaches that we are applying to understanding a neuromechanical model in Aplysia, and the results that we have obtained, are likely to provide insights into the function of other motor systems that encounter changing mechanical loads and hard boundaries, both due to mechanical and neuronal firing properties.
Abstract Main conclusion The oxidative pentose phosphate pathway provides cytosolic NADPH yet reduces carbon and energy use efficiency. Repressing this pathway and introducing cytosolic NADPH-dependent malate dehydrogenase may increase crop yields by ≈5%. Abstract Detailed knowledge about plant energy metabolism may aid crop improvements. Using published estimates of flux through central carbon metabolism, we phenotype energy metabolism in illuminated Camelina sativa leaves (grown at 22 °C, 500 µmol photons m −2 s −1 ) and report several findings. First, the oxidative pentose phosphate pathway (OPPP) transfers 3.3% of the NADPH consumed in the Calvin–Benson cycle to the cytosol. NADPH supply proceeds at about 10% of the rate of net carbon assimilation. However, concomitantly respired CO 2 accounts for 4.8% of total rubisco activity. Hence, 4.8% of the flux through the Calvin–Benson cycle and photorespiration is spent on supplying cytosolic NADPH, a significant investment. Associated energy requirements exceed the energy output of the OPPP. Thus, autotrophic carbon metabolism is not simply optimised for flux into carbon sinks but sacrifices carbon and energy use efficiency to support cytosolic energy metabolism. To reduce these costs, we suggest bioengineering plants with a repressed cytosolic OPPP, and an inserted cytosolic NADPH-dependent malate dehydrogenase tuned to compensate for the loss in OPPP activity (if required). Second, sucrose cycling is a minor investment in overall leaf energy metabolism but a significant investment in cytosolic energy metabolism. Third, leaf energy balancing strictly requires oxidative phosphorylation, cofactor export from chloroplasts, and peroxisomal NADH import. Fourth, mitochondria are energetically self-sufficient. Fifth, carbon metabolism has an ATP/NADPH demand ratio of 1.52 which is met if ≤ 21.7% of whole electron flux is cyclic. Sixth, electron transport has a photon use efficiency of ≥ 62%. Last, we discuss interactions between the OPPP and the cytosolic oxidation–reduction cycle in supplying leaf cytosolic NADPH.