Positive Effect Research Articles

Improving Daily Precipitation Estimates by Merging Satellite and Reanalysis Data in Northeast China

Precipitation plays a key control in the water, energy, and carbon cycles, and it is also an important driving force for land surface modeling. This study provides an optimal least squares merging approach to merge precipitation data sets from multiple sources for an accurate daily precipitation estimate in Northeast China (NEC). Precipitation estimates from satellite-based IMERG and SM2RAIN-ASCAT, as well as reanalysis data from MERRA-2, were used in this study. The triple collocation (TC) approach was used to quantify the error uncertainties in each input data set, which are associated with the weights assigned to each data set in the merging procedure. The results revealed that IMERG provides a better consistency with the other two input data sets and thus was more relied on during the merging process. The accuracy of both SM2RAIN-ASCAT and MERRA-2 showed obvious spatio-temporal patterns due to their retrieval algorithms and resolution limits. The merged TC-based daily precipitation provides the highest correlation coefficient with ground-based measurements (R = 0.52), suggesting its capability to represent the temporal variation in daily precipitation. However, it largely overestimated the precipitation intensity in the summer, leading to a large positive bias.

Effect of Hemolysis on Routine Blood Gas and Whole Blood Analytes.

Hemolysis is a major pre-analytical concern for many laboratory analytes; however, instruments utilized for whole blood chemistries and blood gas measurements lack the ability to detect and measure the degree of hemolysis. This study evaluated the effect of hemolysis on 13 routine whole blood and blood gas analytes and compared visual assessments of hemolysis to measured hemolysis (H-index). Remnant whole blood samples (n = 85) were split into 2 portions and aspirated through a syringe one or more times. To induce hemolysis, a needle was affixed to the end of the syringe to provide shear stress, and a mock procedure without syringe was used as a control. Samples were analyzed on a Radiometer ABL800 series instrument, centrifuged, and the H-index of the plasma portion was measured. Two medical technologists recorded a visual categorization of the specimens as slightly, moderately, or severely hemolyzed. Hemolysis had a modest effect on metabolites and most cooximetry components, with percent bias within ±5% at all levels of hemolysis. Methemoglobin exhibited a larger overall negative bias, up to 13.3%. The absolute pH bias was fairly consistent (within 0.1 pH units) across all levels of hemolysis. As expected, potassium displayed a significant positive bias with increasing hemolysis. Sodium and ionized calcium displayed overall linear trends with a significant negative bias. Hemolysis can falsely increase or decrease certain blood gas analytes and lead to misinterpretation of results. Therefore, hemolysis detection capabilities are crucial for mitigating this effect and ensuring accurate results for patient care.

Depression and emotion regulation strategy use moderate age-related attentional positivity bias

Effective emotion regulation is critical for maintaining emotional health in the face of adverse events that accumulate over the lifespan. These abilities are thought to be generally maintained in older adults, accompanied by the emergence of attentional biases to positive information. Such age-related positivity biases, however, are not always reported and may be moderated by individual differences in affective vulnerabilities and competencies, such as those related to dispositional negative affect and emotion regulation styles. To examine these relationships, we analyzed eye-tracking data from 72 participants (35–74 years; 50 female), 44 without and 28 with a diagnosis of Major Depressive Disorder during a free-viewing task comprising neutral-neutral, negative-neutral, and positive-neutral image pairs. Emotional bias scores were calculated based on the ratio of time spent dwelling on the emotional image vs. the neutral image in each emotional-neutral pair. Results indicate that healthy participants exhibited a stronger positivity bias than a negativity bias, whereas individuals with higher depressive symptom scores showed no difference. Next, we examined how age and emotion regulation strategy use (reappraisal vs. suppression, measured with the Emotion Regulation Questionnaire) impacted these effects. Individuals with Major Depressive Disorder did not exhibit a significant relationship between age and positivity bias. However, for healthy participants who self-reported a preference for using reappraisal in daily life, increased age was associated with an increased positivity bias. These findings indicate that the emergence of the positivity effect in older adults is related to reappraisal regulatory preferences in the absence of depressive symptoms.

Mobility and stability improvements through in-situ AlOx passivation on extremely thin 2-nm-thick InOx back-gate FETs

Abstract The effectiveness of in-situ AlOx passivation on mobility and stability improvement in 2-nm-thick InOx FETs is comprehensively investigated at atomic layer deposition (ALD) temperature ranging from 100oC to 200oC. The chemical state of extremely thin InOx channels are significantly changed by the in-situ AlOx passivation. As a result, AlOx/InOx FETs show superior overdrive current and hysteresis characteristic than those of InOx FETs fabricated at the same ALD temperature. It is also found that a AlOx passivation layer formed at 200oC results in a stronger reduction of InOx, leading to a mobility enhancement of 1.8 against AlOx/InOx FET fabricated at 100oC thanks to an increase of oxygen vacancies and resultant enhanced hopping conduction. For bias stability analysis, amount of hydrogen-induced trapping site within both AlOx and InOx layer is reduced at a higher ALD temperature, resulting in the improvement of both positive and negative bias stress stability.

Evaluating and Improving Snow in the National Water Model, using Observations from the New York State Mesonet

Abstract This study leverages observations from the New York State Mesonet to evaluate and improve the representation of snow within the National Water Model (NWM) and its associated land surface model (Noah-MP). To do so, we run and analyze distributed NWM simulations, forced by gridded meteorological analyses, and Noah-MP point simulations, forced by NYSM observations. Distributed NWM runs, with a baseline configuration, show substantial SWE biases caused by biases in the meteorological forcing used, imperfect representation of snow processes, and mismatches between the land cover in the model and at NYSM station locations. Noah-MP point simulations, using the baseline configuration, reveal a systematic positive bias in SWE accumulation. Sensitivity experiments show that this bias can be mitigated by using an alternative precipitation phase partitioning method. Noah-MP point simulations, with improved precipitation phase partitioning, reveal a systematic negative bias in SWE ablation rates. Sensitivity experiments highlight uncertain parameters within Noah-MP that strongly affect ablation rates and show particularly large sensitivity to the TAU0 parameter, which modulates snow albedo decay rates. Reducing TAU0 improves ablation rates by reducing biases in surface albedo. Distributed NWM experiments, with precipitation phase partitioning and TAU0 adjusted based in Noah-MP point simulation results, show qualitatively similar sensitivities. However, the distributed experiments do not show clear improvements when compared to SWE and streamflow observations. This is likely due to some combination of the above-mentioned sources of bias in the baseline distributed run and (for streamflow) biases in other parameterized processes unrelated to snow in the NWM.

CHANGES IN THE ELEMENTAL COMPOSITION OF THE CHYME AND METABOLIC PROCESSES IN THE RUMEN WHEN EXOGENOUS ENZYMES ARE USED IN FEEDING BULLS

Introduction. Coordination of the processes of scar digestion and metabolism in ruminants is a prerequisite for achieving high efficiency in the use of feed nutrients, improving product quality and profitability of production. The purpose of this study was to evaluate whether the inclusion of the exogenous lipase enzyme in the diet of bullocks in feedlots has a positive ef-fect on physiology, fermentation in the rumen, digestibility and the profile of fatty acids in the rumen. Material and methods. In the experiment, 8 animals were used, divided into 2 groups. the bulls of the control group received the basic diet (RR), the experimental group also received RR with the inclusion of the lipase enzyme at a dosage of 25 g / head / day. The level of volatile fatty acids (VFA) in the contents of the scar was determined by gas chromatography on a gas chromatograph "Crystallux-4000M", determination of nitrogen forms accord-ing to GOST 26180-84. The elemental composition of biosubstrates was studied using atomic emission and mass spectrometry (NPP-ISP and MS-ISP) in the IC of the Central Research Center of the FNC BST RAS. Results. The study of the ratio of LVH in the scar fluid showed that in the experimental group of animals the content of acetic acids decreased by 18.35%, propionic acid – 15.29%, butyric acid – 34.28%, valerian acid – 11.11%, while caproic acid was not found in the experimental group. Nitrogen metabolism in the body showed that the level of total nitrogen in the scar fluid increased by 64.71%, non–protein 53.66%, protein 66.22%, ammonia 78.57% (p 0.05), respectively. Analysis of the biomass of bacteria and protozoa showed that during the experiment, these indicators were higher in the experimental group of animals by 17.07% and 22.22%, respectively, compared with the control. The trace element composition of the scar fluid revealed differences in the mechanism of action of the lipase enzyme on the metabolism of chemicals. There was an increase in the concentration of chemical elements in the experimental group of bulls Ca – by 11.51%, P –17.72%, K – 20.34% (p≤0.05), Fe – 21.31%, Zn – 10.14%, Cu – 23.53%, Se – 39.13%. Against the background of a decrease in Ni – 11.44%, Ba – 14.67%, B – 9.00%, I – 33.33%, Al – 15.71 and Sr – 15.85% (p 0.05). Conclusion. Thus, the study of microbial communities of the LJ rumen, primarily of cattle, is very relevant due to the possibility of rapid diagnosis and prevention of many pathologies of the digestive system associated with improper feeding, which, as a rule, is accompanied by the development of pathogenic and opportunistic microorganisms.

How Listening Versus Reading Alters Consumers’ Interpretations of News

This research investigates how listening to versus reading news alters its interpretation. A proposed theory argues that because listeners (vs. readers) are less able to regulate the rate of incoming information, they selectively attend to the more emotionally arousing elements in a story, such as those that are more negative. This selective attention leads listeners to form different interpretations of news than readers, the nature of which depend on the valence of the story. Six main experiments and three supplemental ones (N = 14,744) support the predicted effects on impression formation as well as the proposed mechanism. For example, participants who listened to (vs. read) a mixed-valence news story on the risks and benefits of a product processed its negative details more selectively, and in turn formed more pessimistic impressions of its safety. Moderators are also explored, showing that negativity biases similar to those observed for listeners arose among readers when their control over information flow was restricted, and that a positivity bias arose among listeners when the positive (vs. negative) information in a story was more surprising. Theoretical contributions to previous research on reading versus listening comprehension are discussed, as are the substantive implications for media firms and consumers.

Unveiling the Aluminum Doping Effects of In‐Situ Transmogrified Dual‐LDH Heterostructure and Its Fermi‐Level Alignment to Water Splitting Potentials

AbstractThe layered double hydroxide (LDH) captivates the starlight of electrochemical water‐splitting applications due to its stacked layers and larger surface area. A novel approach is reported to integrate CoFe‐LDH/NiAl‐LDH heterostructure through a single‐step in situ transmogrification, harnessing the benefits of LDH. The in situ Raman spectroscopy reveals that aluminum (Al) doping promotes the formation of high‐valent CoIII/IV‐O active species concentration in LDH, whereas without Al dopants, the catalyst predominantly exhibit NiII/III‐O species and underperform the catalytic activity. The projected density of states is very close to the Fermi level positions in Al‐doped samples which significantly enhance the electron transfer processes. The Mott–Schottky studies confirm that both Al40 CoFe30 and Al60 CoFe20 catalysts are p‐type semiconductors, exhibiting a distinct redox behaviors under applied bias. At positive bias, Al60 CoFe20 undergoes downward band bending (accumulation), and align the Fermi‐level near the water oxidation potential, which promotes the oxygen evolution reaction (OER). The negative bias causes upward band bending (deep depletion) in the Al40 CoFe30, and shifts the Fermi‐level near the water reduction potential, and hence facilitates hydrogen evolution reaction (HER). Overall, this study highlights the importance of manipulating Fermi‐level alignment in LDH catalysts through strategic metal doping to achieve targeted water‐splitting reactions.

Resting-state functional network segregation of the default mode network predicts valence bias across the lifespan

Abstract The brain is organized into intrinsically connected functional networks that can be reliably identified during resting-state functional magnetic resonance imaging (fMRI). Healthy aging is marked by decreased network segregation, which is linked to worse cognitive functioning, but aging-related changes in emotion are less well characterized. Valence bias, which represents the tendency to interpret emotionally ambiguous information as positive or negative, is more positive in older than younger adults and is associated with differences in task-based fMRI activation in the amygdala, prefrontal cortex, and a cingulo-opercular (CO) network. Here, we examined valence bias, age, and resting-state network segregation of 12 brain networks in a sample of 221 healthy individuals from 6 to 80 years old. Resting-state network segregation decreased linearly with increasing age, extending prior reports of de-differentiation across the lifespan. Critically, a more positive valence bias was related to lower segregation of the default mode network (DMN), due to stronger functional connectivity of the DMN with CO and, to a lesser extent, the ventral attention network (VAN) in all participants. In contrast to this overall segregation effect, in participants over 39 years old (who tend to show a positive valence bias), bias was also related to weaker connectivity between the DMN and Reward networks. The present findings indicate that specific interactions between the DMN, a task control network (CO), an emotion processing network (Reward), and, to a weaker extent, an attention network (VAN), support a more positive valence bias, perhaps through regulatory control of self-referential processing and reduced emotional reactivity in aging. The current work offers further insight into the functional brain network alterations that may contribute to affective well-being and dysfunction across the lifespan.

Charge lifetime improvement of the Continuous Electron Beam Accelerator Facility photogun with a biased anode

GaAs photocathodes in dc high-voltage photoguns are highly susceptible to ion back-bombardment, which reduces the photocathode quantum efficiency and limits the useful operating lifetime for producing polarized electron beams. This paper demonstrates that applying a small positive bias to the photogun anode can significantly suppress ion back-bombardment and increase charge lifetime. This technique was studied extensively using the Continuous Electron Beam Accelerator Facility photogun, where highly polarized electron beams created using a strained-superlattice GaAs/GaAsP photocathode were used and charge lifetimes improved by almost a factor of 2. A new simulation code was developed to model ion production and tracking in order to better understand and explain the factors that led to the performance improvement. Results of the experiments and simulations are discussed in detail. Published by the American Physical Society 2024

Influence of radio-frequency magnetron sputtering power on electrical characteristics and positive bias stress stability of indium tin zinc oxide thin-film transistors

Abstract As the pursuit of high-quality display panels intensifies, the importance of high-performance thin-film transistors (TFTs) becomes increasingly prominent. Indium tin zinc oxide (ITZO) TFTs, as one of the promising directions for high-performance metal oxide TFTs, impose high demands on their performance and reliability. In this study, the performance and stability of ITZO TFTs fabricated under different radio-frequency magnetron sputtering power conditions were systematically tested and investigated. After sputtering power optimization, the field effect mobility of ITZO TFTs reaches 29.68 cm²/V·s, with a steep sub-threshold swing of 0.17 V/decade, near-zero threshold voltage, and good stability. Using atomic force microscopy and X-ray photoelectron spectroscopy characterization techniques, the thin films were analyzed to elucidate the relationship between sputtering power variations and oxygen vacancies.

Using cluster‐based permutation tests to estimate MEG/EEG onsets: How bad is it?

AbstractLocalising effects in space, time and other dimensions is a fundamental goal of magneto‐ and electroencephalography (EEG) research. A popular exploratory approach applies mass‐univariate statistics followed by cluster‐sum inferences, an effective way to correct for multiple comparisons while preserving high statistical power by pooling together neighbouring effects. Yet, these cluster‐based methods have an important limitation: each cluster is associated with a unique p‐value, such that there is no error control at individual timepoints, and one must be cautious about interpreting when and where effects start and end. Sassenhagen and Draschkow (2019) provided an important reminder of this limitation. They also reported results from a simulation, suggesting that onsets estimated from EEG data are both positively biased and very variable. However, the simulation lacked comparisons to other methods. Here, I report such comparisons in a new simulation, replicating the positive bias of the cluster‐sum method, but also demonstrating that it performs relatively well, in terms of bias and variability, compared to other methods that provide pointwise p‐values: two methods that control the false discovery rate and two methods that control the familywise error rate (cluster‐depth and maximum statistic methods). I also present several strategies to reduce estimation bias, including group calibration, group comparison and using binary segmentation, a simple change point detection algorithm that outperformed mass‐univariate methods in simulations. Finally, I demonstrate how to generate onset hierarchical bootstrap confidence intervals that integrate variability over trials and participants, a substantial improvement over standard group approaches that ignore measurement uncertainty.

PLGA Nanoparticles as New Drug Delivery Systems in Leishmaniasis Chemotherapy: A Review of Current Practices.

Although leishmaniasis is one of the most common parasitic diseases, its traditional treatments suffer from some serious problems. To solve such issues, we can take advantage of the effective nanoparticle-based approaches to deliver anti-leishmanial agents into leishmania-infected macrophages either using passive targeting or using macrophagerelated receptors. Despite the high potential of nanotechnology, Liposomal Amphotericin B (AmBisome®) is the only FDA-approved nanoparticle-based anti-leishmanial therapy. In an effort to find more anti-leishmanial nano-drugs, this 2011-2021 review study aimed to investigate the in-vivo and in-vitro effectiveness of poly (lactic-co-glycolic acid) nanoparticles (PLGA-NPs) in the delivery of some traditional anti-leishmanial drugs. Based on the results, PLGA-NPs could improve solubility, controlled release, trapping efficacy, bioavailability, selectivity, and mucosal penetration of the drugs, while they decreased resistance, dose/duration of administration and organotoxicity of the agents. However, none of these nano-formulations have been able to enter clinical trials so far. We summarized the data about the common problems of anti-leishmanial agents and the positive effects of various PLGA nano-formulations on reducing these drawbacks under both in-vitro and in-vivo conditions in three separate tables. Overall, this study proposes two AmB-loaded PLGA with a 99% reduction in parasite load as promising nanoparticles for further studies.

Improving Xenon-129 lung ventilation image SNR with deep-learning based image reconstruction.

To evaluate the feasibility and utility of a deep learning (DL)-based reconstruction for improving the SNR of hyperpolarized 129Xe lung ventilation MRI. 129Xe lung ventilation MRI data acquired from patients with asthma and/or chronic obstructive pulmonary disease (COPD) were retrospectively reconstructed with a commercial DL reconstruction pipeline at five different denoising levels. Quantitative imaging metrics of lung ventilation including ventilation defect percentage (VDP) and ventilation heterogeneity index (VHI) were compared between each set of DL-reconstructed images and alternative denoising strategies including: filtering, total variation denoising and higher-order singular value decomposition. Structural similarity between the denoised and original images was assessed. In a prospective study, the feasibility of using SNR gains from DL reconstruction to allow natural-abundance xenon MRI was evaluated in healthy volunteers. 129Xe ventilation image SNR was improved with DL reconstruction when compared with conventionally reconstructed images. In patients with asthma and/or COPD, DL-reconstructed images exhibited a slight positive bias in ventilation defect percentage (1.3% at 75% denoising) and ventilation heterogeneity index (˜1.4) when compared with conventionally reconstructed images. Additionally, DL-reconstructed images preserved structural similarity more effectively than data denoised using alternative approaches. DL reconstruction greatly improved image SNR (greater than threefold), to a level that 129Xe ventilation imaging using natural-abundance xenon appears feasible. DL-based image reconstruction significantly improves 129Xe ventilation image SNR, preserves structural similarity, and leads to a minor bias in ventilation metrics that can be attributed to differences in the image sharpness. This tool should help facilitate cost-effective 129Xe ventilation imaging with natural-abundance xenon in the future.

Influence of river runoff and precipitation on the seasonal and interannual variability of sea surface salinity in the eastern North Tropical Atlantic

Abstract. In tropical regions, the freshwater flux entering the ocean originates primarily from precipitation and, to a lesser extent when considering basin-scale averages, from continental rivers. Nevertheless, at the regional scale, river flows can have a significant impact on the surface ocean dynamics. Riverine freshwater modifies salinity and, therefore, density, stratification, and circulation. With its particular coastline and high cumulative river discharge, as well as its being in the vicinity of the intertropical convergence zone (ITCZ), the eastern part of the North Tropical Atlantic (e-NTA) region off northwestern Africa is a particularly interesting location to study the linkage between precipitation, river outflow, and sea surface salinity (SSS). Here, we focus on the regional e-NTA SSS seasonal cycle and interannual variability and on the impact of using various river runoff and precipitation forcing data sets to simulate SSS with a regional model. The simulated SSS values are compared with the Climate Change Initiative (CCI) satellite SSS values; in situ SSS values from Argo floats, ships, and a coastal mooring; and the GLORYS reanalysis SSS values. An analysis of the mixed-layer salinity budget is then conducted. Overall, the simulations reproduce the seasonal cycle and interannual variability well despite a positive mean model bias north of 15° N. The seasonal cycle is impacted by the phasing of the different runoff products. The mixed-layer SSS decrease during the rainy season is mainly driven by precipitation followed by runoff by means of horizontal advection and is partly compensated for by vertical mixing. In terms of interannual anomalies, river runoff has a more direct impact on SSS than precipitation. This study highlights the importance of properly constraining river runoff and precipitation to simulate realistic SSS values and the importance of observing SSS in coastal regions to validate such constraints.

Harnessing 360-Degree Video to Prompt Users to Think Along With Pro-Environmental Campaign Messages

Three-hundred-and-sixty-degree videos visualized through virtual reality (VR) technologies are recognized as an effective tool for fostering positive attitudes towards environmental stewardship by immersing users in persuasive storytelling narratives. However, a lack of an overarching framework hinders the understanding of its role in promoting prosocial environmental behaviors, particularly its effects on information processing and behavioral intentions. Notably, recent studies have suggested that feeling transported into a VR environment (i.e., presence) could positively bias message evaluation and the way people process information by activating heuristics connected to immersive experiences (i.e., the bias hypothesis of the heuristic-systematic model). Drawing on this proposition, this study conducted a between-subject design experiment (<em>N</em> = 60), comparing a 360-degree pro-environmental campaign video in VR with that in a two-dimensional format. Results from partial least squares structural equation modeling indicated that a 360-degree video in VR induced a higher sense of presence, yet heuristic evaluation of message credibility decreased when a sense of presence was low. Moreover, message credibility was found to be positively associated with the valence (consistency) of message-relevant thoughts, but moderate evaluation of message credibility buffered the generation of consistent message-relevant thoughts. Finally, the valence (consistency) of message-relevant thoughts had a curvilinear relationship with the intention to engage in pro-environmental behaviors, albeit with a small effect size. Results suggest the complexity in influencing behavioral intentions via 360-degree videos in VR. Nonetheless, the findings support the proposition that the immersive affordance of immersive storytelling content could prompt users to align with campaign messages by activating a positive heuristic bias.

Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ

Abstract. United States (US) background ozone (O3) is the counterfactual O3 that would exist with zero US anthropogenic emissions. Estimates of US background O3 typically come from chemical transport models (CTMs), but different models vary in their estimates of both background and total O3. Here, a measurement–model data fusion approach is used to estimate CTM biases in US anthropogenic O3 and multiple US background O3 sources, including natural emissions, long-range international emissions, short-range international emissions from Canada and Mexico, and stratospheric O3. Spatially and temporally varying bias correction factors adjust each simulated O3 component so that the sum of the adjusted components evaluates better against observations compared to unadjusted estimates. The estimated correction factors suggest a seasonally consistent positive bias in US anthropogenic O3 in the eastern US, with the bias becoming higher with coarser model resolution and with higher simulated total O3, though the bias does not increase much with higher observed O3. Summer average US anthropogenic O3 in the eastern US was estimated to be biased high by 2, 7, and 11 ppb (11 %, 32 %, and 49 %) for one set of simulations at 12, 36, and 108 km resolutions and 1 and 6 ppb (10 % and 37 %) for another set of simulations at 12 and 108 km resolutions. Correlation among different US background O3 components can increase the uncertainty in the estimation of the source-specific adjustment factors. Despite this, results indicate a negative bias in modeled estimates of the impact of stratospheric O3 at the surface, with a western US spring average bias of −3.5 ppb (−25 %) estimated based on a stratospheric O3 tracer. This type of data fusion approach can be extended to include data from multiple models to leverage the strengths of different data sources while reducing uncertainty in the US background ozone estimates.

Ultra-tunable dielectric capacitors enhanced by coupling ferroelectric field effect and semiconductor field effect

Tunable ferroelectric film capacitors play an important role in tunable microwave devices and filter systems due to their high dielectric constant, low loss, and high dielectric tunability. However, there is a trade-off between low loss and high tunability, which limits further enhancement of dielectric performance. Here, we propose an ultra-tunable capacitor by designing a Ba0.7Sr0.3TiO3 (BST)–semiconductor heterostructure. In the tunable capacitor, the BST film is fabricated directly on p-type silicon substrates by magnetron sputtering, and a heterostructure layer is constructed. The coupling effects between the semiconductor depletion layer capacitance and the BST capacitance produce higher capacitance tunability than a traditional sandwich BST capacitor. Based on the coupling effects, a metal–ferroelectric–semiconductor–ferroelectric–metal capacitor is developed, which enables the capacitor to operate under both negative and positive biases, which has an n value (n=Cmax/Cmin) of 90 with 40 V bias voltage and a maximum Q of 1000. The results offer a potential approach to designing high-performance tunable capacitors on silicon with BST film that could build tunable filters for information processing in communication systems.

Internal Electric Field Manipulates Exciton-Phonon Couplings in Single Lead Halide Perovskite Nanocrystals.

Lead halide perovskite nanocrystals (NCs) have attracted much attention as materials for light-emitting diodes and quantum light sources. A deep understanding of exciton-phonon couplings is essential for obtaining a narrow emission line, weak phonon-sideband photoluminescence (PL), and a long exciton coherence time, which are especially useful for high-color-purity quantum-light-source applications. Here, we report the PL spectra of single CsPbBr3 NCs at 5.5 K as a function of the applied electric field. The exciton peak energy shows an asymmetric parabolic shift for positive and negative biases, implying the presence of a spontaneously generated internal electric field in the NCs when no field is applied. Both the internal electric field and exciton-phonon couplings become larger in smaller NCs, and they have a positive correlation with each other. Our findings show that the exciton-phonon couplings can be manipulated with an electric field, which dominates the PL properties of perovskite NCs.

Dual-functional GaN photodiode for photodetection and neuromorphic computing with high specific detectivity.

The discrepancy in the photoresponse characteristics between photodetectors (PDs) and photosynapses is posing a challenge for integrating the two functions into a single device. In this work, a photodetector integrated with neuromorphic capabilities is demonstrated. Under the joint action of the photovoltaic effect and photoconductive effect, the proposed device can switch between the photodetector and photosynapse by simply altering the polarity of bias voltage. Under a reverse or zero bias voltage, the device operates as a photodetector with low dark current and high specific detectivity. On the other hand, when a positive bias voltage is applied, the device showcases synaptic functionalities such as excitatory postsynaptic current, paired-pulse facilitation, and transition from short-term memory to long-term memory. The dual-functional devices hold promise for weak light detection and neuromorphic computing in complex environments.