Observed Performance Enhancement Research Articles

Quantum anomaly detection in the latent space of proton collision events at the LHC

The ongoing quest to discover new phenomena at the LHC necessitates the continuous development of algorithms and technologies. Established approaches like machine learning, along with emerging technologies such as quantum computing show promise in the enhancement of experimental capabilities. In this work, we propose a strategy for anomaly detection tasks at the LHC based on unsupervised quantum machine learning, and demonstrate its effectiveness in identifying new phenomena. The designed quantum models-an unsupervised kernel machine and two clustering algorithms-are trained to detect new-physics events using a latent representation of LHC data, generated by an autoencoder designed to accommodate current quantum hardware limitations on problem size. For kernel-based anomaly detection, we implement an instance of the model on a quantum computer, and we identify a regime where it significantly outperforms its classical counterparts. We show that the observed performance enhancement is related to the quantum resources utilised by the model.

High-Detectivity All-Polymer Photodiode Empowers Smart Vitality Surveillance and Computational Imaging Rivaling Silicon Diodes.

Near-infrared (NIR) organic photodetectors (OPDs), particularly all-polymer-based ones, hold substantial commercial promise in the healthcare and imaging sectors. However, the process of optimizing their active layer composition to achieve highly competitive figures of merit lacks a clear direction and methodology. In this work, celebrity polymer acceptor PY-IT into a more NIR absorbing host system PBDB-T:PZF-V, to significantly enhance the photodetection competence, is introduced. The refined all-polymer ternary broadband photodetector demonstrates superior performance metrics, including experimentally measured noise current as low as 6 fA Hz-1/2, specific detectivity reaching 8×1012 Jones, linear dynamic range (LDR) of 145 dB, and swift response speed surpassing 200 kHz, striking a fair balance between sensitivity and response speed. Comprehensive morphological and photophysical characterizations elucidate the mechanisms behind the observed performance enhancements in this study, which include reduced trap density, enhanced charge transport, diminished charge recombination, and balanced electron/hole mobilities. Moreover, the practical deployment potential of the proof-of-concept device in self-powered mode is demonstrated through their application in a machine learning-based cuffless blood pressure (BP) estimation system and in high-resolution computational imaging across complex environments, where they are found to quantitatively rival commercial silicon diodes.

Microfluidics-on-a-chip for designing celecoxib-based amorphous solid dispersions: when the process shapes the product

AbstractThe fundamental idea underlying the use of amorphous solid dispersions (ASDs) is to make the most of the solubility advantage of the amorphous form of a drug. However, the drug stability becomes compromised due to the higher free energy and disorder of molecular packing in the amorphous phase, leading to crystallization. Polymers are used as a matrix to form a stable homogeneous amorphous system to overcome the stability concern. The present work aims to design ASD-based formulations under the umbrella of quality by design principles for improving oral drug bioavailability, using celecoxib (CXB) as a model drug. ASDs were prepared from selected polymers and tested both individually and in combinations, using various manufacturing techniques: high-shear homogenization, high-pressure homogenization, microfluidics-on-a-chip, and spray drying. The resulting dispersions were further optimized, resorting to a 32 full-factorial design, considering the drug:polymers ratio and the total solid content as variables. The formulated products were evaluated regarding analytical centrifugation and the influence of the different polymers on the intrinsic dissolution rate of the CXB-ASDs. Microfluidics-on-a-chip led to the amorphous status of the formulation. The in vitro evaluation demonstrated a remarkable 26-fold enhancement in the intrinsic dissolution rate, and the translation of this formulation into tablets as the final dosage form is consistent with the observed performance enhancement. These findings are supported by ex vivo assays, which exhibited a two-fold increase in permeability compared to pure CXB. This study tackles the bioavailability hurdles encountered with diverse active compounds, offering insights into the development of more effective drug delivery platforms. Graphical Abstract

Slurry and liquid impingement erosion behavior of low-temperature plasma carburized AISI 420 martensitic stainless steel

The impact of plasma carburizing treatment on the erosion wear resistance of AISI 420 martensitic stainless steel (MSS) was studied. Experiments were carried out varying a broad spectrum of erosion parameters, including impact velocity, impact angle, and exposure duration. Both slurry and liquid impingement erosion were employed in the experiments, with testing conducted using both distilled water and saline solutions to assess the combined effects of corrosion and erosion wear. Compared to untreated samples, a significant improvement in the erosion wear resistance of AISI 420 MSS due to low-temperature plasma carburizing treatment was observed for all tested conditions. The observed performance enhancement can be attributed to the formation of the carburized layer, constituted of the α'C and Fe3C phases. Results also highlighted that the severity of the tribosystem was significantly influenced by the test solution characteristics. A marginal increase in severity was observed upon introducing the saline solution, while a more substantial severity increase occurred with the addition of solid particles in the test fluid. The specimens' mass loss was increased by increasing impact velocity, following a simple potential relationship, and with impact angle, following a first-degree linear equation. In the case of the exposure time, the mass loss curves depended on the test environment. For solutions containing quartz particles, an additional final stabilization stage was observed in addition to the acceleration stage observed in the absence of abrasive component. This phenomenon was attributed to surface work hardening induced by the impact of solid particles. Regarding wear mechanisms, samples tested only with distilled water displayed erosion flow marks. Those containing distilled water and NaCl exhibited not only flow marks but also pits. Lastly, solutions containing solid particles additionally presented features of plastic deformation, lip formation, craters, indentations, and extruded material.

Effect of coherent edge-localized mode on transition to high-performance hybrid scenarios in KSTAR

This paper deals with one of the origins and trigger mechanisms responsible for the observed performance enhancements in the hybrid scenario experiments conducted in Korea Superconducting Tokamak Advanced Research (KSTAR). The major contribution to the performance improvement comes from a broader and higher pedestal formation. The increase of fast ion pressure due to a plasma density decrease also contributes substantially to the global beta. Although the reduced core plasma volume resulting from the pedestal expansion has a negative effect on the core thermal energy, a considerable confinement improvement observed in the inner core region limits the degradation. The one significant characteristic of high-performance discharges is the presence of Coherent Edge-localized Mode (CEM) activity. CEM is triggered during the pedestal recovery phase between typical ELM crashes and has been found to be related to the increase of particle and heat transport. It appears to underlie two commonly observed phenomena in high-performance hybrid scenario discharges in KSTAR; pedestal broadening and continuous density decrease. Despite the associated transport increase, CEM activities can induce performance enhancement. With the pedestal broadening, ELM crashes become delayed and weakened, which, in turn, allows for a higher pedestal. Moreover, the density decrease directly increases fast ion pressure by extending the beam-slowing-down time. The linear gyrokinetic analysis reveals that the increase of fast ions could initiate positive feedback loops, leading to the stabilization of Ion Temperature Gradient mode in the inner core region.

Effectiveness of Creatine in Metabolic Performance: A Systematic Review and Meta-Analysis.

Using the guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), this meta-analysis (MA) tried to figure out how well creatine (Cr) improves metabolic performance. We searched Google Scholar, PubMed, and the Cochrane Library to identify relevant randomized clinical trials (RCTs) exploring the various effects of Cr across different age groups compared to a placebo (PLA). We also investigated the synergistic effects of combining other supplements with Cr. In order to emphasize the different ways and sports where Cr has been used in the past years, we found from the selected articles that Cr demonstrated a more pronounced effect during aerobic or anaerobic exercise compared to PLA groups in the studies. Furthermore, in sports that demand significant cumulative energy, such as long-distance races, biking, or triathlons, athletes have observed performance enhancements with Cr supplementation. We also stipulate that Cr enhances resistance training in people over 50 years old and that adding other training supplements, such as β-hydroxy β-methylbutyrate (HMB), synergistically improves training outcomes when combined with Cr. The current MA was based on a thorough analysis of 10 separate studies. When these results were added together, we found that taking Cr supplements demonstrated statistically significant benefits over PLA. In conclusion, the present MA has found evidence that Cr has positive effects on metabolic outcomes for people who consume it.

Carbon nanotube sheet as a current collector for low-temperature solid oxide fuel cells

The utilization of Carbon Nanotube (CNT) sheets as current collectors for Solid Oxide Fuel Cells (SOFCs) was investigated in this study. A direct spinning method was employed for the synthesis of the 15 μm thick CNT sheet, which demonstrated high efficiency and cost-effectiveness. The material properties of the CNT sheet were characterized as a cathodic current collector and were subsequently integrated into 500 μm thick yttria-stabilized zirconia pellet-based SOFCs. The electrochemical performance of the SOFCs was evaluated at a temperature of 500 °C, resulting in a significant increase of 34.7% compared to the traditional SOFCs employing Pt mesh current collectors. Electrochemical Impedance Spectroscopy (EIS) analysis was performed to demonstrate that the observed performance enhancement was attributed to a reduction in both ohmic and charge transfer resistance. This highlights the potential of CNT sheet current collectors in not only decreasing ohmic resistance but also facilitating the reaction kinetics in solid oxide cells.

Developing a machine learning based building energy consumption prediction approach using limited data: Boruta feature selection and empirical mode decomposition

Artificial Intelligence methods (AI) have been widely applied in building energy consumption prediction. As data-intensive methods, lacking sufficient input features will significantly impede prediction performance. For some buildings where the building energy management systems (BEMs) are underperformed, limited information can be extracted. In this study, a feature engineering framework that combines feature construction and selection was developed to deal with limited feature problems. Empirical mode decomposition and Boruta feature selection were applied with the purpose of generating new informative features and selecting all relevant features, respectively. The proposed strategy was then tested using some popular machine learning algorithms for three different buildings. The results indicated that the proposed strategy was able to extend the feature dimensions and determine all relevant features from the extended feature space, which resulted to a significant improvement in the prediction performance. Unlike most other existing studies whereby observed performance enhancements may be marginal and restricted to few of the tested algorithms, the features selected here consistently improved the outcomes of all the machine learning algorithms tested for all 3 buildings.

Microwave and furnace annealing in oxygen ambient for performance enhancement of p-type SnO thin-film transistors

In this study, we investigated the effect of microwave-irradiation annealing (MWA) and thermal furnace annealing (FA) in oxygen ambient on the active channel layer of p-type tin-oxide (SnO) thin-film transistors. At very low source-drain voltage of −0.1 V, the MWA at 1200 W and FA at 300 °C samples have exhibited significant improvement in the electrical characteristics such as subthreshold swing (SS) of 0.93 and 0.485 V dec−1, the I on/I off ratio of 1.65 × 104 and 3.07 × 104, the field-effect mobility (μ FE) of 0.16 and 0.26 cm2 V−1 s and ultra-low off-state current of 1.9 and 2.0 pA respectively. The observed performance enhancement was mainly attributed to the reduction of interface trap density (N t) by tuning the power of MWA and optimizing the temperature in FA. From the result, we observed the optical band gap (E g) increased by 6% in FA, and 12% in MWA, which confirms improved crystallinity and reduction of defect states. Additionally, a low thermal budget microwave anneal process has shown high transmittance of more than 86% in the visible region (380–700 nm). The physical characterization indicates the partial phase transformation of SnO to SnO2 with retaining p-type conductivity in both annealing processes. The results demonstrate that both the annealing process could be highly promising to be used in the complementary logic circuits of new generation flexible/transparent displays.

A novel biodegradable flowerpot prepared by fermented straw fiber and urea‐formaldehyde adhesive modified with keratin from waste feathers

ABSTRACTThe recycling and utilization of feather waste from animal husbandry and straw from agriculture is a worldwide problem. In this study, keratin was extracted from waste feathers and used to modify urea‐formaldehyde (UF) adhesive to obtain biodegradable adhesive for making straw flowerpots with high performance. The results showed that keratin could reduce free formaldehyde and improve the thermal stability of UF. Furthermore, the mechanical properties of the flowerpot with keratin were greatly improved. The observed performance enhancements were attributed to the excellent adhesiveness of the bonding interface. In addition, the addition of keratin makes the flowerpot more hydrophilic and provides a better source of nutrients for microbes to grow and reproduce on the surface of the flowerpot, which is more conducive to the biodegradation of flowerpots after they are discarded. Our experiment suggests the great potential in terms of profitability and environmental protection by flowerpots prepared by fermented straw fiber and keratin‐modified UF.

Ultrathin sputtered platinum–gadolinium doped ceria cathodic interlayer for enhanced performance of low temperature solid oxide fuel cells

Improvement of the sluggish oxygen reduction reaction (ORR) is the key to lower the operating temperature of conventional solid oxide fuel cells (SOFCs). Developing a novel nanostructure in the cathodic catalyst layer is one of the efficient ways to reduce the operating temperature while improving fuel cell performance. In this paper, all components of low-temperature SOFCs were prepared on a nanoporous substrate by the sputtering method. For the performance enhancement at low temperature, an ultrathin Pt-Gadolinium Doped Ceria (GDC) cermet interlayer was deposited on the cathode side of electrolyte and demonstrated. A significant improvement in electrochemical performance was observed in the Pt-GDC interlayer fuel cell compared to a reference cell. The peak power density of Pt-GDC cathodic cermet interlayer cell was 334 mW/cm2 at 500 °C, which was 42.7% higher than that of the reference cell. Through additional analysis, we confirmed that the observed performance enhancement was attributed to the ultrathin cathodic cermet interlayer, which increases the triple phase boundary and enhances the reaction kinetics for ORR.

Constructing a Spectral Down Converter to Enhance Cu(In,Ga)Se2 Solar Cell Performance Using Yttrium Aluminum Garnet:Ce3+ Ceramics

Spectral conversion has been widely applied in the field of luminescence and is potentially beneficial for photovoltaic solar cells. However, more was said than done for the down‐conversion effect in the past, and quite a number of existing reports overclaimed the observed performance enhancement from down conversion either by wrongly identifying the contributions or by unfairly comparing with an inappropriate reference. Herein, Ce‐doped Y3Al5O12 ceramics with suitable absorption and photoluminescence properties are chosen as the down‐conversion material for Cu(In,Ga)Se2 (CIGS) solar cells. By properly designing optical structures to integrate the down‐conversion material with the CIGS solar cell, the fluorescent photons are efficiently guided to the CIGS absorber layer in addition to eliminating the scattering and maintaining the antireflection (AR) for incident light. The Y3Al5O12:Ce3+ ceramic down converter on CIGS solar cells can bring an enhancement of 0.53 mA cm−2 to the short‐circuit current density solely from down conversion, which is responsible for the major increase in conversion efficiency from 18.5% to 19.0%. A positive down‐conversion effect is demonstrated over AR layer‐coated CIGS solar cells without misclaiming contributions from other accompanied effects or jeopardizing any other accompanying effects.

Oxygen Reduction Reaction on Polycrystalline Platinum: On the Activity Enhancing Effect of Polyvinylidene Difluoride

There have been several reports concerning the performance improving properties of additives, such as polyvinylidene difluoride (PVDF), to the membrane or electrocatalyst layer of proton exchange membrane fuel cells (PEMFC). However, it is not clear if the observed performance enhancement is due to kinetic, mass transport, or anion blocking effects of the PVDF. In a previous investigation using a thin-film rotating disk electrode (RDE) approach (of decreased complexity as compared to membrane electrode assembly (MEA) tests), a performance increase for the oxygen reduction reaction (ORR) could be confirmed. However, even in RDE measurements, reactant mass transport in the catalyst layer cannot be neglected. Therefore, in the present study, the influence of PVDF is re-examined by coating polycrystalline bulk Pt electrodes by PVDF and measuring ORR activity. The results on polycrystalline bulk Pt indicate that the effects of PVDF on the reaction kinetics and anion adsorption are limited, and that the observed performance increase on high surface area Pt/C most likely is due to an erroneous estimation of the electrochemical active surface area (ECSA) from CO stripping and Hupd.

Phase and Morphology Evolution Induced Lithium Storage Capacity Enhancement of Porous CoO Nanowires Intertwined with Reduced Graphene Oxide Nanosheets

AbstractA simple and cost‐effective process is developed for the synthesis of a high‐performance anode consisting of porous CoO nanowires intertwined with reduced graphene oxide sheets (CoO−NWs/rGO). When tested in a lithium‐ion battery, the CoO−NWs/rGO exhibits high initial reversible capacity (∼960 mAh g−1) and excellent rate capability. More importantly, its performance is further enhanced when CoO−NWs/rGO is discharged/charged for >100 cycles. For example, the specific capacity of the CoO−NWs/rGO can reach up to 1195 mAh g−1 after ∼130 cycles. This enhancement of the electrochemical performance of the CoO−NWs/rGO is attributed to two effects during the repeated discharge/charge cycling: a gradual evolution in morphology and crystal structure of electrode materials and the transformation of CoO onto the surface of rGO sheets. While the initial porous structure and the wire‐shaped morphology of CoO NWs may help to alleviate the strains/stresses induced by the volume change associated with cycling, they do not seem to be the primary attributes to the observed performance enhancement. The implication of this finding is very important to the rational design of high‐performance electrode materials: the equilibrium structure and morphology of electrode materials under repeated cycling conditions are far more important than the initial structure and morphology in designing nanostructured electrodes with desired performance and durability.

Intra-auditory integration between pitch and loudness in humans: Evidence of super-optimal integration at moderate uncertainty in auditory signals

When a person plays a musical instrument, sound is produced and the integrated frequency and intensity produced are perceived aurally. The central nervous system (CNS) receives defective afferent signals from auditory systems and delivers imperfect efferent signals to the motor system due to the noise in both systems. However, it is still little known about auditory-motor interactions for successful performance. Here, we investigated auditory-motor interactions as multi-sensory input and multi-motor output system. Subjects performed a constant force production task using four fingers in three different auditory feedback conditions, where either the frequency (F), intensity (I), or both frequency and intensity (FI) of an auditory tone changed with sum of finger forces. Four levels of uncertainty (high, moderate-high, moderate-low, and low) were conditioned by manipulating the feedback gain of the produced force. We observed performance enhancement under the FI condition compared to either F or I alone at moderate-high uncertainty. Interestingly, the performance enhancement was greater than the prediction of the Bayesian model, suggesting super-optimality. We also observed deteriorated synergistic multi-finger interactions as the level of uncertainty increased, suggesting that the CNS responded to increased uncertainty by changing control strategy of multi-finger actions.

Source materials grain size effect on electrode microstructure and its effect on conventional bulk hetero-junction photovoltaics

In this work, the effect of silver cathode on the polymer diode and organic photovoltaic device (OPV) performance was investigated. The electron collecting contacts in diode and OPV device have been deposited from both silver pellet and nanoparticles form. Diode was fabricated by sandwiching poly(3-hexylthiophane-2,5-diyl) between ITO and Ag electrodes. It is observed that diode fabricated using Ag nanoparticles showed significant current density improvement. The enhancement in diode performance was studied by C-V measurements. Further, OPV cells fabricated using Ag nanoparticles showed improvement in current density which results in improved power conversion efficiency (PCE). The observed performance enhancements in diode and OPV device have been correlated with electrode microstructure and its interface properties. The performance enhancement in diode and OPV cells is evaluated by various electrical parameters such carrier concentration (N), density of trap states, trap distribution width (ω) and current density. These data indicate that the electrode grain size matching with the semiconductor morphology across metal/semiconductor interface is more critical for better charge transfer. Matching the roughness of the interface across the junction by use of appropriate starting material particle/grain size can help in extracting the maximum performance of an organic device.

A self-standing macroporous Au/ZnO/reduced graphene oxide foam for recyclable photocatalysis and photocurrent generation

A self-standing three-dimensional (3D) nanocomposite foam of Au/ZnO/reduced graphene oxide (rGO) has been fabricated via a facile and convenient template-directed approach. This is the first report of self-standing ternary macroporous foam consisting of noble metal, ZnO and rGO, which can be directly used in photocatalytic degradation and photocurrent generation, free of any inactive binders or substrates. The resultant 3D Au/ZnO/rGO foam exhibits superior photocatalytic activity than binary ZnO/rGO foam and flat Au/ZnO/rGO film, demonstrating 94% Rhodamine B degradation within 180minutes under 200–780nm irradiation and good cycling stability after 5 photodegradation cycles. Moreover, the Au/ZnO/rGO foam expresses a swift and steady photocurrent of 0.055mAcm−2, which is 3 and 24 times higher than those photocurrent generated by ZnO/rGO foam without Au nanoparticle (AuNP) decoration and flat Au/ZnO/rGO film electrode respectively. The observed performance enhancement is likely contributed by the hierarchical macroporous structure of conductive Au/ZnO/rGO foam, which can not only improve the light utilization, but also facilitate electron transport by promoting the photo-induced charge separation. Furthermore, the AuNPs loaded on ZnO can function as an electron sink to enhance photocurrent generation and photocatalytic property. The simple approach presented here holds great promise for the application in both environmental purification and photoelectric conversion.

Perceptual precision of passive body tilt is consistent with statistically optimal cue integration

When making perceptual decisions, humans have been shown to optimally integrate independent noisy multisensory information, matching maximum-likelihood (ML) limits. Such ML estimators provide a theoretic limit to perceptual precision (i.e., minimal thresholds). However, how the brain combines two interacting (i.e., not independent) sensory cues remains an open question. To study the precision achieved when combining interacting sensory signals, we measured perceptual roll tilt and roll rotation thresholds between 0 and 5 Hz in six normal human subjects. Primary results show that roll tilt thresholds between 0.2 and 0.5 Hz were significantly lower than predicted by a ML estimator that includes only vestibular contributions that do not interact. In this paper, we show how other cues (e.g., somatosensation) and an internal representation of sensory and body dynamics might independently contribute to the observed performance enhancement. In short, a Kalman filter was combined with an ML estimator to match human performance, whereas the potential contribution of nonvestibular cues was assessed using published bilateral loss patient data. Our results show that a Kalman filter model including previously proven canal-otolith interactions alone (without nonvestibular cues) can explain the observed performance enhancements as can a model that includes nonvestibular contributions.NEW & NOTEWORTHY We found that human whole body self-motion direction-recognition thresholds measured during dynamic roll tilts were significantly lower than those predicted by a conventional maximum-likelihood weighting of the roll angular velocity and quasistatic roll tilt cues. Here, we show that two models can each match this "apparent" better-than-optimal performance: 1) inclusion of a somatosensory contribution and 2) inclusion of a dynamic sensory interaction between canal and otolith cues via a Kalman filter model.

Performance enhancement of blue light-emitting diodes with InGaN/GaN multi-quantum wells grown on Si substrates by inserting thin AlGaN interlayers

We have grown blue light-emitting diodes (LEDs) having InGaN/GaN multi-quantum wells (MQWs) with thin AlyGa1−yN (0 < y < 0.3) interlayers on Si(111) substrates. It was found by high-resolution transmission electron microscopy observations and three-dimensional atom probe analysis that 1-nm-thick interlayers with an AlN mole fraction of less than y = 0.3 were continuously formed between GaN barriers and InGaN wells, and that the AlN mole fraction up to y = 0.15 could be consistently controlled. The external quantum efficiency of the blue LED was enhanced in the low-current-density region (≤45 A/cm2) but reduced in the high-current-density region by the insertion of the thin Al0.15Ga0.85N interlayers in the MQWs. We also found that reductions in both forward voltage and wavelength shift with current were achieved by inserting the interlayers even though the inserted AlGaN layers had potential higher than that of the GaN barriers. The obtained peak wall-plug efficiency was 83% at room temperature. We suggest that the enhanced electroluminescence (EL) performance was caused by the introduction of polarization-induced hole carriers in the InGaN wells on the side adjacent to the thin AlGaN/InGaN interface and efficient electron carrier transport through multiple wells. This model is supported by temperature-dependent EL properties and band-diagram simulations. We also found that inserting the interlayers brought about a reduction in the Shockley-Read-Hall nonradiative recombination component, corresponding to the shrinkage of V-defects. This is another conceivable reason for the observed performance enhancement.

An exploratory study of multimodal interaction modeling based on neural computation

Multimodal interaction serves an important role in human-computer interaction. In this paper we propose a multimodal interaction model based on the latest cognitive research findings. The proposed model combines two proven neural computations, and helps to reveal the enhancement or depression influence of multimodal presentation upon the corresponding interaction task performance. A set of experiments is designed and conducted within the constraints of the model, which demonstrates the observed performance enhancement and depression effects. Our exploration and the experimental results help to further solve the question about how tactile feedback signal contribute the multimodal interaction efficiency which could provide guidelines for designing the tactile feedback in multimodal interaction.