Limited Efficiency Research Articles

A theoretical review of passivation technologies in perovskite solar cells

Perovskite solar cells have demonstrated remarkable progress in recent years. However, their widespread commercialization faces challenges arising from defects and environmental vulnerabilities, leading to limitations in energy conversion efficiency and device stability. To overcome these hurdles, passivation technologies have emerged as a promising avenue. These passivators are strategically applied at the interface between perovskite absorbers and charge transport layers to mitigate the adverse effects of defects and environmental factors. While prior reviews have predominantly focused on experimental observations, a comprehensive theoretical understanding of the passivators has been lacking. This review focuses on recent advancements in first-principles density functional theory studies that delve into the fundamental properties of passivators and their intricate interactions with perovskite materials and charge transport layers. By exploring the atomic-level roles of passivators, this review elucidates their impact on critical parameters such as open circuit voltage (Voc ), short circuit current density (Jsc ), fill factor, and the overall stability of perovskite solar cells. The synthesis of theoretical insights from these studies can serve as guidelines for the molecular design of passivators with the ultimate objective of advancing the commercialization of high-performance perovskite solar cells.

Ultra-efficient decontamination via functionalized reactive electrochemical membrane for peroxymonosulfate activation: High water flux with extremely low energy consumption

A perovskite LaCoO3 functionalized Ti4O7 reactive electrochemical membrane (REM) was developed for electro-enhanced peroxymonosulfate (PMS) activation (E-REM-PMS), addressing limitations in wastewater treatment efficiency, reusability, and interference resistance. It achieved 100% carbamazepine (CBZ) removal at a rate constant of 39.69 min−1, 233 and 23 times of electro-REM (E-REM) system without PMS and REM-PMS system without electricity. In-situ Fourier transform infrared spectroscopy (FTIR) highlighted the promotion of electro-activation on PMS, while density functional theory (DFT) calculations elucidated mechanism differences under three adsorption configurations. 1O2 (2.97×10−9 M), SO4•− (2.09×10−11 M) and •OH (7.36×10−12 M) dominated the E-REM-PMS system, consistent with sequence of reactive species by DFT results. Continuous treatment of pharmaceutical wastewater confirmed 100% CBZ removal and 60%-70% TOC mineralization at ultrahigh water flux (642.86 L/m2·h) with minimal energy consumption (0.01 kWh/m3·order). This work proposed a high-performance and anti-fouling REM, offering an efficient and economical solution for wastewater treatment.

Effects of sodium aluminate on fleeting semi-dry carbonation and properties of steel slag powders in low concentration CO2 atmosphere

Accelerated carbonation suffers from the limitation of low efficiency when CO2 supply is inadequate. This study aims at proposing a carbonation accelerator of sodium aluminate (SA) to stimulate the reaction between steel slag and CO2. Additionally, a fleeting semi-dry carbonation is proposed and mixed gas with 20 vol% CO2 was used to simulate the CO2 concentration of flue gas. According to the MGC results, with only 0.07 wt% of SA added, steel slag obtained 3.55 wt% of CO2 uptake after 10 min carbonation under 20 vol% CO2 atmosphere, which is 36.02 % higher than that of the carbonated control steel slag. As a result of elevated carbonation efficiency, f-CaO (free calcium oxide) in SA incorporated steel slag (SA-SS) is decreased more substantially than that of the control steel slag after carbonation. According to autoclaving test, cement paste cast with carbonated SA-SS showed less expansion than the one cast with carbonated control steel slag. Mortar cast with carbonated SA-SS obtained a competitive compressive strength of 40.63 MPa at 28 d. SA plays the role as a pH buffer that slows down the alkalinity decrease during the fleeting carbonation and hence enables more CO2 to dissolve in water. With enhanced carbonation efficiency, CaCO3 particles in carbonated SA-SS are big cubes which is opposed to the small, shapeless grains in carbonated control steel slag.

Recognition of concrete microcrack images under fluorescent excitation based on attention mechanism deep recurrent neural networks

This study aims to recognize fluorescent excitation images of microcracks in concrete components through the adoption of an Attention Mechanism-based Deep Recurrent Neural Network (RNN) model, thereby enhancing the accuracy and efficiency of crack detection. Considering the significance of concrete crack detection and the limitations in efficiency and accuracy of existing methods, this paper proposes an innovative image processing technique that combines fluorescent excitation methods with deep learning models to achieve earlier and more accurate identification of concrete microcracks. C30 concrete specimens were prepared experimentally and treated with fluorescent solution spray. Fluorescent images of cracks under UV light excitation were collected and processed using a segmented attention mechanism deep RNN model. Various performance evaluation metrics, including mean Intersection over Union (mIoU), mean Image Intersection over Union (miIoU), mean Image Dice Coefficient (miDice), and F1 score, were employed to comprehensively assess the model's performance. The results demonstrate that the proposed model achieved significant effectiveness in concrete crack image recognition, showing higher mIoU, miIoU, miDice, and F1 scores compared to other representative deep learning models, thus proving its advantages in recognition accuracy and efficiency. Particularly, by introducing the segmented attention mechanism, the model could capture microcrack features more effectively, significantly improving the accuracy of crack identification. This method not only provides a new technical approach for the early detection of concrete cracks but also lays the foundation for further development of efficient and accurate crack detection technologies to accommodate more complex engineering application scenarios.

Bottom-Up Synthesized Glucan Materials: Opportunities from Applied Biocatalysis.

Linear d-glucans are natural polysaccharides of simple chemical structure. They are comprised of d-glucosyl units linked by a single type of glycosidic bond. Noncovalent interactions within, and between, the d-glucan chains give rise to a broad variety of macromolecular nanostructures that can assemble into crystalline-organized materials of tunable morphology. Structure design and functionalization of d-glucans for diverse material applications largely relies on top-down processing and chemical derivatization of naturally derived starting materials. The top-down approach encounters critical limitations in efficiency, selectivity, and flexibility. Bottom-up approaches of d-glucan synthesis offer different, and often more precise, ways of polymer structure control and provide means of functional diversification widely inaccessible to top-down routes of polysaccharide material processing. Here the natural and engineered enzymes (glycosyltransferases, glycoside hydrolases and phosphorylases, glycosynthases) for d-glucan polymerization are described and the use of applied biocatalysis for the bottom-up assembly of specific d-glucan structures is shown. Advanced material applications of the resulting polymeric products are further shown and their important role in the development of sustainable macromolecular materials in a bio-based circular economy is discussed.

ARM-CO-UP: ARM CO operative U tilization of P rocessors

HMPSoCs combine different processors on a single chip. They enable powerful embedded devices, which increasingly perform ML inference tasks at the edge. State-of-the-art HMPSoCs can perform on-chip embedded inference using different processors, such as CPUs, GPUs, and NPUs. HMPSoCs can potentially overcome the limitation of low single-processor CNN inference performance and efficiency by cooperative use of multiple processors. However, standard inference frameworks for edge devices typically utilize only a single processor. We present the ARM-CO-UP framework built on the ARM-CL library. The ARM-CO-UP framework supports two modes of operation – Pipeline and Switch. It optimizes inference throughput using pipelined execution of network partitions for consecutive input frames in the Pipeline mode. It improves inference latency through layer-switched inference for a single input frame in the Switch mode. Furthermore, it supports layer-wise CPU/GPU DVFS in both modes for improving power efficiency and energy consumption. ARM-CO-UP is a comprehensive framework for multi-processor CNN inference that automates CNN partitioning and mapping, pipeline synchronization, processor type switching, layer-wise DVFS , and closed-source NPU integration.

Optimized Bentonite Clay Adsorbents for Methylene Blue Removal

This study addresses the urgent need for effective water treatment methods by synthesizing and characterizing activated bentonite clay (ABC) adsorbents to remove methylene blue (MB) from aqueous solutions efficiently. Conventional adsorbents often exhibit limitations in efficiency and regeneration capabilities, necessitating novel approaches to water treatment. The primary objective is synthesizing and characterizing high-quality ABC adsorbents capable of effectively removing MB. The activation process was optimized, and adsorbent performance was evaluated regarding MB removal efficiency and regeneration potential. Various activation dos-ages were investigated, and comprehensive physicochemical characterization was performed using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), BET (Brunauer–Emmett–Teller) analysis, X-ray fluorescence (XRF), thermogravimetric analysis (TGA), and X-ray diffraction (XRD). The synthesized adsorbents demonstrated exceptional MB removal efficiency (99.593%) and impressive adsorption capacity (22.131 mg/g) when activated with 16 M sodium hydroxide. The adsorption process exhibited spontaneity and exothermicity, as validated by Freundlich and second-order kinetic models. Furthermore, the adsorbents showcased successful regeneration and reusability over three cycles, highlighting their potential for long-term application in water treatment. This study significantly advances water treatment by offering a novel approach to MB removal using base-activated bentonite clay (BABC) adsorbents, contributing to the development of sustainable water treatment solutions.

Carbon quantum dots/BiVO4 S-scheme piezo-photocatalysts improved carrier separation for efficient antibiotic removal

Reasonable design of an efficient S-scheme photocatalyst remains an ongoing challenge due to the limitation of interfacial charge separation efficiency. Herein, CQDs/BiVO4 S-scheme heterojunction with Bi–O–C bond was synthesized by introducing carbon quantum dots (CQDs) growth on BiVO4 piezo-photocatalyst and absorbed visible light up to 750 nm. Under light + ultrasonic conditions, the reaction rate constant (k) of BVO/C-0.10 reached 0.0517 min−1 on tetracycline (TC) degradation, which was 2.24 and 4.04 times higher than those of BiVO4 and CQDs, respectively. The enhanced performance was attributed to the improved efficiency of the photogenerated carrier separation, originating from the combination of piezoelectric effect and S-scheme heterojunction with Bi–O–C bond. The Bi–O–C bond at the CQDs (3–8 nm) and BiVO4 interfaces connected the two semiconductor materials and provided an atomic-level interface channel for carrier migration. The piezoelectric properties of the composites were investigated by piezo−response force microscopy (PFM). Based on Mott−Schottky curves, X-ray photoelectron spectroscopy (XPS), and scavenging experiments, the possible piezo-photocatalytic mechanism was proposed in combination with the band structures and characteristics of CQDs and BiVO4. This work furnishes unique insights into developing efficient S-scheme piezo-photocatalysts for purifying wastewater.

Beyond Automation: Exploring the Synergy of Cloud, AI, Machine Learning, and IoT for Intelligent Systems

In the rapidly evolving landscape of Industry 4.0 and beyond, the amalgamation of Cloud Computing, Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) has emerged as a transformative force capable of elevating traditional automation to intelligent systems. This research paper delves into the profound potential of synergizing these advanced technologies, aiming to surpass the limitations of rule-based automation and foster a new era of adaptability, efficiency, and innovation.
 The study begins by articulating the escalating demand for intelligent systems that can dynamically respond to complex and ever-changing environments. The integration of Cloud, AI, ML, and IoT is posited as a solution to the constraints of conventional automation, offering the ability to process vast datasets, make informed decisions, and continuously learn from interactions.
 A comprehensive review of existing approaches and related works forms the foundation of this research. The analysis encompasses diverse applications, ranging from smart manufacturing to healthcare, showcasing the ways in which individual technologies have been leveraged. By scrutinizing these approaches, the study aims to distill the strengths and weaknesses, paving the way for a novel methodology that harnesses their collective power.
 Identifying the limitations of current approaches, such as scalability challenges, real-time processing bottlenecks, and interoperability issues, serves as a critical precursor to the proposed methodology. The paper presents a holistic strategy that intricately weaves together Cloud, AI, ML, and IoT into a unified framework. The architectural design, data flow, and interaction mechanisms are elucidated to demonstrate how this synergy can overcome existing challenges, providing adaptability and innovation in diverse domains.
 Empirical results derived from the implementation of the proposed methodology are presented and rigorously analyzed in the Results and Discussion section. Performance metrics, efficiency gains, and the impact on decision-making processes are thoroughly examined. Real-world case studies exemplify the effectiveness of the integrated approach, offering tangible evidence of its potential applications.
 Concluding remarks encapsulate the key findings, emphasizing the significance of the research in shaping the trajectory of intelligent systems. The broader implications of the proposed methodology across various industries are discussed, and avenues for future work are suggested. As technologies continue to evolve, the proposed methodology serves as a foundation for ongoing exploration, adaptation, and integration with emerging technologies.
 In essence, this research paper offers a detailed exploration into the synergy of Cloud, AI, ML, and IoT, paving the way for a new era of intelligent systems that transcend the limitations of traditional automation, fostering adaptability, efficiency, and innovation in an ever-changing technological landscape.

Breaking the limitation of thermodynamic cycle efficiency of the plasma synthetic jet actuator: Noble gases

The low thermodynamic cycle efficiency of the plasma synthetic jet actuator (PSJA) limits its application in flow control of supersonic aircraft. To improve the thermodynamic cycle efficiency of the PSJA, the energy conversion process of the PSJA under single discharge has been investigated by thermodynamic theory analysis and numerical simulation. The relations between thermodynamic cycle efficiency, specific heat ratio of gas medium, non-dimensional energy deposition and heating efficiency are established by theoretical deduction. Employing the three-dimensional nonconstant electrode center energy deposition model, energy conversion processes in the PSJA with six different gas mediums have been investigated. The simulation results show that the thermodynamic cycle efficiency of the PSJA with noble gas medium can exceed 3.2 %, which is 1.92 times of the PSJA with air medium due to their low volume specific heat. The maximum jet x-velocity of helium can reach 493.11 m/s, which is 3.3 times higher than that of air. Consequently, noble gases prove to be effective in improving the thermodynamic cycle efficiency of the PSJA and enhancing the strength of the synthetic jet. The advancement in the performance of the PSJA contributes to their enhanced capabilities in the field of active flow control.

Projected wind and solar energy potential in the eastern Mediterranean and Middle East in 2050

The ongoing energy transition from conventional fuels to renewable energy sources (RES) has given nations the potential to achieve levels of energy self-sufficiency previously thought unattainable. RES in the form of utility-scale solar and wind energy are currently the leading alternatives to fossil-fuel generation. Precise location siting that factors in efficiency limitations related to current and future climate variables is essential for enabling the green energy transition envisioned for 2050. In this context, understanding and mapping the intermittency of RES provides insights to energy system operators for their seamless integration into the grid. The Eastern Mediterranean and Middle East (EMME) region has the potential to harness vast amounts of RES. The scarcity of observations from weather station networks and the lack of private sector incentives for transitioning to RES mean that relevant, supporting weather and climate studies have been limited. This study employs the Weather Research and Forecasting model with Chemistry (WRF-CHEM) to estimate the RES technical potential of EMME countries and map the hourly generation profiles per source and country, simulated for the reference year 2015 and considering future conditions. The findings indicate that by 2050, seven countries within the region could transform into net energy exporters, while the remaining nine might remain reliant on energy imports or fossil fuels. Egypt emerges as a “powerhouse”, potentially enjoying a potential surplus energy generation of 76 GW per hour, whereas the United Arab Emirates may face an annual deficit of 955 TWh. Further, we derived the hourly generation profiles for wind and solar during different seasons. Four dominant patterns were identified. We find a complementary relationship for six countries, and for four countries, a substitute relationship between solar and wind energy generation. Greece stands out with a near-constant wind energy source, which would facilitate its integration into the national grid.

Low-mass Population III Star Formation due to the HD Cooling Induced by Weak Lyman–Werner Radiation

Lyman–Werner (LW) radiation photodissociating molecular hydrogen (H2) influences the thermal and dynamical evolution of the Population III (Pop III) star-forming gas cloud. The effect of powerful LW radiation has been well investigated in the context of supermassive black hole formation in the early Universe. However, the average intensity in the early Universe is several orders of magnitude lower. For a comprehensive study, we investigate the effects of LW radiation at 18 different intensities, ranging from J LW/J 21 = 0 (no radiation) to 30 (H-cooling cloud), on the primordial star-forming gas cloud obtained from a three-dimensional cosmological simulation. The overall trend with increasing radiation intensity is a gradual increase in the gas cloud temperature, consistent with previous works. Due to the HD cooling, however, the dependence of gas cloud temperature on J LW deviates from the aforementioned increasing trend for a specific range of intensities (J LW/J 21 = 0.025–0.09). In HD-cooling clouds, the temperature remained below 200 K during 105 yr after the first formation of the high-density region, maintaining a low accretion rate. Finally, the HD-cooling clouds have only a low-mass dense core (above 108 cm−3) with about 1–16 M ⊙, inside of which a low-mass Pop III star with ≤0.8 M ⊙ (a so-called “surviving star”) could form. The upper limit of star formation efficiency Mcore/Mvir,gas significantly decreases from 10−3 to 10−5 as HD cooling becomes effective. This tendency indicates that, whereas the total gas mass in the host halo increases with the LW radiation intensity, the total Pop III stellar mass does not increase similarly.

Development of a magnetic nanocomposite sorbent (NiCoMn/Fe3O4@C) for efficient extraction of methylene blue and Auramine O

A rapid and efficient method for the simultaneous monitoring and recovery of Auramine O (AO) and Methylene Blue (MB) dyes from water samples is presented. This method, named ultrasound-assisted dispersive-magnetic nanocomposites-solid-phase microextraction (UA-DMN-μSPE), utilizes NiCoMn/Fe3O4@C composite sorbents. Response surface methodology (RSM) combined with artificial neural networks (ANN) and generalized regression artificial neural network (GRNN) under central composite design (CCD) was employed to optimize various parameters for efficient extraction, followed by further refinement using desirability function analysis (DFA) and genetic algorithms (GA). Under optimized conditions, the method achieved exceptional recovery rates (99.5 ± 1.2% for AO and 99.8 ± 1.1% for MB) with acetone as the eluent. Additionally, a high preconcentration factor of 45.50 and 47.30 for AO and MB, respectively, was obtained. Low detection limits of 0.45 ng mL⁻1 (AO) and 1.80 ng mL⁻1 (MB) were achieved with wide linear response ranges (5–1000 and 5–2000 ng mL⁻1 for AO and MB, respectively). The method exhibited good stability with RSDs below 3% for five recycling runs, and minimal interference from various ions was observed. This UA-DMN-μSPE-UV/Vis method offers significant advantages in terms of efficiency, preconcentration, and detection limits, making it a valuable tool for the analysis of AO and MB in water samples.

High-efficiency high-numerical-aperture metalens designed by maximizing the efficiency limit

Theoretical bounds are commonly used to assess the limitations of photonic design. Here we introduce a more active way to use theoretical bounds, integrating them into part of the design process and identifying optimal system parameters that maximize the efficiency limit itself. As an example, we consider wide-field-of-view high-numerical-aperture metalenses, which can be used for high-resolution imaging in microscopy and endoscopy, but no existing design has achieved a high efficiency. By choosing aperture sizes to maximize an efficiency bound, setting the thickness according to a thickness bound, and then performing inverse design, we come up with high-numerical-aperture (NA=0.9) metalens designs with, to our knowledge, record-high 98% transmission efficiency and 92% Strehl ratio across all incident angles within a 60° field of view, reaching the maximized bound. This maximizing-efficiency-limit approach applies to any multi-channel system and can help a wide range of optical devices reach their highest possible performance.

Enhanced Separation Performance of Graphene Oxide Membrane through Modification with Graphitic Carbon Nitride

The treatment of tritiated nuclear wastewater is facing greater challenges with the continuous expansion of the nuclear industry. The key to solving the issue of detritium in low-abundance tritium water lies in developing highly efficient and cost-effective hydrogen isotope separation technology. Graphene oxide (GO) membrane separation method exhibits greater potential compared to other existing energy-intensive technologies for the challenging task of hydrogen isotope separation in nuclear wastewater. In recent years, researchers have explored few strategies to enhance the performance of graphene oxide (GO) membranes in hydrogen isotope water treatment, recognizing the current limitations in separation efficiency. In this study, the GO/g-C3N4 composite membrane has been successfully employed for the first time in the separation of hydrogen isotopes in water. A series of GO membranes were prepared and their performances were tested by a self-made experimental device. As a result, the separation performance of the GO membrane was enhanced by the modification with graphitic carbon nitride (g-C3N4). The permeation rate of the GO/g-C3N4 membrane was higher than that of the GO membrane, while maintaining a high separation factor. Our study also demonstrated that this phenomenon can be attributed to the changes in membrane structure at the microscopic scale. The H/D separation factor and the permeate flux of the composite membrane containing g-C3N4 of 6.7% by mass were 1.10 and 7.2 × 10−5 g·min−1·cm−2 are both higher than that of the GO membrane under the same experimental conditions, which is promising for the isotope treatment.

Ultrahigh Energy Storage Density and Efficiency in Orthorhombic PLZST Antiferroelectric Ceramics via Composition Regulation.

PbZrO3-based antiferroelectric (AFE) ceramic materials have emerged as potential candidates for the next generation of high-energy multilayer ceramic capacitors (MLCCs) because of their distinctive characteristics of double hysteresis loops. The energy storage efficiency of orthorhombic AFE ceramics with ultrahigh storage density is relatively low, which hinders their practical application. In this study, the low efficiency limit of PLZST-based orthorhombic ceramics was overcome by precisely adjusting the Sn4+ content in the (Pb0.95Ca0.02La0.02)(Zr0.99-xSnxTi0.01)O3 AFE ceramics. On one hand, the addition of Sn4+ disrupts the original long-range dipole and improves the rapid response of polarization reversal under the applied voltage. As a result, the difference in electric hysteresis under an electric field is reduced, leading to a significant improvement in energy storage efficiency. On the other hand, increasing the Sn4+ content suppresses the formation of oxygen vacancies, inhibiting grain growth and strengthening grain bonding. This results in ceramics with a high breakdown field strength. Ultimately, the resulting PLCZST ceramics reveal an expressively improved recoverable energy density of 10.2 J cm-3 together with a high energy efficiency of 91.4% under a high applied electric field of 560 kV cm-1. The present study demonstrates the tunability of performance in orthorhombic PLZST AFE ceramics, thereby introducing a ceramic material with exceptional energy storage capabilities for MLCC applications.

High-Performance Hydrogen-Fueled Internal Combustion Engines: Feasibility Study and Optimization via 1D-CFD Modeling

Hydrogen-powered mobility is believed to be crucial in the future, as hydrogen constitutes a promising solution to make up for the non-programmable character of the renewable energy sources. In this context, the hydrogen-fueled internal combustion engine represents one of the suitable technical solutions for the future of sustainable mobility. As a matter of fact, hydrogen engines suffer from limitations in volumetric efficiency due to the very low density of the fuel. Consequently, hydrogen-fueled ICEs can reach sufficient torque and power density only if suitable supercharging solutions are developed. Moreover, gaseous-engine performance can be improved to a great extent if direct injection is applied. In this perspective, a remarkable know-how has been developed in the last two decades on NG engines, which can be successfully exploited in this context. The objective of this paper is twofold. In the first part, a feasibility study has been carried out with reference to a typical 2000cc SI engine by means of 1D simulations. This study was aimed at characterizing the performance on the full load curve with respect to a baseline PFI engine fueled by NG. In this phase, the turbocharging/supercharging device has not been included in the model in order to quantify the attainable benefits in the absence of any limitation coming from the turbocharger. In the second part of this paper, the conversion of a prototype 1400cc direct injection NG engine, running with stoichiometric mixture, to run on a lean hydrogen combustion mode has been investigated via 1D simulations. The matching between engine and turbocharger has been included in the model, and the effects of two different turbomatching choices have been presented and discussed.

The micro black hole cellular battery: The ultimate limits of battery energy density

With the clean energy revolution, many methods of energy production, such as solar and wind power, are quite unstable because of weather variability. However, energy consumption remains relatively stable. Therefore, efficient energy storage could be crucial for the future. In this context, we will explore the theoretical limits of battery efficiency in terms of energy density. Surprisingly, although quite speculative, a potential solution might involve a cellular battery composed of micro black holes. In fact, let us suppose hypothetically that advanced future technology can handle the formation of black holes. Then, according to the extremal solution of the Reissner–Nordström metric from general relativity, such a battery could be stable and would not collapse into a larger black hole because the electromagnetic repulsion would precisely offset the force of gravity. Additionally, although it is generally assumed that nothing can escape from a black hole, a micro black hole could possibly annihilate another micro black hole, resulting in the release of an enormous amount of clean energy. For example, a battery weighing just one kilogram could provide approximately 470 million times the energy of the most efficient 200-kilogram lithium battery at the time of writing. While achieving such a level of technological advancement is certainly not imminent, it is not inconceivable that battery technology development could follow a trajectory similar to that of computer technology. Just as breakthroughs in physics and computer engineering have led to exponential growth in computer efficiency in the last 50 years, it is possible that battery efficiency could double or even quadruple every few years following different types of breakthroughs. Nonetheless, the theoretical concept of a micro black hole battery appears to align with current predictions of fundamental physics regarding the ultimate physical limits on energy density storage. This strongly indicates we are at the very early stage of battery technology, not even close to the end.

Experimental results for RVK-500 recombiner tested in conditions typical for pressurized water NPP severe accidents

Severe accidents at NPPs with light water coolant can lead to situations when large quantities of hydrogen are released due to zirconium-steam reaction. To avoid explosion consequences, they started to install hydrogen passive autocatalytic recombiners (PARs) at NPPs. Calculating simulation based on PAR models is used to predict and justify the needed quantity of PARs and the chosen place of their location inside the NPP. To validate PAR computational models, experimental data are need. Within the scope of this work, the integrated tests of the RVK-500 type recombiner, which included 20 experiments, were conducted to obtain large body of data on PAR operation in different modes and conditions that can be realized in case of hypothetical accident at NPP. For this purpose, a facility equipped with a measuring set able to work at high pressures, temperatures, and humidity was constructed. The tests were conducted in accord with thepredevopled PAR testing procedure and program to describe PAR characteristics, such as its start-up, H2 recombination rate, efficiency, and ignition limit. In addition, a small-scale facility was used to study the potential of particles separated from the catalytic elements to induce combustion.

Automatic detection of quartz glass subsurface defects by laser scattering method based on an ellipsoidal mirror.

With the improvement of quality requirements of optical components, the detection of subsurface defects of optical components has become a key technology. The existing detection methods still have some limitations in detection depth and detection efficiency. In this paper, a defect scattering light collection method based on ellipsoidal mirror model is used to analyze the scattering light collection efficiency under different experimental conditions theoretically, and the favorable conditions for improving the scattering light collection are proposed. After simulation verification, the use of ellipsoidal reflectors to collect scattered light can effectively avoid the impact of surface defects compared to lenses. At the same time, an experimental system based on this method is set up to filter the stray light by mean filtering method. The system detected three scratches (2μm in width and 252nm in depth) on the underside of a piece of quartz glass. The results show that the system can clearly detect the subsurface defects of optical components.