Long-term System Stability Research Articles

N-doped C encapsulated Li2TiSiO5 nanoparticles for high-rate highly stable lithium storage

Achieving high charging rates (≤ 15 min) in lithium-ion batteries (LIBs) is imperative for their widespread implementation in all-electric vehicles. However, the pursuit of elevated charging rates often leads to compromises in capacity and cycling stability. In this manuscript, we present a groundbreaking approach utilizing a composite material composed of nitrogen-doped carbon-encapsulated Li2TiSiO5 nanoparticles (LTSO@C-N) as the anode material for LIBs, offering rapid and exceptionally stable lithium storage. The encapsulation of Li2TiSiO5 nanoparticles by nitrogen-doped carbon is realized via a facile liquid-phase polymerization and the following pyrolysis route. The uniformly deposited nitrogen-doped carbon layer on the surface of Li2TiSiO5 nanoparticles within LTSO@C-N serves a dual purpose: enhancing the conductive properties of Li2TiSiO5 to ensure efficient charge transfer and Li+ transport, while concurrently inhibiting grain pulverization over extended cycling periods. The deliberate incorporation of nitrogen-doped carbon optimizes Li2TiSiO5 anode electrochemical performance, simultaneously reducing structural degradation during prolonged cycling. This enhances the lithium-ion battery system's long-term stability and reliability. While exhibiting an average operational potential of approximately 0.28 V in comparison to Li+/Li, the LTSO@C-N electrode manifests a commendable specific capacity of 345 mAh g-1 at a current density of 0.1 A g-1. Notably, it attains a robust lithium storage capability even under high-rate conditions, exemplified by a sustained capacity of 205 mAh g-1 over 1000 cycles at 2 A g-1, devoid of any discernible decay. The electrode's impressive electrochemical performance highlights its potential as an advanced anode for high-performance lithium-ion batteries, ensuring stability.

Comparison of Human Long-Term Liver Models for Clearance Prediction of Slowly Metabolized Compounds.

The accurate prediction of human clearance is an important task during drug development. The proportion of low clearance compounds has increased in drug development pipelines across the industry since such compounds may be dosed in lower amounts and at lower frequency. These type of compounds present new challenges to in vitro systems used for clearance extrapolation. In this study, we compared the accuracy of clearance predictions of suspension culture to four different long-term stable in vitro liver models, including HepaRG sandwich culture, the Hµrel stochastic co-culture, the Hepatopac micropatterned co-culture (MPCC), and a micro-array spheroid culture. Hepatocytes in long-term stable systems remained viable and active over several days of incubation. Although intrinsic clearance values were generally high in suspension culture, clearance of low turnover compounds could frequently not be determined using this method. Metabolic activity and intrinsic clearance values from HepaRG cultures were low and, consequently, many compounds with low turnover did not show significant decline despite long incubation times. Similarly, stochastic co-cultures occasionally failed to show significant turnover for multiple low and medium turnover compounds. Among the different methods, MPCCs and spheroids provided the most consistent measurements. Notably, all culture methods resulted in underprediction of clearance; this could, however, be compensated for by regression correction. Combined, the results indicate that spheroid culture as well as the MPCC system provide adequate in vitro tools for human extrapolation for compounds with low metabolic turnover. SIGNIFICANCE STATEMENT: In this study, we compared suspension cultures, HepaRG sandwich cultures, the Hµrel liver stochastic co-cultures, the Hepatopac micropatterned co-cultures (MPCC), and micro-array spheroid cultures for low clearance determination and prediction. Overall, HepaRG and suspension cultures showed modest value for the low determination and prediction of clearance compounds. The micro-array spheroid culture resulted in the most robust clearance measurements, whereas using the MPCC resulted in the most accurate prediction for low clearance compounds.

Reviewing the potential of anaerobic membrane bioreactors in wastewater treatment

Anaerobic membrane bioreactors (AnMBRs) represent an innovative approach to wastewater treatment, combining anaerobic digestion with membrane filtration to achieve efficient organic pollutant removal and resource recovery. This review critically examines the potential of AnMBRs in wastewater treatment, highlighting their principles, advantages, challenges, recent advancements, and future prospects. AnMBRs offer several advantages over traditional aerobic treatment methods, including higher organic loading rates, reduced energy requirements, and biogas production through methane generation. However, challenges such as membrane fouling, reactor complexity, and operational costs have limited their widespread adoption. Recent advancements in membrane materials, fouling mitigation strategies, and process optimization have improved AnMBR performance and feasibility. Novel membrane materials with enhanced fouling resistance and durability have been developed, while innovative cleaning techniques and operational protocols have been implemented to mitigate membrane fouling and prolong membrane lifespan. Process optimization strategies, including reactor design modifications and operational parameter adjustments, have enhanced treatment efficiency and reduced energy consumption in AnMBRs. Future research directions in AnMBR technology focus on optimizing reactor configurations, exploring novel membrane materials and fouling control strategies, and conducting comprehensive techno-economic assessments to evaluate the environmental and economic sustainability of AnMBRs. Integration of AnMBRs with emerging technologies such as membrane distillation, forward osmosis, and bioelectrochemical systems holds promise for further enhancing treatment performance and resource recovery capabilities. Additionally, addressing knowledge gaps in membrane fouling mechanisms, microbial community dynamics, and long-term system stability is crucial for advancing AnMBR technology and facilitating its widespread implementation in wastewater treatment. Overall, AnMBRs offer significant potential for sustainable wastewater treatment, providing opportunities for organic pollutant removal, energy recovery, and resource reuse. By addressing technical challenges, optimizing process parameters, and conducting interdisciplinary research, AnMBRs can contribute to the development of efficient, cost-effective, and environmentally friendly wastewater treatment solutions, ultimately supporting the goal of achieving cleaner water resources and a more sustainable future.

A fast and stable GNSS-LiDAR-inertial state estimator from coarse to fine by iterated error-state Kalman filter

Simultaneous localization and mapping (SLAM) aims to solve the problems of robot localization and mapping in unknown environments. Recent related research usually uses closed-loop correction or integrate GNSS (Global Navigation Satellite System) into the optimization framework to ensure the long-term system accuracy and stability at the cost of huge computational resources. To balance efficiency and accuracy, this paper presents a fast and stable GNSS-LiDAR-inertial state estimator: GNSS, LiDAR and IMU are fused to achieve state estimation from coarse to fine, thereby improving the system accuracy and stability; the overall framework based on iterated error-state Kalman filter makes our system faster than most multi-sensor fusion SLAM. We also design a fast GNSS online initialization method and a multi-layer outlier rejection mechanism for our system. In addition, we apply backward propagation for multi-sensor motion compensation to overcome the limitations of fast motion. Finally, comprehensive experiments demonstrate that our system achieves higher accuracy and computational efficiency than the state-of-the-art navigation systems on the latest challenging public datasets, and perform equally well in the real environment.

Nanoemulsions Embedded in Alginate Beads as Bioadhesive Nanocomposites for Intestinal Delivery of the Anti-Inflammatory Drug Tofacitinib.

Oral administration of nanoparticles (NPs) is a promising strategy to overcome solubility and stability issues of many active compounds. However, this route faces major obstacles related to the hostile gastrointestinal (GI) environment, which impairs the efficacy of orally administered nanomedicines. Here, we propose nanocomposites as a promising approach to increase the retention time of NPs in the intestinal tract by using bio- and mucoadhesive matrixes able to protect the cargo until it reaches the targeted area. A microfluidic-based approach has been applied for the production of tailored nanoemulsions (NEs) of about 110 nm, used for the encapsulation of small hydrophobic drugs such as the anti-inflammatory JAK-inhibitor tofacitinib. These NEs proved to be efficiently internalized into a mucus-secreting human intestinal monolayer of Caco-2/HT29-MTX cells and to deliver tofacitinib to subepithelial human THP-1 macrophage-like cells, reducing their inflammatory response. NEs were then successfully encapsulated into alginate hydrogel microbeads of around 300 μm, which were characterized by rheological experiments and dried to create a long-term stable system for pharmaceutical applications. Finally, ex vivo experiments on excised segments of rats' intestine proved the bioadhesive ability of NEs embedded in alginate hydrogels compared to free NEs, showing the advantage that this hybrid system can offer for the treatment of intestinal pathologies.

Online-Learning-Based Fast-Convergent and Energy-Efficient Device Selection in Federated Edge Learning

As edge computing faces increasingly severe data security and privacy issues of edge devices, a framework called federated edge learning (FEL) has recently been proposed to enable machine learning (ML) model training at the edge, ensuring communication efficiency and data privacy protection for edge devices. In this paradigm, the training efficiency has long been challenged by the heterogeneity of communication conditions, computing capabilities, and available data sets at devices. Currently, researchers focus on solving this challenge via device selection from the perspective of optimizing energy consumption or convergence speed. However, the consideration of any one of them is insufficient to guarantee the long-term system efficiency and stability. To fill the gap, we propose an optimization problem to simultaneously minimize the total energy consumption of selected devices and maximize the convergence speed of the global model for device selection in FEL, under the constraints of training data amount and time consumption. For the accurate calculation of energy consumption, we deploy online bandit learning to estimate the CPU-cycle frequency availability of each device, based on an efficient algorithm, named fast-convergent energy-efficient device selection (FCE2DS), is proposed to solve the optimization problem with a low level of time complexity. Through a series of comparative experiments, we evaluate the performance of the proposed FCE2DS scheme, verifying its high training accuracy and energy efficiency.

Frequency-Multiplexed Storage and Distribution of Narrowband Telecom Photon Pairs over a 10-km Fiber Link with Long-Term System Stability

The ability to transmit quantum states over long distances is a fundamental requirement of the quantum internet and is reliant upon quantum repeaters. Quantum repeaters involve entangled photon sources that emit and deliver photonic entangled states at high rates and quantum memories that can temporarily store quantum states. Improvement of the entanglement distribution rate is essential for quantum repeaters, and multiplexing is expected to be a breakthrough. However, limited studies exist on multiplexed photon sources and their coupling with a multiplexed quantum memory. Here, we demonstrate the storing of a frequency-multiplexed two-photon source at telecommunication wavelengths in a quantum memory accepting visible wavelengths via wavelength conversion after 10-km distribution. To achieve this, quantum systems are connected via wavelength conversion with a frequency stabilization system and a noise reduction system. The developed system was stably operated for more than 42 h. Therefore, it can be applied to quantum repeater systems comprising various physical systems requiring long-term system stability.

Iron-Sepiolite High-Performance Magnetorheological Polishing Fluid with Reduced Sedimentation.

A sedimentation-stable magnetorheological (MR) polishing slurry on the basis of ferrofluid, iron particles, Al2O3, and clay nanofiller in the form of sepiolite intended for MR polishing has been designed, prepared, and its polishing efficiency verified. Added clay substantially improved sedimentation stability of the slurry, decreasing its sedimentation rate to a quarter of its original value (1.8 to 0.45 mg s−1) while otherwise maintaining its good abrasive properties. The magnetisation curve measurement proved that designed slurry is soft magnetic material with no hysteresis, and its further suitability for MR polishing was confirmed by its magnetorheology namely in the quadratically increased yield stress due to the effect of applied magnetic field (0 to 600 kA m−1). The efficiency of the MR polishing process was tested on the flat samples of injection-moulded polyamide and verified by surface roughness/3D texture measurement. The resulting new composition of the MR polishing slurry exhibits a long-term stable system with a wide application window in the MR polishing process.

How innovations in methodology offer new prospects for volume electron microscopy

Detailed knowledge of biological structure has been key in understanding biology at several levels of organisation, from organs to cells and proteins. Volume electron microscopy (volume EM) provides high resolution 3D structural information about tissues on the nanometre scale. However, the throughput rate of conventional electron microscopes has limited the volume size and number of samples that can be imaged. Recent improvements in methodology are currently driving a revolution in volume EM, making possible the structural imaging of whole organs and small organisms. In turn, these recent developments in image acquisition have created or stressed bottlenecks in other parts of the pipeline, like sample preparation, image analysis and data management. While the progress in image analysis is stunning due to the advent of automatic segmentation and server‐based annotation tools, several challenges remain. Here we discuss recent trends in volume EM, emerging methods for increasing throughput and implications for sample preparation, image analysis and data management.

Online Credit Card Fraud Detection and Anomaly User Blocking

The use of credit cards has expanded considerably as a result of rapid advancements in electronic commerce technologies. As credit cards become the most popular method of payment for both online and offline purchases, incidences of credit card fraud are on the rise. Transactions with Credit Cards continue to expand in number, capturing a larger share of the US payment system and resulting in a higher rate of stolen account numbers and bank losses. Improved fraud detection has thus become critical to the payment system's long-term stability in the United States. For several years, banks have deployed early fraud warning systems. Large-scale data mining tools have the potential to improve commercial practice. Scalable strategies for analysing enormous volumes of transaction data and efficiently computing fraud detectors in a timely way, especially for e-commerce, is a critical issue. Aside from scalability and efficiency, the fraud-detection task has technical issues such as skewed training data distributions and non-uniform cost per error, both of which have received little attention in the now-established ledge-discovery and data mining communities.

Rational design of TiO2/BiSbS3 heterojunction for efficient solar water splitting

Solar induced water splitting with semiconductor photoelectrodes has been recognized as a sustainable alternative for addressing the energy crisis and pollution by creating hydrogen as a clean fuel. Insufficient light absorption and quick recombination of excitons are the most major bottlenecks in the emergence of semiconductor-based photocatalysts. The major challenge to the commercialization of this technique is the development of photoelectrodes that fulfill the PEC water-splitting requirements. In this study, As a photoanode for PEC water splitting, BiSbS3 NRs were grown on TiO2 films using a simple chemical bath deposition method. Such heterojunctions were chosen to amplify and expand the absorption of visible light, charge transport, charge separation and electrical conduction. The results show that the TiO2/BiSbS3 heterojunction photoanode exhibits relatively low charge transfer resistance, a highest current density of 5.0 mA.cm−2 and STH conversion efficiency of 4.5% at 0.3 V vs RHE. The system's long-term stability was also evaluated for a period of 10,000 s and hydrogen evolution was carried out for 9000 s. Photoluminescence (PL) spectroscopy confirms that TiO2/BiSbS3 heterojunction exhibits stronger light absorption and efficient charge transfer compare to bare TiO2 and BiSbS3. Composite exhibits larger Brunauer − Emmett − Teller (BET) surface area compare to bare TiO2 and BiSbS3 which have contributed in excellent PEC performance compare to bare materials.

A combined model reference adaptive control law for multirotor UAVs

Model reference adaptive control (MRAC) offers the potential to adapt in real-time to changes in the performance of small unmanned air vehicles. There are significant challenges with their use, however, primarily in the implementation and assurance of long-term system stability. This paper presents flight test results for a combined model reference adaptive control (CMRAC) law applied to the height control loop of a multirotor. Key features include the implementation of CMRAC with a baseline controller allowing for in-flight switching between the two; the use of an augmented state to improve the tracking performance and a CMRAC implementation that provides a shorter transient phase, faster parameter convergence, and closer tracking of the desired reference model response when compared with standard MRAC. With the current exponential growth of interest in unmanned air vehicles, the potential benefits of using CMRAC for control system development are significant, particularly for new vehicles with short development and testing phases and in cases where there are significant configuration changes in flight or prior to rapid deployment.

Livestock integration into soybean systems improves long-term system stability and profits without compromising crop yields

Climate models project greater weather variability over the coming decades. High yielding systems that can maintain stable crop yields under variable environmental scenarios are critical to enhance food security. However, the effect of adding a trophic level (i.e. herbivores) on the long-term stability of agricultural systems is not well understood. We used a 16-year dataset from an integrated soybean-beef cattle experiment to measure the impacts of grazing on the stability of key crop, pasture, animal and whole-system outcomes. Treatments consisted of four grazing intensities (10, 20, 30 and 40 cm sward height) on mixed black oat (Avena strigosa) and Italian ryegrass (Lolium multiflorum) pastures and an ungrazed control. Stability of both human-digestible protein production and profitability increased at moderate to light grazing intensities, while over-intensification or absence of grazing decreased system stability. Grazing did not affect subsequent soybean yields but reduced the chance of crop failure and financial loss in unfavorable years. At both lighter and heavier grazing intensities, tradeoffs occurred between the stability of herbage production and animal live weight gains. We show that ecological intensification of specialized soybean systems using livestock integration can increase system stability and profitability, but the probability of win–win outcomes depends on management.

MBCP: Performance Analysis of Large Scale Mainstream Blockchain Consensus Protocols

As Blockchain innovation picks up popularity in many areas, it is frequently hailed as a sound innovation. Because of the decentralization and encryption, many imagine that data put away in a Blockchain is and will consistently be protected. Among various abstraction layers of Blockchain architecture, the consensus layer is the core component behind the performance and security measures of the Blockchain network. Consensus mechanisms are a critical component of a Blockchain system's long-term stability. Consensus forms the core of blockchain technology. Therefore, a range of consensus protocols has been introduced to maximize Blockchain systems' efficiency and meet application domains' individual needs. This research paper describes the layered architecture of Blockchain. A comprehensive review of mainstream consensus protocols mainly Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), Proof of Activity (PoA) is presented in the paper. These mainstream consensus protocols have been explained and detailed performance analysis of these consensus protocols has been done. We have proposed a performance matrix of these consensus protocols based on different parameters like Degree of decentralization, Latency, Fault Tolerance Rate, Scalability, etc. Consensus protocols being the core of a strong fault-tolerant secured blockchain system, the proposed work intends to help inappropriate protocol selection and further research on strengthening trust and ownership in the technology. Depending upon different parameters like decentralization which is low in POA compared to other protocols, whereas POW is non-scalable, so depending on the priority of a particular performance parameter, the paper will help in the selection of a specific protocol.

High density long-term cultivation of Chlorella vulgaris SAG 211-12 in a novel microgravity-capable membrane raceway photobioreactor for future bioregenerative life support in SPACE

Hybrid life support systems are of great interest for future far-distant space exploration missions to planetary surfaces, e.g. Mars, planned until 2050. By synergistically combining physicochemical and biotechnological algae-based subsystems, an essential step towards the closure of the carbon loop in environmental control and life support systems (ECLSS) shall be accomplished, offering a wide beneficial potential for ECLSS through the utilization of oxygenic photosynthesis: O2 and potential human food can be formed in-situ from CO2 and water. The wild type green alga Chlorella vulgaris strain SAG 211-12 was selected as model microorganism due to its photoautotrophic growth, high biomass yield, cultivation flexibility and long-term cultivation robustness. The current study presents for the first time a stable xenic long-term processing of microalgae in a novel microgravity capable membrane raceway photobioreactor for 188 days with the focus on algal growth kinetics and gas evolution. In particular, culture homogeneity and viability were monitored and evaluated during the whole cultivation process due to their putative crucial impact on long-term functionality and efficiency of a closed cultivation system. Based on a specially designed cyclic batch cultivation process for SAG 211-12, a successive biomass growth up to a maximum of 12.2 g l−1 with a max. global volumetric productivity of 1.3 g l−1 d−1 was reached within the closed loop system. The photosynthetic capacity was assessed to a global molar photosynthetic quotient of 0.31. Furthermore, cultivation parameters for a change from batch to continuous processing at high biomass densities and proliferation rates are introduced. The presented µgPBR miniature plant and the developed high throughput cultivation process are planned to be tested under real space conditions within the PBR@LSR project (microgravity and cosmic radiation) aboard the International Space Station with an operation period of up to 180 days to investigate the impact on long-term system stability.

Multiplanet systems in inviscid discs can avoid forming resonant chains

ABSTRACT Convergent migration involving multiple planets embedded in a viscous protoplanetary disc is expected to produce a chain of planets in mean motion resonances (MMRs), but the multiplanet systems observed by the Kepler spacecraft are generally not in resonance. We demonstrate that under equivalent conditions, where in a viscous disc convergent migration will form a long-term stable system of planets in a chain of MMRs, migration in an inviscid disc often produces a system which is highly dynamically unstable. In particular, if planets are massive enough to significantly perturb the disc surface density and drive vortex formation, the smooth capture of planets into MMRs is disrupted. As planets pile up in close orbits, not protected by resonances, close encounters increase the probability of planet–planet collisions, even while the gas disc is still present. While inviscid discs often produce unstable non-resonant systems, stable, closely packed, non-resonant systems can also be formed. Thus, when examining the expectation for planet migration to produce planetary systems in MMRs, the effective turbulent viscosity of the protoplanetary disc is a key parameter.

A Pluto–Charon Sonata: Dynamical Limits on the Masses of the Small Satellites

Abstract During 2005–2012, images from Hubble Space Telescope (HST) revealed four moons orbiting Pluto–Charon. Although their orbits and geometric shapes are well-known, the 2σ uncertainties in the masses of the two largest satellites—Nix and Hydra—are comparable to their HST masses. Remarkably, gravitational n-body computer calculations of the long-term system stability on 0.1–1 Gyr timescales place much tighter constraints on the masses of Nix and Hydra, with upper limits ∼10% larger than the HST mass. Constraints on the mass density using size measurements from New Horizons suggest Nix and Hydra formed in icier material than Pluto and Charon.

The electrolyte matters: Stable systems for high rate electrochemical CO2 reduction

Products from electrochemical CO2 reduction have the potential to replace fossil resources in the chemical industry by using renewable energies. However, stable electrolyte systems are an ongoing challenge for long-term electrolysis operation. We report the stability of different electrolyte combinations for two different electrochemical membrane reactor (ecMR) designs. Gas diffusion electrodes (GDEs) with different composition and manufacturing processes were subsequently tested in a stable electrolyte. Electrolytes in cation exchange membrane based ecMRs are only stable, if the anolyte is an acid with only protons as cations. Pure water usage is possible if a zero-gap assembly is used on the anode side. The supporting catholyte can be chosen freely as long as it is not electrochemically active and does not react with CO2. In a stable electrolyte system, pressed and non-pressed Nafion- and PTFE-bonded GDEs with copper and silver as catalyst are compared for current densities up to −300 mA cm−2. The results highlight the importance of the individual optimization of the GDE network in terms of porosity and hydrophobicity. An C2H4 current efficiency of 51% for a copper GDE and a C:H synthesis gas ratio of 2:1 with a silver GDE are measured for −300 mA cm−2. Further, experiments with highly acidic and highly buffered electrolytes, respectively electrolytes with a high ionic strength, show a strong decrease in cathodic overpotential. This work gives a clear guideline for ecMR electrolyte operation for a long-term stable system performance. We highlight the need for a deeper understanding of interfacial phenomena to maximize energetic efficiency.

Analysis of technical and economic parameters of fusion power plants in future power systems

The European power system faces two main challenges: first, the increasing share of fluctuating energy sources in the power generation sector challenges the balance of generation and demand. Second, the expected shift towards using more electricity in the heating and transportation sectors leads to rising demand. To ensure both sufficient energy supply and long-term power system stability of the power system, fusion power is expected to play an important role in the future. This paper provides a sensitivity analysis of fusion power plant parameters in a power system with a large fraction of renewable energies. The results depend strongly on the underlying scenario assumptions, especially on future technical and economic improvements. Finally, the amount of fusion power investments depends on both demand level and relative costs of competing technologies.

Compact, Automated, Inexpensive, and Field-Deployable Vacuum-Outlet Gas Chromatograph for Trace-Concentration Gas-Phase Organic Compounds.

The identification and quantification of gas-phase organic compounds, such as volatile organic compounds (VOCs), frequently use gas chromatography (GC), which typically requires high-purity compressed gases. We have developed a new instrument for trace-concentration measurements of VOCs and intermediate-volatility compounds of up to 14 carbon atoms in a fully automated (computer-free), independent, low-cost, compact GC-based system for the quantitative analysis of complex mixtures without the need for compressed, high-purity gases or expensive detectors. Through adsorptive analyte preconcentration, vacuum GC, photoionization detectors, and need-based water-vapor control, we enable sensitive and selective measurements with picogram-level limits of detection (i.e., under 15 ppt in a 4 L sample for most compounds). We validate performance against a commercial pressurized GC, including resolving challenging isomers of similar volatility, such as ethylbenzene and m/ p-xylene. We employ vacuum GC across the whole column with filtered air as a carrier gas, producing long-term system stability and performance over a wide range of analytes. Through theory and experiments, we present variations in analyte diffusivities in the mobile phase, analyte elution temperatures, optimal linear velocities, and separation-plate heights with vacuum GC in air at different pressures, and we optimize our instrument to exploit these differences. At 2-6 psia, the molecular diffusion coefficients are 6.4-2.1 times larger and the elution temperatures are 39-92 °C lower than with pressurized GC with helium (at 30 psig) depending on the molecular structure, and we find a wide range of optimal linear velocities (up to 60 cms-1) that are faster with broader tolerances than with pressurized-N2 GC.