Scale Applications Research Articles

Scalable MOF-based mixed matrix membranes with enhanced permeation processes facilitate the scale application of membrane-based carbon capture technologies

Mixed-matrix membranes (MMMs) leverage the processability of polymers and selectivity of Metal-Organic Frameworks (MOFs). However, they still suffer from poor interfacial compatibility and limited scalability in preparation. In certain polymers, MOFs can bridge the pores within the polymer membrane, enhancing the CO2 adsorption and solubility properties, thus selectively boosting the CO2 permeability. In this study, high-performance MMMs were prepared using scalable CALF-20 in combination with PIM-1. MMMs with a 5% doping level achieved CO2 permeability up to 8003 barrer with 25% improvement in CO2/N2 selectivity. This enhancement was attributed to well-designed MMMs, where MOFs matched the abundant non-interconnecting pores in the PIM-1 membrane. This study represents a significant advancement towards scaling up the preparation of high-performance MOF-based MMMs for carbon capture applications.

Selective ammonia recovery from wastewater by SDS-AC based microfiltration membrane flow electrode capacitor deionization

Flow Electrode Capacitance Deionization (FCDI) has been frequently used for NH4+ recovery from wastewater as a low-energy, high-efficiency electrochemical technique. However, issues such as high cost (mainly due to the use of ion-exchange membranes) and weak selectivity have limited the expansion of their applications. In this study, SDS-AC was prepared and applied in microfiltration membrane FCDI (MFFCDI) to recover ammonia (NH4+). The material characterization results showed that the surfactant was stably loaded on the AC surface, and the adsorption capacity of modified AC for NH4+ was greatly enhanced. During the recovery process, NH4+ migrated to the electrode chamber and immobilized on the SDS-AC, while Na+ migrated to the electrode chamber and then released to the desalination chamber due to co-ion repulsion. Based on this principle, selective recovery of NH4+ was achieved (selectivity = 3.51). At the end of the recovery, more than 70 % of the NH4+ was immobilized on the SDS-AC and the NH4+ could be desorbed with NaOH. The results of the recycling experiments showed good stability of the SDS-AC-based MFFCDI system, and the recovery of food waste fermentation liquor demonstrated that the system could realize the selective recovery of NH4+ from complex feed water. In summary, the SDS-AC-based MFFCDI technology has great potential for the application of NH4+ recovery from wastewater. Although the scale of this study was limited to the laboratory stage, it still shows potential for application in engineering. In the future, larger scale applications in engineering will be carried out and the environmental and economic benefits of the technology will be assessed through a full life cycle analysis.

Industrial–scale production of various bio–commodities by engineered microbial cell factories: Strategies of engineering in microbial robustness

The utilization of renewable, non–edible biomass for synthesis of valuable bio–products including bio–fuels, bio-chemicals and bio–polymeric materials, in an environmentally sustainable manner is crucial for addressing the urgent environmental challenges caused by our substantial dependence on fossil fuel resources. In this context, engineered microbial cell factories (MCFs), which are the modified microorganisms, have gained attention and provide biosynthetically optimized pathways for the production of desired bio–commodities using renewable carbon sources. Biosynthetic routes for the production of such bio–commodities can be categorized into three groups based on the chosen microbial host for genetic modification: native, non–native, and artificial pathways. Engineered MCFs are increasingly essential in the pharmaceutical, food, and bio–chemical industries and are being developed to address the growing world population and socioeconomic crisis. Mainly, microorganisms have been utilized in the manufacturing of a range of bio–products including amino acids, carboxylic acids, carotenoids, enzymes, vitamins, plant natural products, biogas, and other biofuels. Furthermore, the implementation of advanced metabolic engineering and synthetic biology tools & techniques enhances the speed, concentration, and efficiency of commercially important substances by modifying the metabolism, carbon–energy balance and eliminating an undesired ATP sink, physiology, and stress response. All these has resulted in rapid growth of industrial biotechnology for production of several bio–commodities. Further, the scale and numbers of bio–commodities is increasing with time. This review summarizes the design of MFCs, selection of microbial strains, metabolic pathways, engineered MCFs for industrial–scale applications, strategies for engineering microbial robustness, commercial restrictions, and their future prospects.

The Gastroscopy RAte of Cleanliness Evaluation (GRACE) Scale: an international reliability and validation study.

Mucosal visualization during upper gastrointestinal (UGI) endoscopy can be impaired by the presence of foam, bubbles, and mucus. Some UGI endoscopy visibility scales have been proposed but have not undergone multicenter validation. This study aimed to develop and validate the Gastroscopy RAte of Cleanliness Evaluation (GRACE) scale. A multicenter, international, cross-sectional study was conducted. The GRACE scale is based on a score from 0 (worst) to 3 (excellent) for esophagus, stomach, and duodenum, for a total ranging from 0 to 9. In phase 1, four expert endoscopists evaluated 60 images twice, with a 2-week interval between rounds; in phase 2, the same 60 images were scored twice by one expert and one nonexpert endoscopist from 27 endoscopy departments worldwide. For reproducibility assessment and real-time validation, the scale was applied to consecutive patients undergoing gastroscopy at each center. On internal validation, interobserver agreement was 0.81 (95 %CI 0.73-0.87) and 0.80 (95 %CI 0.72-0.86), with reliability of 0.73 (95 %CI 0.63-0.82) and 0.72 (95 %CI 0.63-0.81), in the two rounds, respectively. On external validation, overall interobserver agreement was 0.85 (95 %CI 0.82-0.88) and reliability was 0.79 (95 %CI 0.73-0.84). In real-time evaluation, the overall proportion of correct classifications was 0.80 (95 %CI 0.77-0.82). The GRACE scale showed good interobserver agreement, reliability, and validity. The widespread use of this scale could enhance quality and standardize the assessment of mucosal cleanliness during UGI endoscopy, pushing endoscopists to strive for excellent visibility and reducing the risk of missed lesions.

Decarbonization of existing heating networks through optimal producer retrofit and low-temperature operation

District heating networks are considered crucial for enabling emission-free heat supply, yet many existing networks still rely heavily on fossil fuels. With network pipes often lasting over 30 years, retrofitting heat producers in existing networks offers significant potential for decarbonization. This paper presents an automated design approach, to decarbonize existing heating networks through optimal producer retrofit and ultimately enabling 4th generation operation. Using multi-objective, mathematical optimization, it balances CO2 emissions and costs by assessing different CO2 prices. The optimization selects producer types, capacities, and for each period their heat supply and supply temperature. The considered heat producers are a natural gas boiler, an air-source heat pump, a solar thermal collector, and an electric boiler. A non-linear heat transport model ensures accurate accounting of heat and momentum losses throughout the network, and operational feasibility. The multi-period formulation incorporates temporal changes in heat demand and environmental conditions throughout the year. By formulating a continuous problem and using adjoint-based optimization, the automated approach remains scalable towards large scale applications. The design approach was assessed on a medium-sized 3rd generation district heating network case and was able to optimally retrofit the heat producers. The retrofit study highlights a strong influence of the CO2 price on the optimal heat producer design and operation. Increasing CO2 prices shift the design towards a heat supply dominated by an energy-efficient and low-emission heat pump. Furthermore, it was observed that even for the highest explored CO2 price of 0.3€kg−1, the low-emission heat pump, electric boiler and solar thermal collector cannot fully replace the natural gas boiler in an economic way.

Fast Production of Covalent Organic Frameworks for Covalent Enzyme Immobilization with Boosted Enzymatic Catalysis by Solar‐Driven Photothermal Effect

AbstractDeveloping new enzyme‐immobilization systems to stabilize their dynamic structures and meanwhile enhance their catalytic activity is of great significance but very challenging. Herein, we design and fabricate a class of robust mesoporous covalent organic frameworks (COFs) via Michael addition‐elimination reaction. It is found that highly crystalline COFs can be produced in 10 min, which is attributed to the promoting effect of the intramolecular hydrogen bond activation. The COFs rich in hydroxyl groups can be facilely post‐modified by epibromohydrin to covalently immobilize enzymes with both high loading and activity. Furthermore, we create a solar‐driven photothermal‐promoted strategy by introducing photoactive azo groups to COF carriers, which can boost the enzyme catalytic performance (lipase) with much higher conversion of various racemic substrates and chiral resolution upon solar light irradiation. The heterogeneous biocatalysts also demonstrate exceptional reusability and stability. This work provides a green and energy‐efficient approach to facilitate the scale application of enzyme‐immobilized biocatalysts.

Fast Production of Covalent Organic Frameworks for Covalent Enzyme Immobilization with Boosted Enzymatic Catalysis by Solar-Driven Photothermal Effect.

Developing new enzyme-immobilization systems to stabilize their dynamic structures and meanwhile enhance their catalytic activity is of great significance but very challenging. Herein, we design and fabricate a class of robust mesoporous covalent organic frameworks (COFs) via Michael addition-elimination reaction. It is found that highly crystalline COFs can be produced in 10 min, which is attributed to the promoting effect of the intramolecular hydrogen bond activation. The COFs rich in hydroxyl groups can be facilely post-modified by epibromohydrin to covalently immobilize enzymes with both high loading and activity. Furthermore, we create a solar-driven photothermal-promoted strategy by introducing photoactive azo groups to COF carriers, which can boost the enzyme catalytic performance (lipase) with much higher conversion of various racemic substrates and chiral resolution upon solar light irradiation. The heterogeneous biocatalysts also demonstrate exceptional reusability and stability. This work provides a green and energy-efficient approach to facilitate the scale application of enzyme-immobilized biocatalysts.

Luminescent Multifunctional Nanomaterials: Capacitive Removal and Enhanced Detection Efficiency of Heavy Metals Ions for Advanced Water and Wastewater Treatment Application

AbstractIn recent years, heavy metal ions pollution in the industrialized environment of the societies threaten human health that flaunt ill‐sorted blueprints in freshwater resources obviously. The paradigm of designing luminescent multifunctional nanomaterials finds directions to the strategies of synthesizing cost‐effective, green, and versatile nanomaterials not only for detection, but also removal process of heavy metal ions in large scale applications. Among them, discovering the advances of luminescent multifunctional nanomaterials provides broad types of biomaterials, polymers and porous nanoparticles that grabs focal of investigations over the past several years due to their unique advantages such as enhanced detection efficiency with lowest limit of detection (LOD), minimum ions interference in versatile removal process, fast responsivity and selectivity as outstanding as unique physicochemical properties. This review paper tries to highlight the paradigm of principles for design, development, and utilization of luminescence nanomaterials for considering fundamental detection and removal mechanisms of heavy metal ions. In particular, these nanomaterials increase the remediation quality that are tackled in detail by focusing on opportunities and challenges in the field. Finally, design methods of these nanomaterials and concentrating on empowered detection and removal efficiency for heavy metals ions highlights novel prospective and strategies for largescale applications.

Investigation of scalable chiral metamaterial beams for combined stiffness and supplemental energy dissipation

Abstract Metamaterials have gained important interest in the research community attributable to advances in additive manufacturing enabling their fabrication at reasonable costs. The vast majority of their applications and demonstrations are at micro- and nano-scales, and challenges remained regarding the larger scale applications. In this paper, we are interested by the scalability of metamaterials, targeting structural engineering applications. To do so, we explore mechanisms capable of providing both bending stiffness and high-performance energy dissipation. Our study includes beams constructed with chiral topologies of different structural hierarchy orders, and we also explore three new topologies that we termed chiral friction, chiral-rectangular and chiral-hexagonal design to engineer the beams and the use of friction rods with tunable post-stress that inserted longitudinally through the beams to provide enhanced friction. The mechanical performance of the metamaterial beams is characterized through a series three-point bending tests. Of interest is to evaluate the bending stiffness, shape recoverability, and energy dissipation capabilities. We find that the chiral-hexagonal topology equipped with a non-stressed friction rod exhibit excellent energy dissipation capabilities, showing an improved loss factor by 11.9 times compared to the control beam using 68% of its materials density. Moreover, the use of the post-stress mechanism shows that it is possible to augment both its shape recovery and bending stiffness up to 99.3% and 47.1%, respectively. Overall, our investigation shows that it is possible to engineer scalable metamaterial beams targeting structural engineering applications, and that the use of topology optimization and strategically designed post-tensioning mechanism can allow tuning of mechanical performance.

A Facile Strategy for Freeze-Drying Preparation of Silica Aerogel from Sodium Silicate

Silica aerogels have attracted widespread attention for their distinct nanoporous networks, composed of interconnected silica nanoparticles and high-volume nanosized pores. Nonetheless, producing silica aerogels with low costs and simple processes still remains a considerable challenge. Herein, the mesoporous silica aerogels were prepared from inorganic silicon source through the freeze-drying. Using sodium silicate as the silica precursor, the gel was formed by the ion exchange and sol-gel in sequence. The regeneration of the weak acidic ion exchange resin produced the sodium acetate solution, which can be potentially used as carbon source for sewage treatment. To eliminate the collapse of microstructure of the silica hydrogel during freeze-drying, the tert-butanol aqueous solution was used as the freeze-drying medium. Particularly, the direct mixing of tert-butanol and silica sol to generate wet gel avoids prolonged and material-consuming solvent replacement. The pore structure of mesoporous silica aerogel can be adjusted by changing the concentration of tert-butanol solution. The 18 wt% tert-butanol solution results in the most favorable mesoporous structure of silica aerogel, owing to the eutectic behavior within the gel, which was verified by differential scanning calorimetry (DSC) analysis, and also due to the superior and uniform mesoporous structure of wet gel, which was validated by the cryogenic scanning electron microscopy (cryo-SEM) observation. Under optimal process conditions, the obtained silica aerogel exhibited a high porosity (97.74%) and typical mesoporous structure with the large pore volume (4.84 cm3·g-1) and an average pore diameter of 24.40 nm. The proposed cost-effective preparation strategy could elevate the potentials for large scale applications of silica aerogels in the fields of thermal insulation for building, industrial catalysis and adsorption, etc.

6.D. Skills building seminar: Family Vulnerability Scale: Why and how to use at Primary Health Care to promote health equity?

Abstract Family vulnerability encompasses multiple perspectives that are interconnected with the health needs of each family member. Families experiencing vulnerability face heightened risks of poor health outcomes. Nonetheless, these vulnerabilities are further compounded by systemic inequalities within healthcare systems, where biological or clinical factors are exclusively considered to organize and/or prioritize access, especially given the scarcity of valid instruments to measure family vulnerability. Primary Health Care (PHC) plays a pivotal role in addressing health inequalities, especially considering its bond with community. From this context, the Family Vulnerability Scale for Brazil (EVFAM-BR, in Portuguese) was developed and validated, been composed of 14 items about four dimensions (income, healthcare, family and violence) (2019-2023). By reducing the gap between science and practice, the implementation process of EVFAM-BR was started at the same year the scale was validated (2023). First, it occurred at 14 PHC services in São Paulo (Southeast Region, Brazil) and second, since 2024 has been implemented at Boa Vista (North Region, Brazil). Also, between 2024 and 2026, the implementation of EVFAM-BR is expected to take place in other Brazilian states participating in the third phase of the PlanificaSUS project, which is developed aiming to support State health departments to implement the Health Care Planning method to organize and integrate PHC and specialized outpatient care based on population health care needs. At this stage, capacity building is needed to align the concept of family vulnerability and to train PHC managers and health professionals on how to apply and use results from EVFAM-BR. This training has already been performed for around 1,000 health professionals from two different regions of Brazil, including managers, Community Health Workers, nurses, and physicians. The present workshop proposal aims to disseminate the EVFAM-BR and to offer the EVFAM-BR experience. It proposes knowledge transferring throughout participants engagement at three activities. Activity 1) “Family Vulnerability: From concept to a scale validity and application”: it is designed to engage participants to discuss about the family vulnerability concept and applicability at PHC, and to discuss on how EVFAM-BR implementation process has been occurring at Brazil and how can be tailored to other contexts. Activity 2) “Role Play: Practicing EVFAM-BR”: Two cases will be used for role play dynamics that will take place in trios, in which one will represent the community health worker, another will be the patient and the third will be the observer. Activity 3) That ones that assumed observer role will share their experiences of using EVFAM-BR. Finally, a discussion will be facilitated based on the participants’ impressions and a review of the main points covered throughout the workshop. Key messages • Family vulnerability stratification (through EVFAM-BR) is essential to plan services achieving equity and qualified population-based care management and to qualify patient approach and care. • Family Vulnerability Scale (EVFAM-BR) training represents efforts to reduce the gap between research and practice and contributes to address social determinants of health on healthcare.

Family Vulnerability: From concept to a scale validity and application

Abstract This activity will last 20 minutes. An interactive presentation will be structured at three steps. First, a debate will be facilitated to engage participants on the following questions: i. What is family vulnerability? ii. Why should we measure family vulnerability at the context of Primary Health Care (PHC)? Second, once concepts are aligned, a brief presentation about the Vulnerability Family Scale for Brazil (EVFAM-BR) will be performed. At this time, participants will have the opportunity to know about the process of development, validation and the final version of EVFAM-BR (Souza et al., 2023, available at https://doi.org/10.1371/journal.pone.0280857). Third, presenters will share step by step how EVFAM-BR can be implemented into PHC, considering two real-world experiences in Brazil, Southeast and North regions, and will discuss about possible strategies to tailor it at different cultural and geographic context, from settings with higher vulnerability and low resources to high technology settings.

A real scale application of a novel set of spatial and similarity features for detection and classification of natural seismic sources from distributed acoustic sensing data

SUMMARY Distributed acoustic sensing (DAS) turns a fibre optic into a very dense network of equally distributed seismic sensors. We focused on the high-density sampling of the seismic wavefield, expressed in strain rates, measured by DAS. Classical approaches used to identify seismic signals rely on the recorded features at one station, but it is difficult to include spatial information in case of dense seismic station networks. This work aims at introducing new spatial and similarity features for seismic event classification suitable to analyse DAS observations. We propose a processing chain based on the XGBoost algorithm and the use of specifically designed spatiotemporal and similarity features for the event classification, and Markov random field for the spatial clustering. The methodology is designated to be applied on a continuous stream of DAS observations. We tested our processing chain to detect earthquakes and quarry blasts recorded in the region by permanent seismic networks and included in the RENASS catalogue. These events are part of a strain-rate seismic survey carried out during a 3 weeks campaign of DAS measurements along à 91 km fibre optic cable deployed in the central Pyrenees mountains (France). Despite the high anthropogenic activities along the fibre optic path, the proposed method succeeded in detecting earthquakes of magnitude >0.4 and quarry blasts of magnitude >1.0 while limiting the number of false alarms. This performance is particularly noteworthy for low-magnitude events, where detection is accomplished despite a lower signal-to-noise ratio compared to traditional seismometers. The methodology opens the door to real time detection and classification of seismic events measured with long-distance fibre optic systems.

Introducing the ELPIS scale: a novel tool for measuring emotional empathy toward cancer patients.

Empathy, defined as the ability to understand and share another person's feelings, is crucial in the healthcare setting, particularly for patients with cancer who face significant psychosocial challenges. We aimed to develop a novel tool, the Empathy, Life with Cancer, and Psychosocial Skills (ELPIS) Scale that prioritizes emotional and cognitive components in order to determine the reflection of the negative stigmatization of cancer in societies on individuals, excluding the behavioral and ethical dimensions of empathy. The study was conducted using a quantitative research design with a sample of first- and second-year medical students in Türkiye. An initial pool of 48 items was developed based on an extensive review of the literature and existing empathy scales. Following expert review and pilot testing, the scale was refined to 24 items. Exploratory factor analysis and confirmatory factor analysis were conducted to establish the scale's factor structure and validate its reliability and validity. The exploratory factor analysis revealed a three-factor structure comprising "emotional empathy," "sympathetic responses," and "realistic approaches," with a total of 20 items after refinement. Confirmatory factor analysis confirmed the model fit, with the scale demonstrating high internal consistency across all three dimensions. The scale's reliability was further supported by high Cronbach's alpha values. The results suggest that the ELPIS Scale is a reliable and valid instrument for measuring emotional empathy toward cancer patients. It offers a nuanced approach by separately assessing emotional, sympathetic, and realistic components of empathy, making it a valuable tool for both educational and clinical applications. Future research should explore the scale's application in diverse populations and settings, as well as its utility in tracking empathy development over time. In conclusion, the ELPIS Scale, which focuses on the emotional and cognitive components of empathy, a multifaceted construct, fills a critical gap in the measurement of empathy in the context of cancer care and provides a comprehensive tool that can improve both patient care and the education of healthcare providers.

The added value of combining solar irradiance data and forecasts: A probabilistic benchmarking exercise

Despite the growing awareness in academia and industry of the importance of solar probabilistic forecasting for further enhancing the integration of variable photovoltaic power generation into electrical power grids, there is still no benchmark study comparing a wide range of solar probabilistic methods across various local climates. Having identified this research gap, experts involved in the activities of IEA PVPS T1611International Energy Agency - Photovoltaic Power Systems - Solar Resource for High Penetration and Large Scale Applications. agreed to establish a benchmarking exercise to evaluate the quality of intra-hour and intra-day probabilistic irradiance forecasts.The tested forecasting methodologies are based on different input data including ground measurements, satellite-based forecasts and Numerical Weather Predictions (NWP), and different statistical methods are employed to generate probabilistic forecasts from these. The exercise highlights different forecast quality depending on the method used, and more importantly, on the input data fed into the models.In particular, the benchmarking procedure reveals that the association of a point forecast that blends ground, satellite and NWP data with a statistical technique generates high-quality probabilistic forecasts. Therefore, in a subsequent step, an additional investigation was conducted to assess the added value of such a blended point forecast on forecast quality. Three new statistical methods were implemented using the blended point forecast as input.To ensure a fair evaluation of the different methods, we calculate a skill score that measures the performance of the proposed model relative to that of a trivial baseline model. The closer the skill score is to 100%, the more efficient the method is. Overall, skill scores of methods that use the blended point forecast ranges from 42% to 46% for the intra-hour scenario and 27% to 32% for the intra-day scenario. Conversely, methods that do not use the blended point forecast exhibit skill scores ranging from 33% to 43% for intra-hour forecasts and 8% to 16% for intra-day forecasts.These results suggest that using (a) blended point forecasts that optimally combine different sources of input data and (b) a post-processing with a statistical method to produce the quantile forecasts is an effective and consistent way to generate high-quality intra-hour or intra-day probabilistic forecasts.

Fusion of spectral and topographic features for land use mapping using a machine learning framework for a regional scale application.

This study investigated the dynamics of land use and land cover (LULC) modelling, mapping, and assessment in the Kegalle District ofSri Lanka, where policy decision-making is crucial in agricultural development where LULC temporal datasets are not readily available.Employing remotely sensed datasets and machine learning algorithms, the work presented here aims to compare the accuracy of three classification approaches in mapping LULC categories across the time in the study area primarily using the Google Earth Engine (GEE). Three classifiers namely random forest (RF), support vector machines (SVM), and classification and regression trees (CART) were used in LULC modelling, mapping, and change analysis. Different combinations of input features were investigated to improve classification performance. Developed models were optimised using the grid search cross-validation (CV) hyperparameter optimisation approach. It was revealed that the RF classifier constantly outstrips SVM and CART in terms of accuracy measures, highlighting its reliability in classifying the LULC. Land cover changes were examined for two periods, from 2001 to 2013 and 2013 to 2022, implying major alterations such as the conversion of rubber and coconut areas to built-up areas and barren lands. For suitable classification with higher accuracy, the study suggests utilising high spatial resolution satellite data, advanced feature selection approaches, and a combination of several spatial and spatial-temporal data sources. The study demonstrated practical applications of derived temporal LULC datasets for land management practices in agricultural development activities in developing nations.

Bioinspired synthesis of ZrO2‐Zr3Er4O12‐based mixed nanomaterial; characterization and analyzing its potential as an electrode material in energy‐based devices and its electrocatalytic property

AbstractThe sustainable and ecofriendly synthesis of transition metal oxide‐based nanomaterials has always been a matter of concern. In this study, a bioinspired synthesis route was adopted to synthesize ZrO2‐Zr3Er4O12‐based mixed nanomaterial using leaf extract of medicinal plant Amaranthus viridis as reducing and stabilizing agent in replacement of the obnoxious chemicals which are a great threat to the sustainable environment. The synthesized material revealed the spherical shaped morphology through scanning electron microscopy, whereas crystal size of 15.7 nm was observed through Xray‐diffraction, and band gap value of 2.7 eV was acquired using Tauc plot. Newly synthesized ZrO2‐Zr3Er4O12 nanocomposite was then investigated for its role as electrocatalyst in a generation of energy through the hydrogen evolution reaction and oxygen evolution reaction. The ZrO2‐Zr3Er4O12‐based electrocatalyst showed better potential for hydrogen evolution reaction measurements with the overpotential value of 242 mV. Furthermore, the notable capacitance value of 495.6 F/g was obtained through cyclic voltammetry for energy storage studies. The cyclic stability was also analyzed using linear sweep voltammetry and results showed promising stability for 2000 cycles. Consequently, the green and economical synthesis route as well as promising electrochemical behavior of ZrO2‐Zr3Er4O12‐based electrode make it feasible choice for large scale application.

Mathematical modeling and experimental analysis of the double-effect DCMD-heat pump integrated system

High energy consumption represents one of the hindrances in enabling large scale application of membrane distillation. In this work, experimental and simulation studies of a double-effect direct-contact membrane distillation integrated with a single-stage vapor-compression heat pump (DE-DCMD-HP) were carried out for concentrating tap water with the aim to evaluate the energy saving of the integrated system. It was found during our experiments that an auxiliary cooler must be added to remove the excess heat from HP to enable the integrated system to reach the steady-state condition. The temperature-heat flux plots were first utilized to analyze how HP and DE-DCMD affected each other and reveal their coupling mechanism. The simulation results showed that the increase in the first-effect feed inlet temperature, Tfi,1 and the flow rate, V caused the thermodynamic cycle line of refrigerant shift to higher temperature, which led to the increase of the input power of the compressor and the auxiliary cooler, ultimately affecting the water production mass rate, ṁd, the coefficient of performance, COP, the gain output ratio, GOR, and the specific energy consumption, SEC. The experimental and simulation results revealed that increasing Tfi,1 and V increased the permeate flux Nh and GOR and reduced the SEC. The performances for three different DCMD configurations were furthermore evaluated via experiments at constant feed temperature whereby the SEC decreased from 2168 kWh·t−1 for single-effect DCMD to 1085 kWh·t−1 for DE-DCMD to 257 kWh·t−1 for DE-DCMD-HP.

Roll‐to‐Roll Production of High‐Performance All‐Organic Polymer Nanocomposites for High‐Temperature Capacitive Energy Storage

AbstractDielectric materials with significant performance in high temperatures are highly desired, especially in harsh environments. However, the polymer‐based dielectric films have developed so far, the production scale remains at the state of the lab. Here, an all‐organic strategy is proposed by introducing phenyl‐acid‐based polymer nanodots (PAPD) into Polyetherimide (PEI), achieving high capacitive energy storage properties even at 200 °C and mass production by an industrial continuous roll‐to‐roll process. The abundant hydrogen bonding between PAPD and PEI chains ensures uniform distribution for the enhanced interaction between nanofillers and polymer matrix. Under UV irradiation, the electron‐affinity and band gap of the film are further extended, which impede charge transfer and reduction of conductive loss. A low loading (0.3 wt.%) of PAPD renders the membrane significant improvement in breakdown strength and charge–discharge efficiency. An ultrahigh energy storage density of 5.1 J cm−3 with a charge–discharge efficiency of over 90% and charge–discharge cycle stability up to 2 × 104 cycles at 150 °C is observed. Furthermore, a 1000 m long roll of polymeric film is roll‐to‐roll fabricated on an industrial solution‐casting production line and the low cost makes practical commercial scale application possible. Considering the low loading and low cost of nanofiller, this all‐organic design strategy sheds light on the industrial application of high‐temperature dielectric materials.

Advancing the Coupling of III–V Quantum Dots to Photonic Structures to Shape Their Emission Diagram

AbstractThe development of optoelectronic devices based on III–V semiconductor colloidal quantum dots (CQDs) is highly sought after due to their reduced toxicity. While devices based on conventional CQDs (II–VI semiconductors, halide perovskites) have achieved impressive technological leaps since their discovery, the most mature of these compounds contain toxic heavy metal elements (Cd, Hg, or Pb), which are highly undesirable for safe industrial scale applications. The strong covalent bonds of III–V compounds like InP, InAs, or InSb prevent the release of their toxic atoms, making them safer. However, these same bonds create severe material constraints. Namely, their harsher reaction conditions and increased sensitivity to oxidation have kept most of the research focused on material development. Meanwhile, their integration into devices and their coupling to photonic structures lag behind. Here, the integration of InAs/ZnSe core‐shell CQDs is advanced. First, the material parameters necessary to design plasmonic gratings coupled to the CQDs are elucidated and those gratings are fabricated. Angle‐resolved spectroscopy shows that the plasmon modes successfully couple to the CQD layer's emission leading to a tunable directivity with a 15° linewidth. A 3‐fold increase of the PL signal is achieved at normal incidence, thus advancing toward the goal of efficient outcoupling in LEDs.