Advanced 3D ordered electrodes for PEMFC applications: From structural features and fabrication methods to the controllable design of catalyst layers

The catalyst layers(CLs) electrode is the key component of the membrane electrode assembly(MEA) in proton exchange membrane fuel cells(PEMFCs). Conventional electrodes for PEMFCs are composed of carbon-supported, ionomer, and Pt nanoparticles, all immersed together and sprayed with a micron-level thickness of CLs. They have a performance trade-off where increasing the Pt loading leads to higher performance of abundant triple-phase boundary areas but increases the electrode cost. Major challenges must be overcome before realizing its wide commercialization. Literature research revealed that it is impossible to achieve performance and durability targets with only high-performance catalysts, so the controllable design of CLs architecture in MEAs for PEMFCs must now be the top priority to meet industry goals. From this perspective, a 3D ordered electrode circumvents this issue with a support-free architecture and ultrathin thickness while reducing noble metal Pt loadings. Herein, we discuss the motivation in-depth and summarize the necessary CLs structural features for designing ultralow Pt loading electrodes. Critical issues that remain in progress for 3D ordered CLs must be studied and characterized. Furthermore, approaches for 3D ordered CLs architecture electrode development, involving material design, structure optimization, preparation technology, and characterization techniques, are summarized and are expected to be next-generation CLs for PEMFCs. Finally, the review concludes with perspectives on possible research directions of CL architecture to address the significant challenges in the future.

Isolation of Picocyanobacteria (Order Synechococcales) and Occurrence of Cyanotoxins (Anatoxin-a) in Saline Microhabitats at Martha’s Vineyard, MA

We have used serial filtration to isolate picocyanobacteria from brackish and marine microhabitats for analysis. We used 16s metabarcoding to confirm the picocyanobacteria as members of the Order Synechococcales, Genus Cyanobium 6307 (Upper Chilmark Pond) and differing abundances of Cyanobium 6307 and Synechococcus 9902 (Chilmark Pond, Edgartown Great Pond, Tisbury Great Pond and Tashmoo Pond). The proportion and composition of (pico)cyanobacteria in water samples were influenced by the salinity concentrations at various sites, as evidenced by fluorometry and 16s metabarcoding analysis. The cyanobacterial neurotoxin anatoxin-a was present in the picocyanobacterial samples from all studied sites. Additional analyses using fluorometry and 16s metabarcoding described members of the Order Nostocales, including a halotolerant population of Dolichospermum sp., Sphaerospermopsis spp. and Nodularia spp. in Upper Chilmark Pond. We were able to establish a positive linear correlation between cyanobacterial biomass (phycocyanin) and anatoxin-a concentrations using samples taken from Upper Chilmark Pond.

Isolation of Picocyanobacteria (Order Synechococcales) and Occurrence of the Cyanotoxin Anatoxin-A in a Shallow Mesotrophic Pond

We have verified the use of a serial filtration method to isolate picocyanobacteria for analysis. We used eDNA metabarcoding to confirm the picocyanobacteria as members of the Order Synechococcales, Genus Cyanobium, specifically Cyanobium 6307. Fluorometric analysis using accessory pigments phycocyanin and phycoerythrin described periods of excess biomass, where the net growth rate model confirmed these conditions. The total anatoxin-a concentrations in the picocyanobacterial sample ranged from 0.0074 - 6.41 μg·L-1 representing a 40-fold difference over the entire sampling season. Sampling frequency of every three days appeared to be an important factor in capturing these changes in anatoxin-a concentration. During a period of excess biomass, we were able to establish a linear correlation between cyanobacterial biomass and Anatoxin-a concentrations.

Electrocatalytic CO_(2)reduction to syngas

While carbon dioxide(CO_(2))is a major greenhouse gas,it is also an important C1 resource.In the trend of energy conservation and emission reduction,electrocatalytic reduction has become a very promising strategy for CO_(2)utilization because it can convert CO_(2)directly to high-valued chemicals and fuels under mild conditions.In particular,the product CO and by-product H_(2)can be combined into syngas by an electrocatalytic CO_(2)reduction reaction(CO_(2)RR)in an aqueous medium.Different molar ratios of CO and H_(2)may be used to produce essential bulk chemicals or liquid fuels such as methanol,alkanes,and olefins through thermochemical catalysis,Fischer-Tropsch synthesis,microbial fermentation,and other techniques.This work discusses the latest strategies in controlling the molar ratio of CO/H_(2)and improving the yield of CO_(2)RR-to-syngas.The challenges of electrocatalytic syngas production are analyzed from an industrial application perspective,and the possible measures to overcome them are proposed in terms of new catalyst design,electrolyte innovation,flow reactor optimization,anodic reaction coupling,and operando technique application.

Changes in human hepatic metabolism in steatosis and cirrhosis

AIMTo understand the underlying metabolic changes in human liver disease we have applied nuclear magnetic resonance (NMR) metabolomics analysis to human liver tissue.METHODSWe have carried out pilot study using 1H-NMR to derive metabolomic signatures from human liver from patients with steatosis, nonalcoholic steatohepatitis (NASH) or alcohol-related liver damage (ARLD) to identify species that can predict outcome and discriminate between alcohol and metabolic-induced liver injuries.RESULTSChanges in branched chain amino acid homeostasis, tricarboxylic acid cycle and purine biosynthesis intermediates along with betaine were associated with the development of cirrhosis in both ARLD and nonalcoholic fatty liver disease. Species such as propylene glycol and as yet unidentified moieties that allowed discrimination between NASH and ARLD samples were also detected using our approach.CONCLUSIONOur high throughput, non-destructive technique for multiple analyte quantification in human liver specimens has potential for identification of biomarkers with prognostic and diagnostic significance.

Introduction to the special issue on polarization of light in biomedical applications

Although birefringence was discovered just three years after white light was separated into different colors,polarimetry has lagged behind spectroscopy in characterizing diverse materials,likely due to our naked eyes'limited sensitivity to polarizations.Recent advancements in light sources,polarization optics,detectors,displays,data processing,and feature extraction techniques are rapidly propelling polarimetry as a convenient and potent tool for probing the distinct properties of complex and turbid materials.It is well known now that polarization properties of a material encode rich information on its distinct features,including not only the bulk optical properties related with dispersions and absorptions,but also distribution and microstructural properties of the scattering particles in turbid media such as the size,shape,orientation and alignment,surface morphology and internal structure,etc.All these features can be used for differentiating different materials,sensing ambient environment around scatterers,or monitoring dynamic processes in complex systems.

A Novel Deep Model with Meta-Learning for Rolling Bearing Few-Shot Fault Diagnosis

Machine learning,especially deep learning,has been highly successful in data-intensive applications;however,the performance of these models will drop significantly when the amount of the training data amount does not meet the requirement.This leads to the so-called few-shot learning(FSL)problem,which requires the model rapidly generalize to new tasks that containing only a few labeled samples.In this paper,we proposed a new deep model,called deep convolutional meta-learning networks,to address the low performance of generalization under limited data for bearing fault diagnosis.The essential of our approach is to learn a base model from the multiple learning tasks using a support dataset and finetune the learnt parameters using few-shot tasks before it can adapt to the new learning task based on limited training data.The proposed method was compared to several FSL methods,including methods with and without pre-training the embedding mapping,and methods with finetuning the classifier or the whole model by utilizing the few-shot data from the target domain.The comparisons are carried out on 1-shot and 10-shot tasks using the Case Western Reserve University bearing dataset and a cylindrical roller bearing dataset.The experimental result illustrates that our method has good performance on the bearing fault diagnosis across various few-shot conditions.In addition,we found that the pretraining process does not always improve the prediction accuracy.

Hydrogen Production Performances via Steam Reforming over Hydrotalcite Derived Catalyst: A Sustainable Energy Production Review

The review outcome represents the optimum catalytic conditions for the production of hydrogen using hydrotalcite derived catalysts. It covers dry and steam reforming of methane, steam reforming of methanol and ethanol to hydrogen. The review also revealed the specific properties of hydrotalcite derived catalysts for the reactions. Among catalyst investigated, Ni & Fe promoted Al-Mg containing hydrotalcite catalyst perform best (99%) for dry reforming of methane at 250°C. For steam methane reforming, Ni containing ca-aluminates hydrotalcite catalyst act as the best (99%) at 550°C. Cu-supported Zn-Al-containing catalyst performs the best (99.98%) for steam reforming of methanol at 300°C whereas Cu impregnated Mg-Al containing hydrotalcite is the best (99%) for steam reforming of ethanol at 200°C - 600°C. It’s (HT) tunable and versatile textural and morphological properties showed excellent catalytic performances for different industrial processes and in sustainable hydrogen production.

Prime Mover Capacity Optimization and Thermodynamic Performance Analysis of Internal Combustion Engine Based CCHP System

In this research,a solar hybrid combined cooling heating and power(CCHP)system is proposed considering the different scenarios of Prime Movers(PMs)and the part-load performance of PMs is validated by the designed values from the manufacturer of Volvo.Moreover,a multi-optimization model based on a genetic algorithm is developed in order to select both the most promising performance PM and the most cost-effectiveness,environmentally friendly number of collectors for the proposed CCHP system,simultaneously.Then the hourly performance of this solar hybrid CCHP is determined through a case study of a hotel in Shanghai.Results show that the highest efficiency of the PM with larger capacity has the most promising performance and the collector number of 90 turns out to be a superior value for the hotel building based on the primary energy saving ratio of 61.61%.Moreover,on a typical summer day,the recovered waste heat and the solar energy can provide all the thermal energy demands,while,an auxiliary boiler should be started to fulfill the energy gap in both typical transition and winter days.From the simulation result,the CO_(2) emissions can be reduced by 856.2 t/a due to the solar energy introduced into the system.Besides,the dynamic investment payback period will change from 3.01 years to 3.56 years when the fuel price(P_(fuel))ranges from 0.8P_(fuel) to1.2P_(fuel).

Nanocellulose-based porous materials: Regulation and pathway to commercialization in regenerative medicine

We review the recent progress that have led to the development of porous materials based on cellulose nanostructures found in plants and other resources. In light of the properties that emerge from the chemistry, shape and structural control, we discuss some of the most promising uses of a plant-based material, nanocellulose, in regenerative medicine. Following a brief discussion about the fundamental aspects of self-assembly of nanocellulose precursors, we review the key strategies needed for material synthesis and to adjust the architecture of the materials (using three-dimensional printing, freeze-casted porous materials, and electrospinning) according to their uses in tissue engineering, artificial organs, controlled drug delivery and wound healing systems, among others. For this purpose, we map the structure-property-function relationships of nanocellulose-based porous materials and examine the course of actions that are required to translate innovation from the laboratory to industry. Such efforts require attention to regulatory aspects and market pull. Finally, the key challenges and opportunities in this nascent field are critically reviewed.

Phase preservation of orbital angular momentum of light in multiple scattering environment

Recent advancements in wavefront shaping techniques have facilitated the study of complex structured light’s propagation with orbital angular momentum(OAM)within various media.The introduction of spiral phase modulation to the Laguerre–Gaussian(LG)beam during its paraxial propagation is facilitated by the negative gradient of the medium’s refractive index change over time,leading to a notable increase in the rate of phase twist,effectively observed as phase retardation of the OAM.This approach attains remarkable sensitivity to even the slightest variations in the medium’s refractive index(∼10−6).The phase memory of OAM is revealed as the ability of twisted light to preserve the initial helical phase even propagating through the turbid tissue-like multiple scattering medium.The results confirm fascinating opportunities for exploiting OAM light in biomedical applications,e.g.such as non-invasive trans-cutaneous glucose diagnosis and optical communication through biological tissues and other optically dense media.

Potassium isotopes trace the formation of juvenile continental crust

Constraining the processes associated with the formation of new(juvenile)continental crust from mantle-derived(basaltic)sources is key to understanding the origin and evolution of Earth’s landmasses.Here we present high-precision measurements of stable isotopes of potassium(K)from Earth’s most voluminous plagiogranites,exposed near El-Shadli in the Eastern Desert of Egypt.These plagiogranites exhibit a wide range of d41K values(–0.31‰±0.06‰to 0.36‰±0.05‰;2 SE,standard error)that are significantly higher(isotopically heavier)than mantle values(–0.42‰±0.08‰).Isotopic(87Sr/86Sr and^(143)Nd/^(144)Nd)and trace element data indicate that the large variation in d41K was inherited from the basaltic source rocks of the El-Shadli plagiogranites,consistent with an origin through partial melting of hydrothermally-altered mid-to-lower oceanic crust.These data demonstrate that K isotopes have the potential to better constrain the source of granitoid rocks and thus the secular evolution of the continental crust.

Resource and waste quantification scenarios for wind turbine decommissioning in the United Kingdom

Wind power produces more electricity than any other form of renewable energy in the United Kingdom(UK)and plays a key role in decarbonisation of the grid.Although wind energy is seen as a sustainable alternative to fossil fuels,there are still several environmental impacts associated with all stages of the lifecycle of a wind farm.This study determined the material composition for wind turbines for various sizes and designs and the prevalence of such turbines over time,to accurately quantify waste generation following wind turbine decommissioning in the UK.The end of life stage is becoming increasingly important as a rapid rise in installation rates suggests an equally rapid rise in decommissioning rates can be expected as wind turbines reach the end of their 20-25-year operational lifetime.Waste data analytics were applied in this study for the UK in 5-year intervals,stemming from 2000 to 2039.Current practices for end of life waste management procedures have been analysed to create baseline scenarios.These scenarios have been used to explore potential waste management mitigation options for various materials and components such as reuse,remanufacture,recycling,and heat recovery from incineration.Six scenarios were then developed based on these waste management options,which have demonstrated the significant environmental benefits of such practices through quantification of waste reduction and greenhouse gas(GHG)emissions savings.For the 2015-2019 time period,over 35 kilotonnes of waste are expected to be generated annually.Overall waste is expected to increase over time to more than 1200 kilotonnes annually by 2039.Concrete is expected to account for the majority of waste associated with wind turbine decommissioning initially due to foundations for onshore turbines accounting for approximately 80%of their total weight.By 2035-2039,steel waste is expected to account for almost 50%of overall waste due to the emergence of offshore turbines,the foundations of which are predominantly made of steel.

High-resolution two-photon polymerization:the most versatile technique for the fabrication of microneedle arrays

Microneedle patches have received much interest in the last two decades as drug/vaccine delivery or fluid sampling systems for diagnostic and monitoring purposes.Microneedles are manufactured using a variety of additive and subtractive micromanufacturing techniques.In the last decade,much attention has been paid to using additive manufacturing techniques in both research and industry,such as 3D printing,fused deposition modeling,inkjet printing,and two-photon polymerization(2PP),with 2PP being the most flexible method for the fabrication of microneedle arrays.2PP is one of the most versatile and precise additive manufacturing processes,which enables the fabrication of arbitrary three-dimensional(3D)prototypes directly from computer-aided-design(CAD)models with a resolution down to 100 nm.Due to its unprecedented flexibility and high spatial resolution,the use of this technology has been widespread for the fabrication of bio-microdevices and bio-nanodevices such as microneedles and microfluidic devices.This is a pioneering transformative technology that facilitates the fabrication of complex miniaturized structures that cannot be fabricated with established multistep manufacturing methods such as injection molding,photolithography,and etching.Thus,microstructures are designed according to structural and fluid dynamics considerations rather than the manufacturing constraints imposed by methods such as machining or etching processes.This article presents the fundamentals of 2PP and the recent development of microneedle array fabrication through 2PP as a precise and unique method for the manufacture of microstructures,which may overcome the shortcomings of conventional manufacturing processes.

Redefining pandemic preparedness:Multidisciplinary insights from the CERP modelling workshop in infectious diseases,workshop report

In July 2023,the Center of Excellence in Respiratory Pathogens organized a two-day workshop on infectious diseases modelling and the lessons learnt from the Covid-19 pandemic.This report summarizes the rich discussions that occurred during the workshop.The workshop participants discussed multisource data integration and highlighted the benefits of combining traditional surveillance with more novel data sources like mobility data,social media,and wastewater monitoring.Significant advancements were noted in the development of predictive models,with examples from various countries showcasing the use of machine learning and artificial intelligence in detecting and monitoring disease trends.The role of open collaboration between various stakeholders in modelling was stressed,advocating for the continuation of such partnerships beyond the pandemic.A major gap identified was the absence of a common international framework for data sharing,which is crucial for global pandemic preparedness.Overall,the workshop underscored the need for robust,adaptable modelling frameworks and the integration of different data sources and collaboration across sectors,as key elements in enhancing future pandemic response and preparedness.

Temperature‑Regulating Phase Change Fiber Scaffold Toward Mild Photothermal–Chemotherapy

Photothermal therapy(PTT)is a treatment that increases the temperature of tumors to 42–48℃,or even higher for tumor ablation.PTT has sparked a lot of attention due to its ability to induce apoptosis or increase sensitivity to chemotherapy.Excessive heat not only kills the tumor cells,but also damages the surrounding healthy tissue,reducing therapeutic accuracy and increasing the possible side effects.Herein,a phase change fiber(PCF)scaffold serving as a thermal trigger in mild photothermal–chemo tumor therapy is developed to regulate temperature and control drug release.These prepared PCFs,comprised of hollow carbon fibers(HCFs)loaded with lauric acid as a phase change material(PCM),can effectively store and release any excess heat generated by irradiating with a near-infrared(NIR)laser through the reversible solid–liquid transition process of the PCM.With this feature,the optimal PTT temperature of implanted PCF-based composite scaffolds was identified for tumor therapy with minimal normal tissue damage.In addition,controlled release of chemotherapeutic drugs and heat shock protein(HSP)inhibitors from the PCF-based composite scaffolds have been shown to improve the efficacy of mild PTT.The developed PCF-based scaffold sheds light on the development of a new generation of therapeutic scaffolds for thermal therapy.

Multi-scale nature of non-blade-order propagating flow disturbances in axial compressors

Non-blade-order flow disturbances, also referred to as pre-stall disturbances or tip flow unsteadiness, are closely related with compressor instabilities. The present work provides a comprehensive investigation on multi-scale nature of non-blade-order disturbances and the underlying flow physics in axial compressors. By applying full-annulus Unsteady Reynolds-Averaged Navier-Stokes(URANS) simulations, along with space–time correlation and spatial Fourier decomposition, to the disturbed pressure, the propagating feature of the non-blade-order disturbances is obtained. Further, a bridge between non-blade-order disturbances and the evolution of unsteady vortex has been set up. The results show that non-blade-order disturbances, featured as short-length-scale(35 modes across annulus), first appear as the occurrence of tip leakage vortex fluctuation, while the compressor still operates far from stall. Leading-edge radial vortex appears at near stall condition, and its movement induces a circumferential propagating disturbance overlaying on the one induced by oscillating tip leakage vortex. The interaction of the short-scale disturbances with a lowamplitude long-scale(of circumference) disturbance is observed, which results in disturbances with multiple scales of consecutive spatial modes, along with multiple frequency peaks in spectra. The compressor falls into stall as the circumferential nonuniform scattering of the leading-edge vortexes occurs. The densely-and sparsely-scattered leading-edge radial vortexes induce a high-amplitude long-scale(of circumference) disturbance , i.e. stall disturbance.