Particle Concentration Research Articles

Versatile and Remotely Controllable Light-Induced Coagulation of Particles Under Flow in a 2D Channel.

On-demand switch on/off blood clogging is of paramount importance for the survival of mammals, for example as a quick response to seal damage wounds to minimize their bleeding rate. This mechanism is a complex chain process from initiated red blood cell aggregation at the target location (open wound) that quickly seals on a macroscopic scale the damaged flash. Inspired by nature an on-demand switchable particle clogging mechanism is developed with high spatial resolution down to micrometer size using light as an external non-invasive stimulation. Particle clogging can be adjusted on demand strong enough to even withstand pressure-driven fluid flow, additionally building up walls of aggregated particles, which stop the momentum of big particles under shear. The principle relies on a photosensitive surfactant, which induces under light illumination a long-ranged lateral attractive phoretic-osmotic activity of silica microparticles forcing them to aggregate. The strength of aggregation and therefore motion reduction or even stop of the particles against the fluid flow depends on the ratio between the aggregation strength and the velocity of the particles. The aggregation strength can be precisely controlled by the applied light intensity and adjusted particle concentration. Increasing both parameters results in a stronger aggregation tendency.

Prediction model for vertical distribution of oil particles under thermal plume and displacement ventilation in a machining workshop

Oil particle concentrations exhibit an inhomogeneous distribution in large-space machining workshops with a displacement ventilation system. The inhomogeneous distribution can lead to variations in the required supply air volume used to control the indoor particle concentration at different heights. To rapidly calculate the particle concentration distribution in the vertical direction, this study established a zonal particle concentration prediction model based on the mass and energy balance by considering the interaction between the heat source thermal plume, wall thermal plume, and supply airflow. An experiment was conducted in a scaled chamber to validate the proposed prediction model. The result showed that the relative error between the prediction model and experiment ranged from −17% to 10%. A case study was performed to demonstrate the applicability of the prediction model to the control of a displacement ventilation system. Using the prediction model, the control system can maintain the particle concentration in the work area below 0.5 mg/m³with variable particle source emission rates and reduce the supply air volume by at least 24% and 55% compared with the variable and constant air volume systems, respectively, neither of which can address the inhomogeneous distribution of oil particle concentration. The prediction model can also be used for the design of displacement ventilation systems when the inhomogeneous particle concentration distribution is considerable.

Effect of Particle Concentration on the Microstructure and Properties of Electrodeposited Nickel–Diamond Composite Coatings

For the purpose of improving the wear properties of Ni composite coatings, diamond particles were co-electrodeposited into Ni–diamond composite coatings. The effect of diamond particle concentration in the electrolyte on the surface morphology, microstructure, and wear properties of Ni–diamond composite coatings was investigated. The electrodeposition behaviors of the composite coatings were simulated by COMSOL5.6. The results showed that the content of diamond particles in the coating was elevated by increasing the particle concentration in the electrolyte. The formation of [200] fiber texture was blocked and concurrently brought about crystallite refinement of the Ni deposits by the embedded particles. The COMSOL simulation findings indicated that embedded particles influenced the microstructure of the Ni deposits through processes such as heterogeneous nucleation, rearrangement, and concentration of local current density. The synergistic effect of the tailored microstructure and embedded particles substantially enhanced the wear resistance of the coating. By increasing the particle concentration in the electrolyte, the wear resistance of the coating was gradually enhanced, and the coating electrodeposited at 16 g/L possessed the lowest friction coefficient and the smallest profile of wear scratch owning to the strengthened synergistic effect.

Investigation of Copper Codeposits with SiC Nano from Ionic Liquid (Ethaline) as Function of Concentration and Micro Particles Sizes where the Working Electrode in ‘Vertical’ Position Using Acoustic Impedance Electrochemical Quartz Crystal Microbalance (EQCM)

The gravimetric inspection of co-electrodeposited copper, with hard inert second phase ceramics SiC and 0.02 M [CuCl2.2H2O] in 1 ChCl: 2 EG, based liquid for different solution-phase loadings of 1-3 \(\mu\)m silicon carbide unpolished gold AT cut working electrode placed in’Vertical’ position, revealed that the EQCM method admits the first in-situ quantification or particulate inclusion.  It was found that the composition of incorporated substance was fairly dependant on the concentration of second phase particles in solution, where in this study the 5% SiC has the amount in the copper which is in a good agreement with alumina particles with the same size.  Another observation was that most of the material was drawn onto the surface rather than settling on to it, however the distribution of the hard phase was found to be reasonably even throughout the coating.  This technology is important because it assists deposition of bright copper coatings without adding hazard materials, such as cyanide. On the other hand the comparison between concentrations of  0.02 M  and 0.2 M [CuCl2.2H2O] in 1 ChCl: 2 EG based liquid for 10% solution-phase loadings of 45-55 nm size silicon carbide was also investigated, where the working electrode is placed in’Horizontal’  postion. It is very interisting that the experimental result showed that the mass loaded by 0.2 M solution is about 10 times greater than for the mass loaded by 0.02 M solution.

Rain-Based Train Washing: A Sustainable Approach to Reduce PM Concentrations in Underground Environments

Fine particle concentrations measured in many underground rail systems around the world consistently exceed those observed at ground level, potentially posing significant implications for human health. While numerous authors have observed these high particle concentrations and analyzed both their atomic compositions and health impacts, few have investigated devices and technologies capable of reducing these high levels in underground environments. In light of these considerations and recognizing the multifaceted challenges associated with maintaining air quality in underground metro systems, the aim of this paper was to evaluate the usefulness and effectiveness of utilizing rainwater for washing trains to abate particulate matter (PM) concentrations in underground rail systems. To achieve this aim, an ad hoc case study was considered: the Naples Metro Line 1 (Italy), which is characterized by 4.5 km in the ground level and 13.5 km underground. A measurement campaign was carried out during storms of strong intensity through PM measuring instruments placed on station platforms along the metro line. Precisely, the trains were washed by the rain in the initial ground level section, and then continued wet within the underground one. The results of this measurement campaign were compared with those of a comparable survey carried out during average clear weather conditions, and the results showed that the train washing produces a significant PM10 concentration reduction of up to about 60% in the underground environment. If confirmed in other experimental settings, these results could lay the groundwork for the introduction of structured washing system devices (e.g., periodically washing trains and/or tunnels) for the reduction of PM concentration in underground metro systems. The present study sought to contribute valuable insights towards sustainable and environmentally conscious approaches to addressing air quality concerns, particularly by harnessing the natural resource of rainwater during specific meteorological events.

Experimental study of the effect of particle–wall interactions on inertial particle dynamics in wall turbulence

Based on Voronoi analysis, the properties related to the near-wall motion of particles in a turbulent boundary layer were experimentally investigated via different release modes, with a friction Reynolds number $Re_\tau =3530$ . For high-inertia sand particles with Stokes number $St^+ \sim O(10^2\unicode{x2013}10^3)$ and a volume fraction $\varPhi _v \sim O(10^{-4})$ , particle image tracking velocimetry was used to determine the particle position and near-wall distribution properties. We established three particle release modes, including top-released, bottom overall-released and bottom partially released sand particles, under the same flow field conditions and calculated the differences in particle near-wall clustering and void properties. It was confirmed that wall effects (including collision and strike-splash) have a great influence on particle clustering and void behaviour near the wall. In the top-released sand particle and locally laid sand particle cases, particles bounced off the smooth walls and re-entered the carrier flow, causing significant clustering and sparsing of particles near the walls. In contrast, in the overall sand-laying case where the bottom wall was completely covered with sand particles, there is no apparent cluster or void phenomenon near the wall $(z/\delta <0.12)$ and the particles are randomly distributed, due to the combined effect of particle impact and splashing. In addition, the clustering and voids of particles become more pronounced with increasing wall-normal distance in the three release modes, and the particle distribution shows some self-similarity at each flow layer. The probability density function of the concentration of cluster particles decreases following a ‘ $-5/3$ ’ power law. However, due to the particle–wall interaction, the probability density function gradually deviates from the ‘ $-5/3$ ’ power law.

A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations

Abstract. The effective radiative forcing (ERF) due to aerosol–cloud interactions (ACIs) and rapid adjustments (ERFaci) still causes the largest uncertainty in the assessment of climate change. It is understood only with medium confidence and is studied primarily for warm clouds. Here, we present a novel cloud-by-cloud (C×C) approach for studying ACI in satellite observations that combines the concentration of cloud condensation nuclei (nCCN) and ice nucleating particles (nINP) from polar-orbiting lidar measurements with the development of the properties of individual clouds by tracking them in geostationary observations. We present a step-by-step description for obtaining matched aerosol–cloud cases. The application to satellite observations over central Europe and northern Africa during 2014, together with rigorous quality assurance, leads to 399 liquid-only clouds and 95 ice-containing clouds that can be matched to surrounding nCCN and nINP respectively at cloud level. We use this initial data set for assessing the impact of changes in cloud-relevant aerosol concentrations on the cloud droplet number concentration (Nd) and effective radius (reff) of liquid clouds and the phase of clouds in the regime of heterogeneous ice formation. We find a Δln⁡Nd/Δln⁡nCCN of 0.13 to 0.30, which is at the lower end of commonly inferred values of 0.3 to 0.8. The Δln⁡reff/Δln⁡nCCN between −0.09 and −0.21 suggests that reff decreases by −0.81 to −3.78 nm per increase in nCCN of 1 cm−3. We also find a tendency towards more cloud ice and more fully glaciated clouds with increasing nINP that cannot be explained by the increasingly lower cloud top temperature of supercooled-liquid, mixed-phase, and fully glaciated clouds alone. Applied to a larger number of observations, the C×C approach has the potential to enable the systematic investigation of warm and cold clouds. This marks a step change in the quantification of ERFaci from space.

Optimization of magnetoactive polymer membranes using radial magnetization

Magnetoactive polymer membranes (MAPMs) are manufactured by synthesizing magnetic powders and silicon. Owing to the unique combination of their magnetic and elastic properties, MAPMs have attracted considerable interest as actuators for applications such as soft robotics and medical drug pumps. However, the real-world applications of MAPMs are limited by complicated magnetization processes and their inability to generate large actuation forces. Herein, we propose a radially magnetized MAPM and a magnetization process that eliminates repetitive folding, resulting in elaborate and uniformly magnetized MAPMs without any additional processes. We optimized the membrane thickness and concentration of the magnetic particles by considering the trade-off between actuation performance and controllability. Moreover, we optimized the membrane thickness and concentration of the magnetic powders by analyzing their actuation performance using custom-made pump system. We also quantified the performance of the pump by evaluating its flow rate and precision. Our results show that the maximum outlet pressure of radially-magnetized MAPMs was higher than those of MAPMs manufactured using conventional vertical magnetization by more than 5.5 times. Overall, this study presents a promising candidate for driving miniaturized pump systems and demonstrates the potential of MAPMs as versatile actuators.

ДИСПЕРСТІ ОРТАЛАРДЫҢ ОПТИКАЛЫҚ ҚАСИЕТТЕРІ

The aim of the study is to study light scattering, one of the optical properties of dispersed media. A number of optical methods for determining the size, shape and concentration of colloidal particles and macromolecules are based on the Tyndall effect. A ray of light passing through a colloidal solution is visible as a result of scattering, this type of scattering is called opalescence. Scientific discovery new data on optical effects occurring on magnetic colloids under the influence of magnetic and hydrodynamic fields have been obtained. To create neutral light filters controlled by a magnetic field, it is possible to use established diffraction scattering models with a small angle. The article defines the correspondence and errors of the J.W. Rayleigh or Clausius equations of light scattering intensity for a collide sulfur solution obtained experimentally to solve the problem.

Microplastic concentrations and risk assessment in water, sediment and invertebrates from Simon's Town, South Africa

Plastic pollution is an ever-increasing threat globally and poor waste management in South Africa has caused an increase in plastic leakage into the environment. Plastic waste in the environment are categorized according to size and plastic particles smaller than 5 mm in size are regarded as microplastics (MPs), and little to no research has been done on MPs pollution within the marine coastal environment and rocky shores in South Africa. Sampling was done in February 2020 at a rocky shore within Simon's Town Marina, Cape Town. MPs were extracted from collected water (n = 5), sediment (n = 5) and biota (n ≤ 30) samples. The extracted MPs were further classified based on shape, colour, size and an attenuated total reflectance Fourier-transform infrared (ATR-FTIR) instrument was utilized for polymer type identification The risks posed by MPs because of concentration at which they occurred and chemical composition were assessed in all the sample types. As expected, MPs were higher in sediment (38 ± 2 MP/kg) than in water (0.37 ± 0.06 MP/L) as the area has low water energy, allowing MP particles to settle within the sediment. Filter-feeding organisms had the lowest average MP particle concentrations (0.28 ± 0.04 MP/g) but displayed the highest variation of MP particle colours due to the non-selective feeding strategy, where other feeding strategies ingested mostly black/grey particles. The dominant MP size was between 100 μm and 500 μm in size for all samples combined, with the most abundant MP polymer type being nylon (27.27 %), polyethylene terephthalate (PET) (18.18 %) and natural MP particles such as cotton (18.18 %). The risk assessment indicated that polymer type poses a greater risk of MP pollution than MP concentrations.

Particles influence on the direct absorption spectroscopy of TDLAS

Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology is widely used for monitoring the gas pollutants. But in actual measurement environments, there are usually particles, which will affect the TDLAS direct absorption spectroscopy. In this paper, the influence of particles on the direct absorption spectroscopy of TDLAS was analyzed by using TDLAS-DAS technology combined with particle extinction method. According to analysis, it was found that the presence of particles does not affect the gas characteristic absorption spectral line strength and the gas absorption spectroscopy broadening, but it does affect the output laser intensity and absorbance received by the detector. The transmittance of particles can be obtained through the slope of the output laser intensity, which can be used to correct the absorbance to achieve accurate measurement of gas concentration. This paper analyzed the effects of particle size, incident wavelength, and composition on particle extinction coefficient and obtained the extinction coefficient of soot. If the laser wavelength is 1.53 μm and the particle size of soot is 45 μm, the extinction coefficient of soot is 2.1016. The magnitude of laser intensity attenuation at different particle concentrations can be obtained based on the extinction coefficient of particulate matter. When the concentration of soot is greater than 26290 mg/m3 and the optical path is 100 cm, the transmittance is less than 0.1 and the laser intensity attenuation reach over 90 %, which may affect the detection of gas absorption spectroscopy information and the accuracy of measurement. On this basis, this paper established the relationship between gas concentration and corrected absorbance to invert the gas concentration in the presence of particulate matter when the concentration of soot is less than 26290 mg/m3. The inversion gas concentration error obtained by the absorbance peak calibration method is within 3 %, and the inversion gas concentration error obtained by the absorbance integration method is within 1 %. From the inversion results, it can be seen that the accurate measurement of gas concentration in the presence of particulate matter can be achieved by extracting the slope of the output laser intensity to correct absorbance.

Mechanism of enhanced microfine low-rank coal flotation by jet slurry conditioning

ABSTRACT Microfine low-rank coals are subject to metamorphic changes that hinder their floatability, impeding their clean and efficient utilization. The objective of this study was to refine the jet-slurry technique to enhance the floatability of microfine low-rank coals. Furthermore, advanced methods including Focused beam reflectance measurement (FBRM), high-sensitivity microelectromechanical balancer (DCAT), Fourier transform infrared spectrometer (FTIR), and scanning electron microscope (SEM) were employed to dissect the physicochemical effects of jet slurring on microfine low-rank coal particles. The study found that as the concentration of microfine coal particles increased, surface reagent adsorption initially rose and then fell with greater feed volumes. In contrast, adhesion forces displayed an inverse trend. Optimal results were achieved with a feed volume set at 25 L/min. This phenomenon is attributable to multiple regulatory factors. Within certain limits, intensifying conditioning promotes particle agglomeration, curtails fine gangue mineral coverage, boosts sodium dodecyl sulfate (SDS) adsorption, diminishes microfine coal wettability, and better kerosene-coal particle mixing. However, at excessive jet speeds (30 L/min), substantial physical pressure variances and mechanical dispersion forces arise, undermining SDS or kerosene’s chemical adsorption to coal or modified coal, thus reducing reagent attachment. The aforementioned study demonstrates that within certain parameters, jet slurring significantly betters coal-gangue separation, thereby amplifying the flotation efficacy of microfine low-rank coals. This research offers strategic insights into microfine low-rank coal flotation processes and lays a theoretical groundwork for the selection of suitable techniques and reagents.

Artificial neural network approach to simulate the impact of concentration in optimizing heat transfer rate on water-based hybrid nanofluid under slip conditions: A regression analysis

The recent era of science depends upon the efficient performance of the heat transfer rate in several engineering applications for which the role of nanofluids have a greater impact. Therefore, the impact of particle concentration in optimizing heat transfer analysis of water-based hybrid nanofluid is conducted via an artificial neural network. The combined effect of oxide nanoparticles such as MgO and TiO2 in water performs their effective role with various factors involved in the flow phenomena. The magnetized hybrid nanofluid flow over an expanding surface filled with porous material shows its noble behavior on the flow properties. Further, it is not usual to omit the effectiveness of the dissipative heat impact. Therefore, the role of viscous, Joule, and Darcy dissipation is incorporated in the energy profile for which the profiles became coupled. The designed nonlinear model invokes suitable similarity rules that give rise to a system of nonlinear ordinary equations in non-dimensional form. Afterwards, the traditional numerical approach is beneficial to conduct the simulation of the flow profiles. The optimization of the heat transfer rate analysis is obtained by the implementation of an artificial neural network (ANN) for the response of Nusselt number using various factors. The regression analysis for the embedding data shows the effectiveness of the proposed approach in this discussion. The proposed study describes the important outcomes as; an increasing slip produces a thinning in the bounding surface thickness for the case of pure fluid comparing to the nanofluid and hybrid nanofluid. Further, the data set used for the hybrid nanofluid shows an efficient fitting than the case of nanofluid.

Effect of particles on foam drainage

Despite many applications, the three phase foam is so complicated and far from being fully understood. Drainage is critical to foam decay, so the effect of particles on foam drainage has been investigated in this research to better understand the complex three phase foam. The power law relationship, drainage regime, foam permeability and the residual solid particles were investigated with different particle concentration, particle hydrophobicity and particle size. It was found that the power law index increased with the increasing of particle concentration and particle hydrophobicity, which indicates the transition of drainage regime from node dominated to Plateau border dominated. It was also found that the medium size particles could increase the Plateau border viscous loss more obviously. Foam permeability with different particles was also discussed via fitting the viscous loss of both Plateau border and nodes. Finally, residual solid particle was used to study the particle behaviour during the free drainage after forced drainage. This research could help us better understand the drainage of three phase foam.

Identification and quantification of microplastics in salts by complementary approaches using pyrolysis-gas chromatography/quadrupole-time of flight mass spectrometry (Py-GC/QTOFMS) and laser direct infrared (LDIR) chemical imaging analysis

Microplastics (MPs) and nanoplastics (NPs) have been suspected as contaminants in various foodstuffs, including salts, all over the world. Regarding the different sizes and polymer types, the mass concentrations of actual plastic particles in salt are not very clear. The purpose of this study is to develop a scalable method for qualitative and quantitative analysis of MPs and NPs by using Pyrolysis Gas Chromatography Quadrupole-Time of Flight mass spectrometry (Py-GC/QTOFMS) to detect their mass concentrations in salt samples. The targeted and suspected lists of polymers in salts were compiled based on the combined results of the high-resolution mass spectrometry (HRMS) full scanning with auxiliary MS dataset and the laser direct infrared (LDIR) chemical imaging analysis. The seven targeted MPs with polymer standards, i.e., polyvinyl chloride (PVC), polymethyl methacrylate (PMMA), polypropylene (PP), polystyrene (PS), polyethylene (PE), polyethylene terephthalate (PET), and polycarbonate (PC), were first subjected to a full MS scanning mode of the Py-GC/QTOFMS analysis. Subsequently, the parental masses of their pyrolysis compounds were used as the seeds to generate the related daughter masses. This process established both retention time and mass-pairs matching for the target MS/MS mode for enabling the identification and quantification of the particles. The suspected MPs with a matching degree >0.65 in the LDIR list were explored either by the full scan MS. Only PVC was identified, and PET was suspected. The Py-GC/QTOFMS result is complementary and comparable to the LDIR detection with the matching degree >0.85. We identified that PVC and PET (suspected) can be measured in both commercial and bulk sea salts, and their concentrations in sea salts are much higher than in rock salts, implying heavy contamination of the seawater.

Nonthermal plasma air disinfection for the inactivation of airborne microorganisms in an experimental chamber and indoor air.

Airborne transmission of diseases presents a serious threat to human health, so effective air disinfection technology to eliminate microorganisms in indoor air is very important. This study evaluated the effectiveness of a non-thermal plasma (NTP) air disinfector in both laboratory experiments and real environments. An experimental chamber was artificially polluted with a bioaerosol containing bacteria or viruses. Additionally, classroom environments with and without people present were used in field tests. Airborne microbial and particle concentrations were quantified. A 3.0 log10 reduction in the initial load was achieved when a virus-containing aerosol was disinfected for 60min and a bacteria-containing aerosol was disinfected for 90min. In the field test, when no people were present in the room, NTP disinfection decreased the airborne microbial and particle concentrations (P<0.05). When people were present in the room, their constant activity continuously contaminated the indoor air, but all airborne indicators decreased (P<0.05) except for planktonic bacteria (P=0.094). NTP effectively inactivated microorganisms and particles in indoor air.

Evaluating silicosis risk: Assessing dust constitution and influence of water as a primary prevention measure in cutting and polishing of silica agglomerates, granite and marble

An increasing number of silicosis cases have been reported related to the use of silica agglomerates. Many studies agree on the severity of this disease, which often presents with severe clinical forms in young workers and after a short latency period.Are there differences in the composition of dust generated by cutting and polishing with silica agglomerates versus granite and marble? Does the use of water injection reduce the risk associated with the use of these materials?We carried out a comparative observational-analytical study, measuring the concentration of dust generated during different machining operations on three different materials: granite, marble, and silica agglomerates. The effect of water injection on dust generation was evaluated.Personal sampling pumps were used, connected to a cyclone with polyvinyl chloride filters. The flow rate of the pumps was adjusted using a piston flowmeter. Measurements with a cascade impactor were made to assess the size distribution of respirable crystalline silica particles within the respirable fraction. In addition, environmental measurements with a spectrometer were made.10 tests were carried out on granite and silica agglomerates for each procedure. In the case of marble, with very low silica content, only 2 tests of each type were carried out. Duration of each measurement was between 6 and 25 min. Cleaning times were set for each of the operations.The amount of dust collected in the respirable fraction was 70.85, 32.50 and 35.78 mg/m3 for dry cutting; 6.50, 3.75 and 3.95 mg/m3 for wet cutting; and 21.35, 13.68 and 17.50 mg/m3 for dry polishing, for granite, marble, and silica agglomerates respectively.Dry procedures in marble, silica agglomerates and granite showed higher dust concentration of particles smaller than 0.5 μm. Silica agglomerates showed higher concentrations of respirable crystalline silica particles than granite and marble, mainly with dry procedures. The greater production of small particles in dry and wet procedures with silica agglomerates shows that water injection is an insufficient preventive measure.

A Comparative Study on Various ANN Optimization Algorithms for Magnetorheological Elastomer Carbonyl Iron Particle Concentration Estimation

Estimation particle composition such as particle shape, size, and concentration are crucial prior to the fabrication process of magnetorheological elastomer (MRE) to avoid process repetition due to inaccurate formulation. Currently, most of MRE prediction model were purposely used to predict the rheological properties such as shear stress and dynamic modulus, known as forward model. Nonetheless, very few studies have been reported to be capable able of predicting particle composition particularly in MR materials, which known as inverse model. Therefore, this paper proposed a carbonyl iron particle (CIP) concentration based MRE prediction model using neural network algorithm. Neural network-based machine learning model is more approachable compared to conventional mathematical modelling approach due to easily identify trends and pattern while handling multi-variety data. Various optimization algorithms have been employed such as Adam, RMSprop, SGD, AdaGrad, and Nadam throughout the modelling process. As the results, given shear strain amplitude, magnetic flux density, storage modulus, and loss factor as model input, SGD gave the maximum prediction accuracy with 0.95 and 3.038 MPa of R2 and RMSE, respectively. Hence, this model can be the basis to the MRE material and devices development particularly as the tool to reduce costing and time consuming.

Abstract 5161: Integrating patient’s derived organoids and liquid biopsy: An exploratory study of early stage pancreatic cancer

Abstract Background: Pancreatic cancer (PC) has a 5-year survival of 12% despite recent therapeutic advancements. There is a desperate need to discover novel ways of treating PC since a large proportion of patients do not benefit from therapy and experience significant toxicity. A major cause of therapy failure is therapy resistance due to tumor heterogeneity. Nowadays, a deeper understanding of tumor heterogeneity could be assisted by the use of patients-derived organoids (PDOs). Furthermore, the use of liquid biopsy may allow for the investigation of circulating factors with predictive value and for disease monitoring over time. Methods: Patients were enrolled in the comprehensive, multiomic study of pancreatic cancer CONTAINER. Patients with early stage PC treated with preoperative chemotherapy or undergoing surgery first were selected for the present study. When possible, a surgical specimen was collected to obtain PDOs. Tissue from resected tumors was dissociated by GentleMACSTM dissociator (Miltenyi Biotec), fragments were embedded in MatrigelTMand cultured in PancreaCultTM human Organoid Media (stemcell technologies). PDO histological features were investigated by H&amp;E staining and IHC. Blood samples were collected before and one month after surgery. From blood samples circulating tumor cells (CTCs) were enriched and isolated, extracellular vesicles (EVs) were isolated from plasma with size-exclusion chromatography and their concentration and size distribution was evaluated with NanoSight NS300. Then, EV surface antigens were characterized by flow cytometry. A panel of inflammatory cytokines was finally evaluated through Ella Automated Immunoassay System. Results: In CONTAINER study 113 patients were enrolled and 30 of them underwent surgery. 21 surgical specimens were received from which 18 PDOs were successfully established. EVs with diameter ≥ 70nm were isolated from plasma, EV mean size was similar before and after surgery whereas individual variations in particle concentration and in surface antigen exposure were observed. Correlation with clinical and pathological characteristics of patients will be performed once reached an adequate sample size for statistical analyses. A panel of inflammatory cytokines (IL1β-, IFNγ, TNFα, IL6, IL8, TGFβ1, CRP and Leptin) was assessed in plasma samples obtained before and after surgery. Except for IL1β, a significant individual variation of circulating cytokines before and after surgery was observed. Conclusions: This study will contribute to unveil mechanisms of disease progression and drug resistance in PC. Possible predictive factors and mechanisms of drug resistance will be investigated taking advantage of the information derived from both in vitro models and circulating tumor-related entities. Citation Format: Michela Cortesi, Tania Rossi, Michele Zanoni, Sara Bandini, Carlo Alberto Pacilio, Alessandro Cucchetti, Martina Valgiusti, Chiara Gallio, Alessandro Passardi, Giorgia Gurioli, Sara Bravaccini, Alessandra Dubini, Giovanni Luca Frassineti, Paola Ulivi, Giovanni Martinelli, Giorgio Ercolani, Ilario Giovanni Rapposelli. Integrating patient’s derived organoids and liquid biopsy: An exploratory study of early stage pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5161.

Study on pin temperature and wear behaviour of plasma sprayed Ni-Cr coatings with nano Al2O3 particle

ABSTRACT In this study, the dry sliding wear behaviour of plasma sprayed composite Ni-Cr coatings with nano Al2O3 particle concentrations of 0, 5, 10, 15, 20, and 100 wt.% on Al6061 substrate material was analysed. The coatings were characterised by scanning electron microscopy. The results showed higher porosity and coating thickness values for 100% and 20% nano Al2O3 particle coatings. The microhardness was found to increase with an increase in nano Al2O3 particle concentration in the Ni-Cr coating matrix. The porosity values were found to decrease with an increase in coating thickness. It is found that the specific wear rate of the Ni-Cr/15% Al2O3 particle coating is reduced by 54.02% compared to the Al2O3 particle coating.