Application of PAT Probes in Aluminum Phosphate Adjuvant Manufacturing.

PURPOSE: This study is focused on monitoring process parameters and quality attributes of aluminum phosphate (AlPO4) using multiple in-line probes incorporated into an industrial-scale adjuvant suspension manufacturing unit. METHODS: The manufacturing of aluminum adjuvant suspension was monitored at manufacturing scale using conductivity, turbidity, infrared, and particle sizing and count probes to follow the continuous evolution of particle formation and size distribution, and the reaction kinetics during the synthesis of AlPO4. RESULTS: The data showed that AlPO4 forms large particles at the early stages of mixing, followed by a decrease in size and then stabilization towards the later stages of mixing and pH adjustment. The results provided a complementary view of process events and assisted in optimizing several parameters, e.g., flow rate of reactants AlCl3 and Na3PO4 solutions, mixing rate, pH, and conductivity of AlPO4, as well as adjuvant quality attribute such as particle size, thus streamlining and shortening the process development stage. CONCLUSION: The results of this study showed the usefulness of the in-line probes to automate continuous assessment of AlPO4 batch-to-batch consistency during in-house adjuvant production at the industrial scale.

Larger particle size distribution of environmental RNA compared to environmental DNA: a case study targeting the mitochondrial cytochrome b gene in zebrafish (Danio rerio) using experimental aquariums.

Environmental RNA (eRNA) analysis is conventionally expected to infer physiological information about organisms within their ecosystems, whereas environmental DNA (eDNA) analysis only infers their presence and abundance. Despite the promise of eRNA application, basic research on eRNA characteristics and dynamics is limited. The present study conducted aquarium experiments using zebrafish (Danio rerio) to estimate the particle size distribution (PSD) of eRNA in order to better understand the persistence state of eRNA particles. Rearing water samples were sequentially filtered using different pore-size filters, and the resulting size-fractioned mitochondrial cytochrome b (CytB) eDNA and eRNA data were modeled with the Weibull complementary cumulative distribution function (CCDF) to estimate the parameters characterizing the PSDs. It was revealed that the scale parameter (α) was significantly higher (i.e., the mean particle size was larger) for eRNA than eDNA, while the shape parameter (ß) was not significantly different between them. This result supports the hypothesis that most eRNA particles are likely in a protected, intra-cellular state, which mitigates eRNA degradation in water. Moreover, these findings also imply the heterogeneous dispersion of eRNA relative to eDNA and suggest an efficient method of eRNA collection using a larger pore-size filter. Further studies on the characteristics and dynamics of eRNA particles should be pursued in the future.

Assimilating Size Diversity: Population Balance Equations Applied to the Modeling of Microplastic Transport.

Modeling of microplastic (MP) transport in the aquatic environment is complicated by the diverse properties of the plastic particles. Traditional modeling methods such as Lagrangian particle tracking and Eulerian discrete class (DC) methods have limitations as they are not best placed to account for the diverse characteristics of individual particles, namely, size, density, and shape, which are crucial for determining the transport of MPs. In this work, we address the issue of particle size diversity by using the population balance equations (PBE) method. In addition to the advection-diffusion terms, the PBE transport equation involves a deposition sink term. Seven size classes of MPs are modeled in the DC method, which is compared to the PBE method. The evolution of particle size distribution is compared between the two methods using a simplified test case of a schematized estuary with tidal forcing and river discharge. This work successfully demonstrates the applicability and appropriateness of the PBE model in modeling the transport of MPs to track the dynamic and complete size distribution at a reduced computational cost in comparison to the DC model. With the PBE method, it is possible to address other diversities of the MPs such as the shape and density.

Characterizing and Predicting nvPM Size Distributions for Aviation Emission Inventories and Environmental Impact.

Concerns about civil aviation's air quality and environmental impacts have led to recent regulations on nonvolatile particulate matter (nvPM) mass and number emissions. Although these regulations do not mandate measuring particle size distribution (PSD), understanding PSDs is vital for assessing the environmental impacts of aviation nvPM. This study introduces a comprehensive data set detailing PSD characteristics of 42 engines across 19 turbofan types, ranging from unregulated small business jets to regulated large commercial aircraft. Emission tests were independently performed by using the European and Swiss reference nvPM sampling and measurement systems with parallel PSD measurements. The geometric mean diameter (GMD) at the engine exit strongly correlated with the nvPM number-to-mass ratio (N/M) and thrust, varying from 7 to 52 nm. The engine-exit geometric standard deviation ranged from 1.7 to 2.5 (mean of 2.05). The study proposes empirical correlations to predict GMD from N/M data of emissions-certified engines. These predictions are expected to be effective for conventional rich-burn engines and might be extended to novel combustor technologies if additional data become available. The findings support the refinement of emission models and help in assessing the aviation non-CO2 climate and air quality impacts.

Development of an advanced separation and characterization platform for mRNA and lipid nanoparticles using multi-detector asymmetrical flow field-flow fractionation.

In recent years, the use of lipid nanoparticles (LNPs) for delivery of messenger RNA (mRNA)-based therapies has gained substantial attention in the field of drug development. In such an application, multiple LNP attributes have to be carefully characterized to ensure product safety and quality, whereas accurate and efficient characterization of these complex mRNA-LNP formulations remains a challenging endeavor. Here, we present the development and application of an online separation and characterization platform designed for the isolation and in-depth analysis of mRNAs and mRNA-loaded LNPs. Our asymmetrical flow field-flow fractionation with a multi-detector (MD-AF4) method has demonstrated exceptional resolution between mRNA-LNPs and mRNAs, delivering excellent recoveries (over 70%) for both analytes and exceptional repeatability. Notably, this platform allows for comprehensive and multi-attribute LNP characterization, including online particle sizing, morphology characterization, and determination of encapsulation efficiency, all within a single injection. Furthermore, real-time online sizing by synchronizing multi-angle light scattering (MALS) and dynamic light scattering (DLS) presented higher resolution over traditional batch-mode DLS, particularly in differentiating heterogeneous samples with a low abundance of large-sized particles. Additionally, our method proves to be a valuable tool for monitoring LNP stability under varying stress conditions. Our work introduces a robust and versatile analytical platform using MD-AF4 that not only efficiently provides multi-attribute characterizations of mRNA-LNPs but also holds promise in advancing studies related to formulation screening, quality control, and stability assessment in the evolving field of nanoparticle delivery systems for mRNAs.

Exploring ultrafine particle emission characteristics from in-use light-duty diesel trucks in China using a portable measurement system.

Diesel vehicle exhaust is one of the major contributors to ultrafine particles (UFPs) in urban areas in China. However, there is still a lack of knowledge about UFPs emission characteristics from current in-use diesel vehicles. This study has carried out an on-road test of 10 in-use Light-duty Diesel Trucks (LDDTs) with different emission control standards in China using a self-established portable measurement system based on the Electronic Low-pressure Impactor (ELPI) and characterized the ultrafine particle number (PN) concentration, particle size distribution and metal element contents. The results revealed a significant reduction of 93.37% in the average PN0.1 emission factor of LDDTs from China III to China VI. Notably, LDDTs compliant with the China VI vehicle emission control standard exhibited the lowest PN0.1 and PM0.1 emission factors, measuring 4.991 × 1014 #/km and 0.627 g/km, respectively. By taking into account emissions under real driving conditions, we found that the PN emission rates grow with the increase of the Vehicle Specific Power (VSP). The cold-start phase had higher PN emissions than the hot-start phase, with 8590, 1890, 477, and 22 times higher than those of the ambient air (1.18 × 105 #/cm3), respectively. The installation of Diesel Particulate Filter (DPF) can decrease UFPs by more than 99.8%, while the PN emission factor during the DPF regeneration stage (1.85 × 1016 #/km) increased by 5 orders of magnitude that of the DPF normal works (7.51 × 1011 #/km). Metal element contents analysis shows that Fe, Ca, Al and Mg are the dominant elements in UFPs of LDDT exhaust gas, but the element of Ni is slightly increasing in a China VI, possibly due to the new automotive engine exhaust manifolds being made of Ni instead of cast iron for the purpose of having more high-temperature resistance. Our study demonstrates the importance of monitoring and routine maintenance of exhaust after-treatment systems.

Dispersant-enhanced migration of radiocesium among soil size fractions: A novel strategy for volume reduction of radioactively contaminated soil.

In the aftermath of the Fukushima Daiichi Nuclear Power Plant accident, a pioneering large-scale decontamination project was initiated, aiming to enable the return of evacuees. This project, the first of its kind in human history, involved the transportation of soils collected during decontamination to interim storage facilities. Before recycling or disposal, these soils undergo processes like volume reduction. However, there's a need for innovative methods to reduce volume effectively and treat secondary wastes more efficiently. The current study explores the impact of a dispersant, sodium hexametaphosphate (SHMP), on the behavior of radiocesium (r-Cs: 137Cs) dynamics in different size fractions of radioactively contaminated soils from Fukushima. The solid-phase speciation analysis of Fukushima soils validated that at least 50% of the 137Cs or other minerals are associated with difficult-to-extract soil phases. Nonetheless, the low 137Cs/133Cs ratio in corresponding soil phases implies a slower r-Cs fixation mechanism. The wet-sieving of r-Cs contaminated soil fraction, < 2 mm, with SHMP, resulted in different soil subfractions (2000-212, 212-53, and < 53 µm). Following SHMP treatment, dispersion of > 92% of 137Cs associated with < 212 µm soil size fractions was observed. The migration of 137Cs towards smaller soil size fractions can be attributed to either SHMP-induced cation exchange or the formation of polyvalent complexes involving SHMP and soil minerals. The condensation of 137Cs in < 212 µm, as induced by SHMP, enabled the subsequent reuse of the larger soil fraction (> 212 µm), which was less contaminated. This study provides a new perspective on the effects of dispersants and contributes to a better understanding of the complex interactions among organic carbon, 137Cs, monovalent and polyvalent cations, and soil functional groups concerning the volume reduction of soils contaminated with r-Cs.

Anaerobic membrane bioreactor coupled with polyaluminum chloride for high-strength phenolic wastewater treatment: Robust performance and potential mechanisms.

Anaerobic digestion of phenolic wastewater by anaerobic membrane bioreactor (AnMBR) has revealed increasing attractiveness, but the application of AnMBRs for treating high-strength phenolic wastewater faces challenges related to elevated phenol stress and membrane fouling. In this study, the coupling of AnMBR and polyaluminum chloride (PAC) was developed for efficient treatment of high-strength phenolic wastewater. The system achieved robust removal efficiencies of phenol (99%) and quinoline (98%) at a gradual increase of phenol concentration from 1000 to 5000 mg/L and a constant quinoline concentration of 100 mg/L. The dosing of PAC could effectively control the membrane fouling rate with the transmembrane pressure (TMP) increasing rate as low as 0.17 kPa/d. The robust performances were mainly attributed to the favorable retention of functional microbes through membrane interception, while pulse cross flow buffered against phenol stress and facilitated cake layer removal. Meanwhile, the enriched core functional microbes, such as Syntrophorhabdus, Syntrophus, Mesotoga and Methanolinea, played a crucial role in further reduction of phenol stress. Notably, the significant presence of biomacromolecule degrader, such as Levilinea, contributed to membrane fouling mitigation through extracellular polymer degradation. Moreover, the enlargement of particle size distribution (PSD) by PAC was expected to mitigate membrane fouling. This study provided a promising avenue for sustainable treatment of high-strength phenolic wastewater.

A Three-Wavelength Optical Sensor for Measuring the Multi-Particle-Size Channel Mass Concentration of Thermal Power Plant Emissions.

Emissions from thermal power plants have always been the central consideration for environmental protection. Existing optical sensors in thermal power plants usually measure the total mass concentration of the particulate matter (PM) by a single-wavelength laser, bearing intrinsic errors owing to the variation in particle size distribution (PSD). However, the total mass concentration alone cannot characterize all the harmful effects of the air pollution caused by the power plant. Therefore, it is necessary to measure the mass concentration and PSD simultaneously, based on which we can obtain multi-particle-size channel mass concentration. To achieve this, we designed an optical sensor based on the three-wavelength technique and tested its performance in a practical environment. Results showed that the prototype cannot only correctly measure the mass concentration of the emitted PM but also determine the mean diameter and standard deviation of the PSDs. Hence, the mass concentrations of PM10, PM2.5, and PM1 are calculated, and the air pollutants emission by a thermal power plant can be estimated comprehensively.

A Novel image processing technique for weighted particle size distribution assessment.

The objective of the study was to create a reliable method that could be used to evaluate the particle size distribution of samples and pre-mixes in real-world situations, particularly those consisting of typical formulation blends. The goal was to use this method to assess the uniformity of the samples and ensure that they met the required quality standards. The researchers aimed to create a method that could be easily incorporated into the manufacturing process, providing a practical and efficient solution. This study demonstrates the use of ImageJ software to analyze the particle size distribution (PSD) of powders. The technique produces qualitative data from microscopy images and quantitative data from analysis of parameters including average diameter, D10, D50, D90, and standard deviation. The method was tested with various treatments, showing differentiating outcomes in all cases. The alternate technique provides a rapid and cost-effective method for PSD analysis, surpassing the limitations of sieve analysis. Extensive testing of the method, using a variety of sample types, including typical formulation blends, was performed. The results suggest that the method can effectively assess the morphology of changing materials during batch manufacturing and characterize uniformity in blends. The methodology has the capability to identify attributes related to PSD that are typically required to be monitored during manufacturing. The technique allows for accurate and reliable quantification of the attributes through image capture technology. The technique has future potential and has important implications for material science, powder rheology, pharmaceutical formulation development, and continual process monitoring.

[Figure: see text]A Novel Image Processing Technique for Weighted Particle Size Distribution Assessment.

Investigating the effect of wall material and pressure homogenisation on encapsulation parameters and thermal stability in chia seed oil microcapsules.

AIM: To evaluate the effect of different wall material (WM) matrices followed by homogenisation to encapsulate chia seed oil (CSO) using freeze drying technology. METHODS: CSO was encapsulated using three ratios (100/0, 50/50, and 100/0) of two WM matrices: MTS/WPC (modified tapioca starch-whey protein concentrate) and MD/WPC (maltodextrin-whey protein concentrate). The evaluation included encapsulation efficiency (EE), oxidative stability, and α-linolenic acid (ALA) retention. Homogenised microcapsules (-H) were then assessed for storage and thermal stability, along with cumulative oil release. RESULTS: The MD-WPC-H 50/50 microcapsules had superior EE (97.32%), higher ALA retention (60.2%), storage stability (up to 30 days), higher thermal stability (up to 700 °C), and desirable oil release in simulated condition. CONCLUSION: Selecting suitable WM and homogenisation is key for improving EE, storage, thermal stability, and targeted release. The CSO microcapsule can serve as a functional ingredient to improve the quality of diverse food products.

Particle size distribution of total suspended sediments in urban stormwater runoff: Effect of land uses, precipitation conditions, and seasonal variations.

Understanding particle size distribution (PSD) of total suspended sediments in urban runoff is essential for pollutant fate and designing effective stormwater treatment measures. However, the PSDs from different land uses under different weather conditions have yet to be sufficiently studied. This research conducted a six-year water sampling program in 15 study sites to analyze the PSD of total suspended sediments in runoff. The results revealed that the median particle size decreased in the order: paved residential, commercial, gravel lane residential, mixed land use, industrial, and roads. Fine particles less than 125 µm are the dominant particles (over 75%) of total suspended sediments in runoff in Calgary, Alberta, Canada. Roads have the largest percentage of particles finer than 32 µm (49%). Gravel lane residential areas have finer particle sizes than paved residential areas. The results of PSD were compared with previous literature to provide more comprehensive information about PSD from different land uses. The impact of rainfall event types can vary depending on land use types. A long antecedent dry period tends to result in the accumulation of fine particles on urban surfaces. High rainfall intensity and long duration can wash off more coarse particles. The PSD in spring exhibits the finest particles, while fall has the largest percentage of coarse particles. Snowmelt particles are finer for the same land use than that during rainfall events because the rainfall-runoff flows are usually larger than the snowmelt flows.

Preparation and Mechanism of Shale Inhibitor TIL-NH2 for Shale Gas Horizontal Wells.

In this study, a new polyionic polymer inhibitor, TIL-NH2, was developed to address the instability of shale gas horizontal wells caused by water-based drilling fluids. The structural characteristics and inhibition effects of TIL-NH2 on mud shale were comprehensively analyzed using infrared spectroscopy, NMR spectroscopy, contact angle measurements, particle size distribution, zeta potential, X-ray diffraction, thermogravimetric analysis, and scanning electron microscopy. The results demonstrated that TIL-NH2 significantly enhances the thermal stability of shale, with a decomposition temperature exceeding 300 °C, indicating excellent high-temperature resistance. At a concentration of 0.9%, TIL-NH2 increased the median particle size of shale powder from 5.2871 µm to over 320 µm, effectively inhibiting hydration expansion and dispersion. The zeta potential measurements showed a reduction in the absolute value of illite's zeta potential from -38.2 mV to 22.1 mV at 0.6% concentration, highlighting a significant decrease in surface charge density. Infrared spectroscopy and X-ray diffraction confirmed the formation of a close adsorption layer between TIL-NH2 and the illite surface through electrostatic and hydrogen bonding, which reduced the weakly bound water content to 0.0951% and maintained layer spacing of 1.032 nm and 1.354 nm in dry and wet states, respectively. Thermogravimetric analysis indicated a marked reduction in heat loss, particularly in the strongly bound water content. Scanning electron microscopy revealed that shale powder treated with TIL-NH2 exhibited an irregular bulk shape with strong inter-particle bonding and low hydration degree. These findings suggest that TIL-NH2 effectively inhibits hydration swelling and dispersion of shale through the synergistic effects of cationic imidazole rings and primary amine groups, offering excellent temperature and salt resistance. This provides a technical foundation for the low-cost and efficient extraction of shale gas in horizontal wells.

Comprehension of drying kinetics and stone milling process of chestnuts: a focus on moisture content, milling speed, and energy evaluation.

BACKGROUND: Chestnut flour plays an important role in the production of bread, bakery products, and gluten-free foods. Most of the references in the literature focus on the drying process itself and not on the effects of the drying and milling processes. Moreover, the literature is lacking recommendations regarding optimal moisture content and milling speed, thus motivating the present study. The first aim is to understand the chestnut drying process through an in-depth evaluation of drying kinetics; the second aim is to assess the effects of three different moisture content (2%, 4% and 6%) and three different stone rotational speeds (120, 220 and 320 rpm) on operative milling parameters (flour yield, milling time, energy consumption, temperature increase, average power, specific milling energy), flour particle size distribution, and chestnut flours characteristics. RESULTS: The results show that moisture content and stone rotational speed have statistically-significant effects on milling operative parameters, flour particle size and chestnut flour composition. In particular, stone rotational speed affected almost all the tested variables (mill operative parameters, flour particle size distribution, and flour characteristics). Therefore, as the stone rotational speed increases, energy consumption, average power, specific energy, and damaged starch content significantly increase. CONCLUSION: These findings clearly show that moisture content and stone rotational speed are powerful tools that allow the exploiation of the milling process to modulate the characteristics of the obtained flours. In conclusion, two different approaches for chestnut milling were suggested depending on the type of flour to be produced. © 2024 Society of Chemical Industry.

Tree-based algorithms for spatial modeling of soil particle distribution in arid and semi-arid region.

Accurate estimation of particle size distribution across a large area is crucial for proper soil management and conservation, ensuring compatibility with capabilities and enabling better selection and adaptation of precision agricultural techniques. The study investigated the performance of tree-based models, ranging from simpler options like CART to sophisticated ones like XGBoost, in predicting soil texture over a wide geographic region. Models were constructed using remotely sensed plant and soil indexes as covariates. Variable selection employed the Boruta approach. Training and testing data for machine learning models consisted of particle size distribution results from 622 surface soil samples collected in southeastern Turkey. The XGBoostClay model emerged as the most accurate predictor, with an R2 value of 0.74. Its superiority was further underlined by a 21.36% relative improvement in XGBoostClay RMSE compared to RFClay and 44.5% compared to CARTClay. Similarly, the R2 values for XGBoostSilt and XGBoostSand models reached 0.71 and 0.75 in predicting sand and silt content, respectively. Among the considered covariates, the normalized ratio vegetation index and slope angle had the highest impact on clay content (21%), followed by topographic position index and simple ratio clay index (20%), while terrain ruggedness index had the least impact (18%). These results highlight the effectiveness of Boruta approach in selecting an adequate number of variables for digital mapping, suggesting its potential as a viable option in this field. Furthermore, the findings of this study suggest that remote sensing data can effectively contribute to digital soil mapping, with tree-based model development leading to improved prediction performance.

Laboratory and field evaluation of a low-cost optical particle sizer.

Low-cost sensors are widely used to collect high-spatial-resolution particulate matter data that traditional reference monitoring devices cannot. In addition to the mass concentration, the number concentration and size distribution are also fundamental in determining the origin and hazard level of particulate pollution. Therefore, low-cost optical sensors have been improved to establish optical particle sizers (OPSs). In this study, a low-cost OPS, the Nova SDS029, is introduced, and it is evaluated in comparison to two reference instruments-the GRIMM 11-D and the TSI 3330. We first tested the sizing accuracy using polystyrene latex spheres. Then, we assessed the mass and number size distribution accuracy in three application scenarios: indoor smoking, ambient air quality, and mobile monitoring. The evaluations suggest that the low-cost SDS029 rivals research-grade optical sizers in many aspects. For example, (1) the particle diameters obtained with the SDS029 are close to the reference instruments (usually < 10%) in the 0.3-5 µm range; (2) the number of particles and mass concentration are highly correlated (r ≥ 0.99) with the values obtained with the reference instruments; and (3) the SDS029 slightly underestimates the number concentration, but the derived PM2.5 values are closer to monitoring station than the reference instruments. The successful application of the SDS029 in multiple scenarios suggests that a plausible particle size distribution can be obtained in an easy and cost-efficient way. We believe that low-cost OPSs will increasingly be used to map the sources and risk levels of particles at the city scale.

Comprehensive investigation of recycled PVC powder.

This study constitutes a comprehensive investigation centred on comprehending the behaviour and characteristics of recycled polyvinyl chloride (PVC) powders. The overarching objective is to successfully conclude the initial research phase, during which PVC-coated fabric offcuts undergo a transformation into PVC powder while achieving complete separation from polyethylene terephthalate fibres. The study entails a qualitative description of the morphology of PVC powder particles, employing an optical microscope to distinguish the diverse shapes exhibited by these particles. The optical microscope observations of PVC powder reveal a distinct array of non-spherical particles characterized by flat, elongated shapes. These high-magnification images unveil the intricate morphological features of the particles, highlighting their irregular shapes. Subsequently, a quantitative analysis of PVC particle size distribution is performed, comparing results from optical microscopy with those obtained through mechanical sieving. The qualitative and quantitative findings obtained provide robust evidence supporting the correlation and confirm that most particles are smaller than 600 µm (93.6%) using an optical microscope and the sieving process (96.39%). The greatest fraction (83.44%) is in the size range between 200 and 600 µm. Assessing flowability, another significant aspect in the evaluation of powders, provides insights into its behaviour and interparticle interactions. The flowability results indicate a Compressibility Index of approximately 26.84%, which suggests poor flowability. This means that the powder is likely to encounter difficulties in flowing freely. This finding is in line with the Hausner ratio, which measures 1.37. This investigation of recycled PVC powder will offer insights into the potential applications and processing considerations of this powder. More concretely, the use of recycled PVC powder shows promise as a viable alternative to conventional PVC resin in plastisol formulations, offering the potential to maintain the properties of the final PVC product without adverse effects.

Utilizing the state of environmental DNA (eDNA) to incorporate time-scale information into eDNA analysis.

Environmental DNA (eDNA) analysis allows cost-effective and non-destructive biomonitoring with a high detection sensitivity in terrestrial and aquatic environments. However, the eDNA results can sometimes include false-positive inferences of target organisms owing to the detection of aged eDNA that has long since been released from the individual and is more likely to be detected at a site further away from its source. In order to address the issue, this manuscript focuses on the state of eDNA, proposing new methodologies to estimate the age of eDNA: (1) DNA damage rate, (2) eDNA particle size distribution, and (3) viable cell-derived eDNA. In addition, the manuscript also focuses on the shorter persistence of environmental RNA (eRNA) compared with eDNA, highlighting the application of eRNA and environmental nucleic acid ratio for assessing the age of the genetic materials in water. Although substantial further research is essential to support the feasibility of these methodologies, incorporating time-scale information into eDNA analysis would update current eDNA analysis, improve the accuracy and reliability of eDNA-based monitoring, and further refine eDNA analysis as a useful monitoring tool in ecology, fisheries and various environmental sciences.

Enhanced harvest performance predictability through advanced multivariate data analysis of mammalian cell culture particle size distribution.

The industry's pursuit for higher antibody production has led to increased cell density cultures that impact the performance of subsequent product recovery steps. This increase in cell concentration has highlighted the critical role of solids concentration in centrifugation yield, while recent product degradation cases have shed light on the impact of cell lysis on product quality. Current methods for measuring solids concentration and cell lysis are not suited for early-stage high-throughput experimentation, which means that these cell culture outputs are not well characterized in early process development. This article describes a novel approach that leveraged the data from a widely-used automated cell counter (Vi-CELL™ XR) to accurately predict solids concentration and a common cell lysis indicator represented as lactate dehydrogenase (LDH) release. For this purpose, partial least squares (PLS) models were derived with k-fold cross-validation from the particle size distribution data generated by the cell counter. The PLS models showed good predictive potential for both LDH release and solids concentration. This novel approach reduced the time required for evaluating the solids concentration and LDH for a typical high-throughput cell culture system (with 48 bioreactors in parallel) from around 7 h down to a few minutes.

Tunable Mie resonance in complex-shaped gadolinium niobate.

Nanoscale particles described by Mie resonance in the UV-vis-NIR region are in high demand for optical applications. Controlling the shape and size of these particles is essential, as it results in the ability to control the wavelength of the Mie resonance peak. In this work, we study the extensive scattering properties of gadolinium niobate particles with complex bar- and cube-like shapes in the UV-vis-NIR region. We perform our experimental analysis by characterizing the morphology and extinction spectra, and our theoretical study by implementing a Mie scattering model for a distribution of spherical particles. We can accurately model the size distribution and extinction spectra of complex shaped particles and isolate the contribution of aggregates to the extinction spectra. We can separate the contributions of dipoles, quadrupoles, and octupoles to the Mie resonances for their respective electric and magnetic parts. Our results show that we can tune the broad Mie resonance peak in the extinction spectra by the nanoscale properties of our system. This behavior can aid in the design of lasing and luminescence-enhanced systems. These dielectric gadolinium niobate submicron particles are excellent candidates for light manipulation on the nanoscale.