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Determination of the Maturation Status of Dendritic Cells by Applying Pattern Recognition to High-Resolution Images

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. Here we report a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

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An N$\cdots$H$\cdots$N low-barrier hydrogen bond preorganizes the catalytic site of aspartate aminotransferase to facilitate the second half-reaction

Pyridoxal 5'-phosphate (PLP)-dependent enzymes have been extensively studied for their ability to fine-tune PLP cofactor electronics to promote a wide array of chemistries. Neutron crystallography offers a straightforward approach to studying the electronic states of PLP and the electrostatics of enzyme active sites, responsible for the reaction specificities, by enabling direct visualization of hydrogen atom positions. Here we report a room-temperature joint X-ray/neutron structure of aspartate aminotransferase (AAT) with pyridoxamine 5'-phosphate (PMP), the cofactor product of the first half reaction catalyzed by the enzyme. Between PMP N SB and catalytic Lys258 Nζ amino groups an equally shared deuterium is observed in an apparent low-barrier hydrogen bond (LBHB). Density functional theory calculations were performed to provide further evidence of this LBHB interaction. The structural arrangement and the juxtaposition of PMP and Lys258, facilitated by the LBHB, suggests active site preorganization for the incoming ketoacid substrate that initiates the second half-reaction.

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Introductory guide to backgrounds in XPS spectra and their impact on determining peak intensities

Photoelectron and Auger peaks are central to most of the important uses of x-ray photoelectron spectroscopy (XPS), and thus, they receive the most attention in many types of analysis. Quantitative chemical analysis using XPS requires the assessment of the intensities of the photoemission peaks of the elements detected. Determination of peak intensities requires separation of the photoelectron peak signals from the background on which the peaks rest. For the determination of peak area intensities, the background is subtracted from overall signal intensity. The spectral background is also critical when peak fitting is used to determine intensities of overlapping peaks, and the model of background used in this process can impact the results. In addition to the impact on quantitative analysis, information about the depth distribution of elements in the near surface region can often be obtained by visual inspection of the background and quantified using appropriate modeling. Here, this introductory guide provides some basic information about backgrounds in the XPS analysis, describes the types of background models that are commonly used, suggests some of their strengths and weaknesses, and provides examples of their use and misuse. Although the fundamental nature of some components of the background signals in XPS is not understood, indicating that none of the models in use are fully correct and the area is subject to active research, appropriate good practices have been established for most routine analysis. The guide describes good practices, identifies errors that frequently appear in the literature, and uses examples to demonstrate the impacts of background selections on determinations of peak intensities.

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Effect of Alkali-Silica Reaction on Shear Strength of Reinforced Concrete Structural Members

Alkali-silica reaction (ASR) was discovered in the early 40s by Stanton (1940) of the California Division of Highways. Since, it has been recognized as a major degradation mechanism for concrete dams and transportation infrastructures. Sometimes described as the ’cancer of concrete’, this internal swelling mechanism causes expansion, cracking and loss of mechanical properties. There are no known economically viable solutions applicable to massive concrete to prevent the reaction once initiated. The e ciency of the mitigation strategies for ASR subjected structures is limited. Several cases of ASR in nuclear generating stations have been disclosed in Japan (Takatura et al. 2005), Canada at Gentilly 2 NPP (Tcherner and Aziz 2009) 1, and more recently, in the United States for which the U.S. Nuclear Regulatory Commission issued Information Notice (IN) 2011-20, ’Concrete Degradation by Alkali Silica Reaction,’ on November 18, 2011, to provide the industry with information related to the ASR identified at Seabrook. Considering that US commercial reactors in operation enter the age when ASR degradation can be visually detected and that numerous non nuclear infrastructures (transportation, energy production) have already experienced ASR in a large majority of the States (e.g., Department of Transportation survey reported by Touma (Touma 2000)), the susceptibility and significance of ASR for nuclear concrete structures must be addressed in the perspective of license renewal and long-term operation beyond 60 years. The aim of this report is to perform an extensive parametric series of 3D nonlinear finite element analyses of three di erent “beam-like” geometries, including two di erent depths, three di erent types of boundary conditions, and four other parameters: namely, the ASR volumetric expansion, the reinforcement ratio, the loss of elastic modulus induced by ASR and the loss of tensile strength caused by ASR.

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Insights into the structure–photoreactivity relationships in well-defined perovskite ferroelectric KNbO 3 nanowires

Structure–function correlations are a central theme in heterogeneous (photo)catalysis. In this study, the geometric and electronic structure of perovskite ferroelectric KNbO 3 nanowires with respective orthorhombic and monoclinic polymorphs have been systematically addressed. By virtue of aberration-corrected scanning transmission electron microscopy, we directly visualize surface photocatalytic active sites, measure local atomic displacements at an accuracy of several picometers, and quantify ferroelectric polarization combined with first-principles calculations. The photoreactivity of the as-prepared KNbO 3 nanowires is assessed toward aqueous rhodamine B degradation under UV light. A synergy between the ferroelectric polarization and electronic structure in photoreactivity enhancement is uncovered, which accounts for the prominent reactivity order: orthorhombic > monoclinic. Additionally, by identifying new photocatalytic products, rhodamine B degradation pathways involving N-deethylation and conjugated structure cleavage are proposed. The findings not only provide new insights into the structure–photoreactivity relationships in perovskite ferroelectric photocatalysts, but also have broad implications in perovskite-based water splitting and photovoltaics, among others.

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Helium Ion Microscopy with Secondary Ion Mass Spectrometry for Nanoscale Chemical Imaging and Analysis of Polyolefins

To date, chemical imaging of polymers and polymer blends has been primarily accomplished using time-of-flight secondary ion mass spectrometry (ToF-SIMS) to directly visualize the distribution of components in a complex material with spatial resolution ranging from 100 nm to 5 μm. However, in many cases, this resolution falls far short of visualizing interfaces directly. To overcome these limitations, recent work has focused on developing a SIMS detection system based on a helium ion microscope (HIM) enabling chemical imaging with a demonstrated ~14 nm spatial resolution. Here, we utilize HIM-SIMS for differentiation between the olefin-based polymers of polyethylene (PE) and polypropylene (PP). We illustrate both analyses for separating PE and PP using specific mass fragment ratios as well as demonstrate spatially resolved imaging of phase-separated domains within PE. Altogether, we demonstrate the abilities of HIM-SIMS as a multimodal chemical technique for imaging and quantification of polyolefin interfaces, which could be more broadly applied to the analysis of more complex polymeric systems.

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Homogenized halides and alkali cation segregation in alloyed organic-inorganic perovskites

The role of the alkali metal cations in halide perovskite solar cells is not well understood. Using synchrotron-based nano–x-ray fluorescence and complementary measurements, we found that the halide distribution becomes homogenized upon addition of cesium iodide, either alone or with rubidium iodide, for substoichiometric, stoichiometric, and overstoichiometric preparations, where the lead halide is varied with respect to organic halide precursors. Halide homogenization coincides with long-lived charge carrier decays, spatially homogeneous carrier dynamics (as visualized by ultrafast microscopy), and improved photovoltaic device performance. We found that rubidium and potassium phase-segregate in highly concentrated clusters. Alkali metals are beneficial at low concentrations, where they homogenize the halide distribution, but at higher concentrations, they form recombination-active second-phase clusters.

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Analysis of Tank 38H (HTF-38-22-91, -92) and Tank 43H (HTF-43-22-93, -94) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased slightly from the previous surface sample. The Tank 38H sub-surface sample shows changes in concentration for soluble species in the solution with some increasing and some decreasing. The current Tank 38H sub-surface sample contains more sludge solids than the previous sample based on visual appearance. The small differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate only minimal stratification of solution species within the tank. The Tank 43H surface and sub-surface samples are similar in composition to the previous samples. The similar solution compositions measured in the Tank 43H surface and sub-surface samples indicate a minimal stratification within the tank. The total uranium and plutonium in the current Tank 38H surface sample remains similar to the previous analysis. The Tank 38H sub-surface sample shows an increase in uranium and plutonium concentrations compared to the previous sample likely because of an increase in sludge solids in the current sample. The total uranium concentration in the two Tank 43H samples is essentially unchanged from previous sample results. The plutonium concentration in the Tank 43H surface sample is similar to the previous sample results while the plutonium in the Tank 43H sub-surface sample increased relative to the previous analysis. The sum of the major cations versus the sum of the major anions shows a difference of <10% for both samples from Tank 38H and for both samples from Tank 43H providing an indication of good data quality for the non-radioactive analytes in the samples. The silicon concentrations measured in the Tank 38H sub-surface sample increased compared with the previous sample results likely due to the presence of more sludge solids in the current sample. The Tank 38H surface sample silicon concentrations is similar to the previous sample results. The Tank 43H surface and sub-surface sample silicon concentrations both increased compared to the previous sample results. The samples analyzed from Tanks 38H and 43H show silicon concentrations ranging from 61.5 to 97.3 mg/L.

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Labile Fe(III) supersaturation controls nucleation and properties of product phases from Fe(II)-catalyzed ferrihydrite transformation

We report Fe(II)-catalyzed ferrihydrite (Fh) transformation to more crystalline iron (oxyhydr)oxide phases is a widely occurring geochemical process which has been extensively studied as a function of Fe(II)/Fh ratios at fixed Fh loadings. However, recent isolation of an intermediate Fe(III) species resulting from Fe(II)-Fh contact that facilitates transformation by dissolution/reprecipitation suggests that the kinetics and properties of product phases will instead depend mostly on its rate of accumulation to a critical concentration, consistent with principles in the classical nucleation theory (CNT). This suggests a dependence both on the loading of Fe(II) on the surface, which controls the rate of labile Fe(III) formation, as well as the available volume of solution, which also impacts how fast it can achieve its critical concentration to nucleate product phases. To specifically examine the latter effect, here we studied transformation of 15 mg Fh in 1 mM FeSO 4 solutions at pH 7.2 in batch suspensions of 30 mL, 150 mL, and 450 mL volumes. Time-dependent concentrations of aqueous Fe(II), surface-associated Fe(II), and resulting labile Fe(III) were monitored along with bulk solids characterization as a function of time. Transmission electron microscopy (TEM) was used to visualize the evolution of phases at identical locations on TEM grids. The collective results show that the rates of Fh loss and emergence of product lepidocrocite (Lp) and goethite (Gt) as well as their phase proportions, nucleation mode and morphological properties depend directly on the rate of accumulation of the labile Fe(III) precursor to its critical concentration, which in our experiments was controlled simply by varying the available volume of solution into which it enters. Statistical analyses of TEM image data suggest that while both heterogeneous and homogeneous nucleation occurred in all experiments, the former was increasingly favored at lower Fh/solution ratio due to its lower nucleation barrier being more favorable at attendant lower supersaturations of Fe(III).

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Understanding Diffusion in Hierarchical Zeolites with House-of-Cards Nanosheets

Introducing mesoporosity to conventional microporous sorbents or catalysts is often proposed as a solution to enhance their mass transport rates. Here, we show that diffusion in these hierarchical materials is more complex and exhibits non-monotonic dependence on sorbate loading. Our atomistic simulations of n-hexane in a model system containing microporous nanosheets and mesopore channels indicate that diffusivity can be smaller than in a conventional zeolite with the same micropore structure, and this observation holds true even if we confine the analysis to molecules completely inside the microporous nanosheets. Only at high sorbate loadings or elevated temperatures, when the mesopores begin to be sufficiently populated, does the overall diffusion in the hierarchical material exceed that in conventional microporous zeolites. Here, our model system is free of structural defects, such as pore blocking or surface disorder, that are typically invoked to explain slower-than-expected diffusion phenomena in experimental measurements. Examination of free energy profiles and visualization of molecular diffusion pathways demonstrates that the large free energy cost (mostly enthalpic in origin) for escaping from the microporous region into the mesopores leads to more tortuous diffusion paths and causes this unusual transport behavior in hierarchical nanoporous materials. This knowledge allows us to re-examine zero-length-column chromatography data and show that these experimental measurements are consistent with the simulation data when the crystallite size instead of the nanosheet thickness is used for the nominal diffusional length.

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Engineered Biosynthesis of Alkyne-Tagged Polyketides by Type I PKSs

Polyketides produced by modular polyketide synthases (PKSs) are important small molecules widely used as drugs, pesticides, and biological probes. Tagging these polyketides with a clickable functionality enables the visualization, diversification, and mode of action study through bio-orthogonal chemistry. We report the de novo biosynthesis of alkyne-tagged polyketides by modular type I PKSs through starter unit engineering. Specifically, we use JamABC, a terminal alkyne biosynthetic machinery from the jamaicamide B biosynthetic pathway, in combination with representative modular PKSs. We demonstrate that JamABC works as a trans loading system for engineered type I PKSs to produce alkyne-tagged polyketides. In addition, the production efficiency can be improved by enhancing the interactions between the carrier protein (JamC) and PKSs using docking domains and site-directed mutagenesis of JamC. This work thus provides engineering guidelines and strategies that are applicable to additional modular type I PKSs to produce targeted alkyne-tagged metabolites for chemical and biological applications.

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Conversion of biowastes to biomaterial: An innovative waste management approach

Highlights: • Study demonstrates that hydroxyapatite can be potentially produced from biowastes. • Eggshells and synthetic urine was used for hydroxyapatite synthesis. • Solution pH and stirring influenced hydroxyapatite formation. - Abstract: The study suggests that biowastes (eggshells and urine) can be potentially used as precursors to produce hydroxyapatite (HAp) biomaterial in a simple chemical process. A batch reactor was used in this work to produce HAp powder from eggshells and synthetic urine (SU). Fine powder of calcined eggshells was dissolved in water to produce aqueous calcium hydroxide. The solution was then mixed with concentrated SU in stoichiometric amounts corresponding to HAp (Ca/P molar ratio ∼ 1.67). The initial pH of the solution was alkaline (pH ∼ 8.5) and particles formed rapidly with slight mixing. Stirring the turbid solution for a longer period (72 h) did not show any visual change, but the particle size decreased slightly. When the pH of the solution was adjusted to 5, the solution was initially clear, but particle formation was apparent after 48 h stirring. It was noticed that at a slow stirring speed (100 rpm), film formation occurred on the solution, whereas at a higher stirring speed (500 rpm) no such film formation was observed. X-ray diffraction (XRD) analysis confirmed that the particles (formed at 500 rpm) were an amorphous calcium phosphate (CaP). Alkaline treatment at 80 °C for 2 h converted the amorphous CaP into HAp. Inductively coupled plasma mass spectrometry (ICP-MS) analysis of the particles (formed at 500 rpm) suggested that they are calcium-deficient HAp (Ca/P molar ratio 1.58).

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Fluorescent, phosphorescent, magnetic resonance contrast and radioactive tracer labelling of extracellular vesicles

This review focusses on the significance of fluorescent, phosphorescent labelling and tracking of extracellular vesicles (EVs) for unravelling their biology, pathophysiology, and potential diagnostic and therapeutic uses. Various labeling strategies, such as lipid membrane, surface protein, luminal, nucleic acid, radionuclide, quantum dot labels, and metal complex-based stains, are evaluated for visualizing and characterizing EVs. Direct labelling with fluorescent lipophilic dyes is simple but generally lacks specificity, while surface protein labelling offers selectivity but may affect EV-cell interactions. Luminal and nucleic acid labelling strategies have their own advantages and challenges. Here, each labelling approach has strengths and weaknesses, which require a suitable probe and technique based on research goals, but new tetranuclear polypyridylruthenium(II) complexes as phosphorescent probes have strong phosphorescence, selective staining, and stability. Future research should prioritize the design of novel fluorescent probes and labelling platforms that can significantly enhance the efficiency, accuracy, and specificity of EV labeling, while preserving their composition and functionality. It is crucial to reduce false positive signals and explore the potential of multimodal imaging techniques to gain comprehensive insights into EVs.

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Fission Product Volatility and Off-Gas Systems for Molten Salt Reactors

The overall objective of the Department of Energy investigation into off-gas technology for molten salt reactors (MSR)s is to develop a list of functional requirements for an effective and reliable system. In collaboration with other elements of the Advanced Reactor Campaign ( denoted in italics ), the off-gas work package will address the following questions: 1. What is the composition of the gas stream going to the off-gas system ( chemistry and source term work package )? 2. What is the function of each off-gas treatment component, and how do they work? How efficient are they at removing or delaying fission and activation products? 3. What are the maintenance requirements of the off-gas system? 4. Is the system able to effectively detect and respond to off-normal events ( off-gas, source term, and simulation work packages )? 5. What measurement capabilities are possible now? What are the gaps? The objective of the off-gas project in fiscal year 2019 was to address the second, fourth, and fifth questions above. Thus, project has proceeded along two fronts: one focused on scrubber development at Oak Ridge National Laboratory and the other focused on spectroscopic detection of simulant fission product iodine at Pacific Northwest National Laboratory. A molten hydroxide scrubber was proposed for removal of both acidic gases, entrained mists, and particulates from a sparged molten salt off-gas. Hydroxide solutions are well known for their scrubbing ability and have been used in the off-gas systems of salt processing facilities. For the current project, a NaOH–KOH eutectic is being evaluated as a gettering medium. A laboratory-scale prototype glass scrubber was designed and built for the removal of aerosol simulants. The glass allows visualization of the scrubber operation, which is important for designing the stainless-steel housing for the NaOH–KOH eutectic. In parallel, Pacific Northwest National Laboratory has been developing optical sensors for detecting fission products and aerosol or mist species that could be entrained in the off-gas flow of an MSR. Efforts include Raman spectroscopy to identify and quantify iodine species such as I2 and ICl and laser-induced breakdown spectroscopy and laser-induced fluorescence for mists. Next year, these optical methods will be added to the hydroxide scrubber instrumentation to determine its effectiveness against airborne vapors and mists of concern.

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A Novel, Low-Cost, Portable Device for Counterfeit and Noncompliant Refrigerant Detection

The increasing prevalence of counterfeit refrigerants presents significant risks to Heating, Ventilation, Air Conditioning, and Refrigeration (HVACR) systems, including compromised equipment performance, safety hazards, and environmental non-compliance. This report details the development of a novel, cost-effective, and portable detection device designed to accurately identify counterfeit refrigerants. The device utilizes a controlled gas sampling and analysis system within a sealed chamber, ensuring precise measurements while maintaining safety through a purging mechanism. The system features a high-sensitivity sensor integrated with an onboard control module that analyzes gas composition in real-time, providing users with clear visual indicators for refrigerant authenticity. Laboratory validation demonstrated the device’s high accuracy (exceeding 95%) in detecting unauthorized refrigerant blends. Key advantages include affordability, ease of use, rapid response time, and compatibility with a wide range of refrigerants. This solution supports compliance with regulatory frameworks such as the AIM Act, enhances safety in HVACR operations, and mitigates the risks associated with counterfeit refrigerants. Future developments will focus on expanding refrigerant detection capabilities, integrating machine learning for enhanced accuracy, implementing cost-reduction strategies to improve accessibility and market adoption, and optimizing system packaging for enhanced field portability.

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Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

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In Situ Visualization of Li-Whisker with Grating-Interferometry-Based Tricontrast X-ray Microtomography

The lithium-ion battery has demonstrated tremendous economic and social impacts. Upon battery operation under different conditions, lithium changes its chemical state and physical formation, leading to undesired side reactions, e.g., lithium dendrite growth that degrades the cell performance and causes safety concerns. In situ detection and visualization of lithium metal in functional batteries could offer insights with both scientific and industrial significance but remain a frontier challenge. In this work, we demonstrate in situ three-dimensional imaging of lithium whisker using a grating-interferometry-based tricontrast X-ray microtomography method. Our approach explicitly reveals the micromorphology of the electrochemically developed porous lithium whisker with micrometer-level spatial resolution while offering sensitivity to the nanoporosity that is smaller than the nominal resolution limit. Our result reveals valuable structural information on the lithium whisker that is otherwise inaccessible. This method is also readily applicable to a broad range of battery research, including all-solid-state batteries.

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Solid–liquid separation of lignocellulosic sugars from biomass by rotating ceramic disc filtration

In many biomass conversion processes, the separation of cellulosic sugars from residual, lignin-rich solids is a critical step, and achieving high recovery yields of sugars by conventional tangential crossflow and vacuum filtration is challenged by the presence of biomass solids, which rapidly foul filters, resulting in decreased throughput. Considering the performance limitations of traditional filtration methods, dynamic filtration, which generates high shear at the membrane surface to decrease fouling, is emerging as a viable alternative for demanding solid–liquid separations. For high solids separations, there is little available information regarding the performance, limitations, and energy consumption of dynamic filtration. To that end, here we characterized the performance of a dynamic filtration module, specifically a rotating ceramic disc (RCD) filter, for the aseptic recovery of cellulosic sugars from biomass solids following pretreatment and enzymatic hydrolysis. We show how RCD rotational velocity and percent biomass solids impact the filter throughput. Additionally, we used computational fluid dynamics (CFD) simulations to estimate the shear rate at the membrane surface and to visualize hydrodynamic profiles within the module. With the combined CFD simulations and experimental results, we estimated the energy demand and operating expenses for a viable dynamic filtration system operating with a lignocellulosic feed slurry. Our results indicate that an RCD filter can achieve ≥95% recovery of sugars and produce a retentate slurry containing 12 wt% insoluble solids with low energy consumption (a 2.2-fold improvement over cross-flow filtration) and low operating costs ($\$$0.06 per kg sugars). These results show a viable path towards operationally reliable, energy efficient, and cost-effective separations of sterilized cellulosic sugars from biomass solids and highlight the potential of dynamic filtration systems for challenging solid–liquid separations.

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