Extracellular matrix physical properties govern the diffusion of nanoparticles in tumor microenvironment.

Nanoparticles (NPs) are confronted with limited and disappointing delivery efficiency in tumors clinically. The tumor extracellular matrix (ECM), whose physical traits have recently been recognized as new hallmarks of cancer, forms a main steric obstacle for NP diffusion, yet the role of tumor ECM physical traits in NP diffusion remains largely unexplored. Here, we characterized the physical properties of clinical gastric tumor samples and observed limited distribution of NPs in decellularized tumor tissues. We also performed molecular dynamics simulations and in vitro hydrogel experiments through single-particle tracking to investigate the diffusion mechanism of NPs and understand the influence of tumor ECM physical properties on NP diffusion both individually and collectively. Furthermore, we developed an estimation matrix model with evaluation scores of NP diffusion efficiency through comprehensive analyses of the data. Thus, beyond finding that loose and soft ECM with aligned structure contribute to efficient diffusion, we now have a systemic model to predict NP diffusion efficiency based on ECM physical traits and provide critical guidance for personalized tumor diagnosis and treatment.

Porous Flow Field for Next-Generation Proton Exchange Membrane Fuel Cells: Materials, Characterization, Design, and Challenges.

Porous flow fields distribute fuel and oxygen for the electrochemical reactions of proton exchange membrane (PEM) fuel cells through their pore network instead of conventional flow channels. This type of flow fields has showed great promises in enhancing reactant supply, heat removal, and electrical conduction, reducing the concentration performance loss and improving operational stability for fuel cells. This review presents the research and development progress of porous flow fields with insights for next-generation PEM fuel cells of high power density (e.g., ∼9.0 kW L-1). Materials, fabrication methods, fundamentals, and fuel cell performance associated with porous flow fields are discussed in depth. Major challenges are described and explained, along with several future directions, including separated gas/liquid flow configurations, integrated porous structure, full morphology modeling, data-driven methods, and artificial intelligence-assisted design/optimization.

Numerical Simulation Technologies in Solar-Driven Interfacial Evaporation Processes.

Solar interfacial evaporation technology has the advantages of environmentally conscious and sustainable benefits. Recent research on light absorption, water transportation, and thermal management has improved the evaporation performance of solar interfacial evaporators. However, many studies on photothermal materials and structures only aim to improve performance, neglecting explanations for heat and mass transfer coupling or providing evidence for performance enhancement. Numerical simulation can simulate the diffusion paths and heat and water transfer processes to understand the thermal and mass transfer mechanism, thereby better achieving the design of efficient solar interfacial evaporators. Therefore, this review summarizes the latest exciting findings and tremendous advances in numerical simulation for solar interfacial evaporation. First, it presents a macroscopic summary of the application of simulation in temperature distribution, salt concentration distribution, and vapor flux distribution during evaporation. Second, the utilization of simulation in the microscopic is summed up, specifically focusing on the movement of water molecules and the mechanisms of light responses during evaporation. Finally, all simulation methods have the goal of validating the physical processes in solar interfacial evaporation. It is hoped that the use of numerical simulation can provide theoretical guidance and technical support for the application of solar-driven interfacial evaporation technology.

A prediction model for nanoparticle diffusion behavior in fibrous materials considering steric and hydrodynamic resistances.

Precise prediction of the hindered diffusion behavior of electroneutral particles in fibrous media plays a critical role in the development of drugs, polymer membranes, and porous electrodes. However, the random microstructure and unknown coupling relationship of multiple resistance mechanisms lead to the lack of a universal prediction model. In this work, a dual-resistance model is proposed by reconstructed pore-scale simulations, which presents the coexistence of steric and hydrodynamic resistances in the multiplication form. The simulation results show that the relationship between steric resistance and structural parameters (porosity, fiber radius, and particle radius) is exponential, while that for hydrodynamic resistance is polynomial. The dominant diffusion resistance is found to change from hydrodynamic to steric resistance with a decrease in porosity. The fluorescent polystyrene microsphere diffusivity in a series of SiO2 fibrous media is determined by single-particle tracking experiments, quantitatively confirming the dual-resistance model. The present model can be used for rapid diffusivity prediction and fibrous membrane and drug design.

Thermococcus aciditolerans sp. nov., a piezotolerant, hyperthermophilic archaeon isolated from a deep-sea hydrothermal vent chimney in the Southwest Indian Ridge.

A hyperthermophilic, strictly anaerobic archaeon, designated strain SY113T, was isolated from a deep-sea hydrothermal vent chimney on the Southwest Indian Ridge at a water depth of 2770 m. Enrichment and isolation of strain SY113T were performed at 85 °C at 0.1 MPa. Cells of strain SY113T were irregular motile cocci with peritrichous flagella and generally 0.8-2.4 µm in diameter. Growth was observed at temperatures between 50 and 90 °C (optimum at 85 °C) and under hydrostatic pressures of 0.1-60 MPa (optimum, 27 MPa). Cells of SY113T grew at pH 4.0-9.0 (optimum, pH 5.5) and a NaCl concentration of 0.5-5.5 % (w/v; optimum concentration, 3.0 % NaCl). Strain SY113T was an anaerobic chemoorganoheterotroph and grew on complex proteinaceous substrates such as yeast extract and tryptone, as well as on maltose and starch. Elemental sulphur stimulated growth, but not obligatory for its growth. The G+C content of the genomic DNA was 55.0 mol%. Phylogenetic analysis of the 16S rRNA sequence of strain SY113T showed that the novel isolate belonged to the genus Thermococcus. On the basis of physiological characteristics, average nucleotide identity values and in silico DNA-DNA hybridization results, we propose a novel species, named Thermococcus aciditolerans sp. nov. The type strain is SY113T (=MCCC 1K04190T=JCM 39083T).

Tailoring patchy nanoparticle design to modulate serum albumin adsorption and membrane interaction.

When nanoparticles (NPs) enter into the biological system, a wide range of proteins will coat on their surfaces forming protein corona, which changes the initial synthetic characteristics of NPs to the biological identity, resulting in the loss of their targets or specially designed properties. Although pre-coating with proteins would reduce the protein corona formation, they may diminish the targeting moieties in the transport process. Patchy NPs can offer unique advantages of asymmetry, heterogeneity, and multi-functions. This has inspired us to use the asymmetry to realize the versatility of NPs, to accommodate stealth and targeting functions. In this study, we performed molecular dynamics simulations to investigate the adsorption mechanism between patchy NPs and human serum albumin, and the interaction mechanism between NP-HSA and the membrane. The results show that there is a high probability for HSA to interact with the hydrophobic, or charged brushes of patchy NPs. The adsorption sites, as calculated through the contact probability between NPs and the residues, depend on the NP surface properties. Furthermore, the HSA adsorption on NPs could improve the NP-membrane interaction. The simulation results provide deep understanding of the NP interaction mechanism, which would help the NP design for their biomedical applications.

Integrated analysis of gene expression and DNA methylation datasets identified key genes and a 6-gene prognostic signature for primary lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the main subtype of non-small cell lung cancer with a poor survival prognosis. In our study, gene expression, DNA methylation, and clinicopathological data of primary LUAD were utilized to identify potential prognostic markers for LUAD, which were recruited from The Cancer Genome Atlas (TCGA) database. Univariate regression analysis showed that there were 21 methylation-associated DEGs related to overall survival (OS), including 9 down- and 12 up-regulated genes. The 12 up-regulated genes with hypomethylation may be risky genes, whereas the other 9 down-regulated genes with hypermethylation might be protective genes. By using the Step-wise multivariate Cox analysis, a methylation-associated 6-gene (consisting of CCL20, F2, GNPNAT1, NT5E, B3GALT2, and VSIG2) prognostic signature was constructed and the risk score based on this gene signature classified patients into high- or low-risk groups. Patients of the high-risk group had shorter OS than those of the low-risk group in both the training and validation cohort. Multivariate Cox analysis and the stratified analysis revealed that the risk score was an independent prognostic factor for LUAD patients. The methylation-associated gene signature may serve as a prognostic factor for LUAD patients and the represent hypermethylated or hypomethylated genes might be potential targets for LUAD therapy.

A two-dimensional mathematical model for analyzing the effects of capture probe properties on the performance of lateral flow assays.

Lateral flow assays (LFAs) are promising candidates in biomedical diagnosis fields due to their rapid, low-cost, and portable features. However, improving their sensitivity remains challenging due to the unclear roles of capture probes with different distribution formats on the particle transfer and capturing in the test line. Therefore, we designed experiments and observed an asymmetrical U-shaped distribution of control probes throughout the NC membrane thickness. Based on this outcome, a two-dimensional mathematical model based on the Langmuir surface reaction kinetics was developed to investigate the effect of capture probe distributions on LFA performance. A two-dimensional model was qualitatively validated by comparing with the experimental results and the simulations of the reported one-dimensional model. Then, a higher detection signal was achieved by using the U-shaped distribution of capture probes throughout the NC membrane thickness instead of a uniform distribution. Furthermore, when the NC membrane thickness was less than 110 µm, the ratio of the detection signal in the visible region to the signal in the total section at the test line was above 13%. A thin NC membrane will produce a strong detection signal in the visible region at the test line. The developed model is capable of providing direct predictions in designing highly sensitive LFAs.

Standing Surface Acoustic Wave (SSAW)-Based Fluorescence-Activated Cell Sorter.

Microfluidic fluorescence-activated cell sorters (µFACS) have attracted considerable interest because of their ability to identify and separate cells in inexpensive and biosafe ways. Here a high-performance µFACS is presented by integrating a standing surface acoustic wave (SSAW)-based, 3D cell-focusing unit, an in-plane fluorescent detection unit, and an SSAW-based cell-deflection unit on a single chip. Without using sheath flow or precise flow rate control, the SSAW-based cell-focusing technique can focus cells into a single file at a designated position. The tight focusing of cells enables an in-plane-integrated optical detection system to accurately distinguish individual cells of interest. In the acoustic-based cell-deflection unit, a focused interdigital transducer design is utilized to deflect cells from the focused stream within a minimized area, resulting in a high-throughput sorting ability. Each unit is experimentally characterized, respectively, and the integrated SSAW-based FACS is used to sort mammalian cells (HeLa) at different throughputs. A sorting purity of greater than 90% is achieved at a throughput of 2500 events s-1 . The SSAW-based FACS is efficient, fast, biosafe, biocompatible and has a small footprint, making it a competitive alternative to more expensive, bulkier traditional FACS.

An improved detection limit and working range of lateral flow assays based on a mathematical model.

Lateral flow assays (LFAs) have attracted considerable attention in biomedical diagnostics. However, it's still challenging to achieve a high detection sensitivity and extensive working range, mainly because the underlying mechanism of complex reaction processes in LFAs remains unclear. Many mathematical models have been developed to analyze the complex reaction processes, which are only qualitative with limited guidance for LFA design. Now, a semi-quantitative convection-diffusion-reaction model is developed by considering the kinetics of renaturation of nucleic acids and the model is validated by our experiments. We established a method to convert the LFA design parameters between the simulation and experiment (i.e., inlet reporter particle concentration, initial capture probe concentration, and association rate constant), with which we achieved a semi-quantitative comparison of the detection limit and working range between simulations and experiments. Based on our model, we have improved the detection sensitivity and working range by using high concentrations of the inlet reporter particles and initial capture probe. Besides, we also found that target nucleic acid sequences with a high association rate constant are beneficial to improve the LFA performance. The developed model can predict the detection limit and working range and would be helpful to optimize the design of LFAs.

Polydimethylsiloxane-Paper Hybrid Lateral Flow Assay for Highly Sensitive Point-of-Care Nucleic Acid Testing.

In nucleic acid testing (NAT), gold nanoparticle (AuNP)-based lateral flow assays (LFAs) have received significant attention due to their cost-effectiveness, rapidity, and the ability to produce a simple colorimetric readout. However, the poor sensitivity of AuNP-based LFAs limits its widespread applications. Even though various efforts have been made to improve the assay sensitivity, most methods are inappropriate for integration into LFA for sample-to-answer NAT at the point-of-care (POC), usually due to the complicated fabrication processes or incompatible chemicals used. To address this, we propose a novel strategy of integrating a simple fluidic control strategy into LFA. The strategy involves incorporating a piece of paper-based shunt and a polydimethylsiloxane (PDMS) barrier to the strip to achieve optimum fluidic delays for LFA signal enhancement, resulting in 10-fold signal enhancement over unmodified LFA. The phenomena of fluidic delay were also evaluated by mathematical simulation, through which we found the movement of fluid throughout the shunt and the tortuosity effects in the presence of PDMS barrier, which significantly affect the detection sensitivity. To demonstrate the potential of integrating this strategy into a LFA with sample-in-answer-out capability, we further applied this strategy into our prototype sample-to-answer LFA to sensitively detect the Hepatitis B virus (HBV) in clinical blood samples. The proposed strategy offers great potential for highly sensitive detection of various targets for wide application in the near future.

Molecular analysis of interactions between a PAMAM dendrimer-paclitaxel conjugate and a biomembrane.

Understanding the underlying mechanism of nanomedicine-biomembrane interactions is important for the design and optimization of payload delivery systems. This study investigates the interactions between polyamidoamine (PAMAM) dendrimer-paclitaxel conjugates and biomembranes using coarse-grained molecular dynamics simulations. We found that acidic conditions (e.g., pH ∼ 5) and membrane asymmetry can improve the conjugate penetration. Paclitaxel (PTX) distributions on a G4 PAMAM dendrimer can affect interactions via the penetration mechanism, although they have no significant effect on interactions via the adsorption mechanism. The random distribution of PTX can enhance the ability of PTX molecules to pass through asymmetric membranes. Furthermore, the penetration process becomes more difficult with increasing paclitaxel loading ratios. These results provide molecular insights into the precise translocation mechanism of dendrimer-drug conjugates and thus provide suggestions for drug design and delivery.

An acoustofluidic micromixer via bubble inception and cavitation from microchannel sidewalls.

During the deep reactive ion etching process, the sidewalls of a silicon mold feature rough wavy structures, which can be transferred onto a polydimethylsiloxane (PDMS) microchannel through the soft lithography technique. In this article, we utilized the wavy structures of PDMS microchannel sidewalls to initiate and cavitate bubbles in the presence of acoustic waves. Through bubble cavitation, this acoustofluidic approach demonstrates fast, effective mixing in microfluidics. We characterized its performance by using viscous fluids such as poly(ethylene glycol) (PEG). When two PEG solutions with a resultant viscosity 54.9 times higher than that of water were used, the mixing efficiency was found to be 0.92, indicating excellent, homogeneous mixing. The acoustofluidic micromixer presented here has the advantages of simple fabrication, easy integration, and capability to mix high-viscosity fluids (Reynolds number: ~0.01) in less than 100 ms.

Molecular analysis of interactions between dendrimers and asymmetric membranes at different transport stages.

Studying dendrimer-biomembrane interactions is important for understanding drug and gene delivery. In this study, coarse-grained molecular dynamics simulations were performed to investigate the behaviors of polyamidoamine (PAMAM) dendrimers (G4 and G5) as they interacted with asymmetric membranes from different sides of the bilayer, thus mimicking different dendrimer transport stages. The G4 dendrimer could insert into the membrane during an equilibrated state, and the G5 dendrimer could induce pore formation in the membrane when the dendrimers interacted with the outer side (outer interactions) of an asymmetric membrane [with 10% dipalmitoyl phosphatidylserine (DPPS) in the inner leaflet of the membrane]. During the interaction with the inner side of the asymmetric membrane (inner interactions), the G4 and G5 dendrimers only adsorbed onto the membrane. As the membrane asymmetry increased (e.g., increased DPPS percentage in the inner leaflet of the membrane), the G4 and G5 dendrimers penetrated deeper into the membrane during the outer interactions and the G4 and G5 dendrimers were adsorbed more tightly onto the membrane for the inner interactions. When the DPPS content reached 50%, the G4 dendrimer could completely penetrate through the membrane from the outer side to the inner side. Our study provides molecular understanding and reference information about different dendrimer transport stages during drug and gene delivery.

Oxidative stress increased hepatotoxicity induced by nano-titanium dioxide in BRL-3A cells and Sprague-Dawley rats.

Extensive studies have shown that titanium dioxide (TiO2 ) nanomaterials (NMs) can cause toxicity in vitro and in vivo under normal conditions. However, an adverse effect induced by nano-TiO2 in many diseased conditions, typically characterized by oxidative stress (OS), remains unknown. We investigated the toxicity of nano-TiO2 in rat liver cells (BRL-3A) and Sprague-Dawley (SD) rat livers under OS conditions, which were generated using hydrogen peroxide (H2 O2 ) in vitro and alloxan in vivo, respectively. In vitro results showed that cell death ratios after nano-TiO2 exposure were significantly enhanced (up to 2.62-fold) in BRL-3A cells under OS conditions, compared with normal controls. Significant interactions between OS conditions and nano-TiO2 resulted in the rapid G0/G1 to S phase transition and G2/M arrest, which were opposite to G0/G1 phase arrest in cells after NMs exposure only. In vivo results showed that obvious pathological changes in rat livers and the increased activities of four enzymes (i.e. aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase and alkaline phosphatase) owing to liver damage after nano-TiO2 exposure under OS conditions, compared with their healthy controls. In addition, compared with increased hepatotoxicity after nano-TiO2 exposure, micro-TiO2 showed no adverse effects to cells and rat livers under OS conditions. Our results suggested that OS conditions synergistically increase nano-TiO2 induced toxicity in vitro and in vivo, indicating that the evaluation of nanotoxicity under OS conditions is essentially needed prior to various applications of NMs in foods, cosmetics and potential treatment of diseases.

A submicron forest-like silicon surface promotes bone regeneration by regulating macrophage polarization.

Introduction: Silicon is a major trace element in humans and a prospective supporting biomaterial to bone regeneration. Submicron silicon pillars, as a representative surface topography of silicon-based biomaterials, can regulate macrophage and osteoblastic cell responses. However, the design of submicron silicon pillars for promoting bone regeneration still needs to be optimized. In this study, we proposed a submicron forest-like (Fore) silicon surface (Fore) based on photoetching. The smooth (Smo) silicon surface and photoetched regular (Regu) silicon pillar surface were used for comparison in the bone regeneration evaluation. Methods: Surface parameters were investigated using a field emission scanning electron microscope, atomic force microscope, and contact angle instrument. The regulatory effect of macrophage polarization and succedent osteogenesis was studied using Raw264.7, MC3T3-E1, and rBMSCs. Finally, a mouse calvarial defect model was used for evaluating the promoting effect of bone regeneration on the three surfaces. Results: The results showed that the Fore surface can increase the expression of M2-polarized markers (CD163 and CD206) and decrease the expression of inflammatory cytokines, including interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α). Fore surface can promote the osteogenesis in MC3T3-E1 cells and osteoblastic differentiation of rBMSCs. Furthermore, the volume fraction of new bone and the thickness of trabeculae on the Fore surface were significantly increased, and the expression of RANKL was downregulated. In summary, the upregulation of macrophage M2 polarization on the Fore surface contributed to enhanced osteogenesis in vitro and accelerated bone regeneration in vivo. Discussion: This study strengthens our understanding of the topographic design for developing future silicon-based biomaterials.

Nanoscaled Titanium Oxide Layer Provokes Quick Osseointegration on 3D-Printed Dental Implants: A Domino Effect Induced by Hydrophilic Surface.

Three-dimensional printing is a revolutionary strategy to fabricate dental implants. Especially, 3D-printed dental implants modified with nanoscaled titanium oxide layer (H-SLM) have impressively shown quick osseointegration, but the accurate mechanism remains elusive. Herein, we unmask a domino effect that the hydrophilic surface of the H-SLM facilitates blood wetting, enhances the blood shear rate, promotes blood clotting, and changes clot features for quick osseointegration. Combining computational fluid dynamic simulation and biological verification, we find a blood shear rate during blood wetting of the hydrophilic H-SLM 1.2-fold higher than that of the raw 3D-printed implant, which activates blood clot formation. Blood clots formed on the hydrophilic H-SLM demonstrate anti-inflammatory and pro-osteogenesis effects, leading to a 1.5-fold higher bone-to-implant contact and a 1.8-fold higher mechanical anchorage at the early stage of osseointegration. This mechanism deepens current knowledge between osseointegration speed and implant surface characteristics, which is instructive in surface nanoscaled modification of multiple 3D-printed intrabony implants.

Retarding anion migration for alleviating concentration polarization towards stable polymer lithium-metal batteries.

Traditional dual-ion lithium salts have been widely used in solid polymer lithium-metal batteries (LMBs). Nevertheless, concentration polarization caused by uncontrolled migration of free anions has severely caused the growth of lithium dendrites. Although single-ion conductor polymers (SICP) have been developed to reduce concentration polarization, the poor ionic conductivity caused by low carrier concentration limits their application. Herein, a dual-salt quasi-solid polymer electrolyte (QSPE), containing the SICP network as a salt and traditional dual-ion lithium salt, is designed for retarding the movement of free anions and simultaneously providing sufficient effective carriers to alleviate concentration polarization. The dual salt network of this designed QSPE is prepared through in-situ crosslinking copolymerization of SICP monomer, regular ionic conductor, crosslinker with the presence of the dual-ion lithium salt, delivering a high lithium-ion transference number (0.75) and satisfactory ionic conductivity (1.16 × 10-3 S cm-1 at 30 °C). Comprehensive characterizations combined with theoretical calculation demonstrate that polyanions from SICP exerts a potential repulsive effect on the transport of free anions to reduce concentration polarization inhibiting lithium dendrites. As a consequence, the Li||LiFePO4 cell achieves a long-cycle stability for 2000 cycles and a 90% capacity retention at 30 °C. This work provides a new perspective for reducing concentration polarization and simultaneously enabling enough lithium-ions migration for high-performance polymer LMBs.

Quantum conditional generative adversarial network based on patch method for abnormal electrocardiogram generation.

To address the scarcity and class imbalance of abnormal electrocardiogram (ECG) databases, which are crucial in AI-driven diagnostic tools for potential cardiovascular disease detection, this study proposes a novel quantum conditional generative adversarial algorithm (QCGAN-ECG) for generating abnormal ECG signals. The QCGAN-ECG constructs a quantum generator based on patch method. In this method, each sub-generator generates distinct features of abnormal heartbeats in different segments. This patch-based generative algorithm conserves quantum resources and makes QCGAN-ECG practical for near-term quantum devices. Additionally, QCGAN-ECG introduces quantum registers as control conditions. It encodes information about the types and probability distributions of abnormal heartbeats into quantum registers, rendering the entire generative process controllable. Simulation experiments on Pennylane demonstrated that the QCGAN-ECG could generate completely abnormal heartbeats with an average accuracy of 88.8%. Moreover, the QCGAN-ECG can accurately fit the probability distribution of various abnormal ECG data. In the anti-noise experiments, the QCGAN-ECG showcased outstanding robustness across various levels of quantum noise interference. These results demonstrate the effectiveness and potential applicability of the QCGAN-ECG for generating abnormal ECG signals, which will further promote the development of AI-driven cardiac disease diagnosis systems. The source code is available at github.com/VanSWK/QCGAN_ECG.

Identifying the dominant transport mechanism in single nanoscale pores and 3D nanoporous media.

Gas transport mechanisms can be categorized into viscous flow and mass diffusion, both of which may coexist in a porous media with multiscale pore sizes. To determine the dominant transport mechanism and its contribution to gas transport capacity, the gas viscous flow and mass diffusion processes are analyzed in single nanoscale pores via a theoretical method, and are simulated in 3D nanoporous media via pore-scale lattice Boltzmann methods. The apparent permeability from the viscous flow and apparent diffusivity from the mass diffusion are estimated. A dimensionless parameter, i.e., the diffusion-flow ratio, is proposed to evaluate the dominant transport mechanism, which is a function of the apparent permeability, apparent diffusivity, bulk dynamic viscosity, and working pressure. The results show that the apparent permeability increases by approximately two orders of magnitude when the average Knudsen number (Kn avg) of the nanoporous media or Knudsen number (Kn) of single nanoscale pores increases from 0.1 to 10. Under the same conditions, the increment in the apparent diffusivity is only approximately one order of magnitude. When Kn < 0.01, the apparent permeability has a lower bound (i.e., absolute permeability). When Kn > 10, the apparent diffusivity has an upper bound (i.e., Knudsen diffusivity). The dominant transport mechanism in single nanoscale pores is the viscous flow for 0.01 < Kn < 100, where the maximum diffusion-flow ratio is less than one. In nanoporous media, the dominant transport relies heavily on Kn avg and the structural parameters. For nanoporous media with the pore throat diameter of 3 nm, Kn avg = 0.2 is the critical point, above which the mass diffusion is dominant; otherwise, the viscous flow is dominant. As Kn avg increases to 3.4, the mass diffusion is overwhelming, with the maximum diffusion-flow ratio reaching ∼4.