Measuring transmembrane water exchange can provide potential biomarkers for tumors and brain disorders. Diffusion Magnetic Resonance Imaging (dMRI) is a well-established tool that can non-invasively measure water exchange across cell membranes. Diffusion Exchange Spectroscopy (DEXSY) is one of the dMRI-based frameworks used to estimate exchange. DEXSY provides a detailed picture of multi-site exchange processes but requires a large quantity of data. Several models based on the DEXSY framework have been proposed to reduce the acquisition time. Filter Exchange Imaging (FEXI) and curvature models are two of them that only require certain samples of the DEXSY dataset. Diffusion-Exchange Weighted (DEW) Imaging model is another data reduction method accounting for restricted diffusion within cells and can use a specific subset of the DEXSY dataset to measure exchange. Furthermore, a more general expression of the DEXSY signal, referred to as the general model, can theoretically analyze the full space or reduced DEXSY datasets and estimate exchange. However, the results of the subsampling schemes and the data reduction models have not been compared to the full space estimation.  Therefore, this thesis aims to experimentally explore the feasibility of estimating exchange using these four models (the general, FEXI, curvature and DEW models) with the data acquired using a low-field benchtop MR scanner, and compare the estimates from the general model with different subsampling schemes and the data reduction models to the full space estimation. For this purpose, a double diffusion encoding (DDE) sequence was modified from an existing sequence on the benchtop MR scanner and a DEXSY experiment was conducted on this MR scanner and a yeast phantom to acquire a full space dataset. The exchange parameters estimated from the full space dataset using the general model were used as "ground truths" to evaluate the estimates from the reduced datasets analyzed using the general, FEXI and curvature models. Moreover, two alternative subsampling schemes named the shifted DEW and new trajectory schemes were proposed and employed to measure exchange. The results indicate that all the methods except the curvature sampling scheme employed with both the general and curvature models provided comparable estimates to the "ground truths". The shifted DEW and new trajectory sampling schemes performed better over others in terms of consistency with the "ground truths" and low variations between voxels, suggesting the theoretical and experimental optimization of these two subsampling schemes can be further studied and developed.

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Recycled concrete aggregate (RCA) is often used as a replacement of virgin aggregate in road foundations (base course), embankments, hot-mix asphalt, and Portland cement concrete. However, the use of RCA in exfiltration drainage systems, such as French drains, is currently prohibited in many states of the U.S. The French drain system collects water runoff from the road pavement and transfers to slotted pipes underground and then filters through coarse aggregate and geotextile. The primary concerns with using RCA as a drainage media are the fines content and the precipitation of calcium carbonate to cause a reducing in filter fabric permittivity. Additional concerns include the potential for rehydration of RCA fines. The performance of RCA as drainage material has not been evaluated by many researchers and the limited information limits its use. A literature review has been conducted on the available information related to RCA as drainage material. A survey was issued to the Departments of Transportation across the nation in regards to using RCA particularly in French drains. Some state highway agencies have reported the use of RCA as base course; however, no state reports the use of RCA in exfiltration drainage systems. This thesis describes the investigations on the performance of RCA as backfill material in French drains. RCA was tested for its physical properties including, specific gravity, unit weight, percent voids, absorption, and abrasion resistance. RCA cleaning/washing methods were also applied to evaluate the fines removal processes. The potential for RCA rehydration was iv evaluated by means of heat of hydration, pH, compressive strength, and setting time. The permeability of RCA was tested using the No. 4 gradation. Long term permeability testing was conducted to evaluate the tendency for geotextile clogging from RCA fines. Calcium carbonate precipitation was also evaluated and a procedure to accelerate the precipitation process was developed. The results show that RCA has a high abrasion value, that is, it is very susceptible to break down from abrasion during aggregate handling such as transportation, stockpiling, or placing. The most effective cleaning method was found to be pressure washing with agitation. RCA has not demonstrated the tendency to rehydrate and harden when mixed with water. The permeability test results show that the No. 4 gradation does not restrict the flow of water; the flow rate is highly dependent on the hydraulic system itself, however excessive fines can cause large reductions in permeability over time. It has been determined that No. 4 gradation of RCA can provide a suitable drainage media providing the RCA is properly treated before its use.

Active and passive transport of substances between the microcirculation in the brain and the central nervous system is regulated by the Blood-Brain Barrier (BBB). This barrier allows for chronic and acute modulation of the CNS microenvironment, and protects the brain from potentially noxious compounds carried in the circulatory system. In-vitro modeling of the BBB has become the target of much research over the past decade, as there are many unanswered questions regarding modulations in the permeability of this barrier. Additionally, the development of a practical and inexpensive model of the BBB would facilitate a much more efficient drug development process. The goal of this project is to investigate the formation of the BBB through assessment of tight junction formation and endothelial cell monolayer permeability. Accomplishment of this goal will include completion of the two primary aims of this thesis, which are 1) development of an immunohistochemical staining protocol for the labeling of tight junctional proteins, and 2) characterization of permeability across a porous membrane co-cultured with bovine aortic endothelial cells (BAECs) and C6 glioma cells. Both of these aims were met, as a reliable IF protocol for tight junctional staining was developed, and permeability values across a permeable membrane seeded with BAECs and C6s were collected. The completion of these aims has helped to accomplish the goal of investigating the formation of tight junctions in an in-vitro model of the BBB. The IF protocol that has been developed, along with the collected permeability data will aid the development of a more dynamic in-vitro model of the BBB to aid in research surrounding acute modulation of the BBB, along with facilitating a timelier drug development process.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23491号 / 工博第4903号 / 新制||工||1766(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 小池 克明, 教授 岸田 潔, 准教授 奈良 禎太 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Yes / The water permeability constant, (Kw) is one of many important parameters that affect optimal design and operation of RO processes. In model based studies, e.g.within the RO process model, estimation of Kw is therefore important. There are only two available literature correlations for calculating the dynamic Kw values. However, each of them are only applicable for a given membrane type, given feed salinity over a certain operating pressure range. In this work, we develop a time dependent neural network (NN) based correlation to predict Kw in RO desalination processes under fouling conditions. It is found that the NN based correlation can predict the Kw values very closely to those obtained by the existing correlations for the same membrane type, operating pressure range and feed salinity. However, the novel feature of this correlation is that it is able to predict Kw values for any of the two membrane types and for any operating pressure and any feed salinity within a wide range. In addition, for the first time the effect of feed salinity on Kw values at low pressure operation is reported. While developing the correlation, the effect of numbers of hidden layers and neurons in each layer and the transfer functions is also investigated.

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Yes / The development of ultra-high performance cementitious composite (UHPCC) represents a significant advancement in the field of concrete science and technology, but insufficient hydration and high autogenous shrinkage relatively increase the pores inside UHPCC, in turn, affecting the macro-performance of UHPCC. This paper, initially, optimized the pore structure of UHPCC using different types and dimensions of nanofillers. Subsequently, the pore structure characteristics of nano-modified UHPCC were investigated by the mercury intrusion porosimeter method and fractal theory. Finally, the fluid permeability of nano-modified UHPCC was estimated by applying the Katz-Thompson equation. Experimental results showed that all incorporated nanofillers can refine the pore structure of UHPCC, but nanofillers with different types and dimensions have various effects on the pore structure of UHPCC. Specifically, CNTs, especially the thin-short one, can significantly reduce the porosity of UHPCC, whereas nanoparticles, especially nano-SiO2, are more conducive to refine the pore size. Among all nanofillers, nano-SiO2 has the most obvious effect on pore structure, reducing the porosity, specific pore volume and most probable pore radius of UHPCC by 31.9%, 35.1% and 40.9%, respectively. Additionally, the pore size distribution of nano-modified UHPCC ranges from 10-1nm to 105nm, and the gel pores and fine capillary pores in the range of 3-50nm account for more than 70% of the total pore content, confirming nanofillers incorporation can effectively weaken pore connectivity and induce pore distribution to concentrate at nanoscale. Fractal results indicated the provision of nanofillers reduces the structural heterogeneity of gel pores and fine capillary pores, and induces homogenization and densification of UHPCC matrix, in turn, decreasing the UHPCC fluid permeability by 15.7%-79.2%. / The authors thank the funding supported from the National Science Foundation of China (51978127, 52178188 and 51908103), the China Postdoctoral Science Foundation (2022M720648 and 2022M710973) and the Fundamental Research Funds for the Central Universities (DUT21RC(3)039). / The full-text of this article will be released for public view at the end of the publisher embargo on 11 May 2024.

Carbon capture and related gas separation processes are critical tools in our efforts to combat climate change. While polymer membranes are seen as a central construct to achieve these goals, their performance needs further improvement to meet current sustainability objectives. It is in this context that membranes composed of polymer-grafted nanoparticles (GNPs) become highly germane. Chemically tethering the available polymer to the nanoparticle (NP) surface in GNP systems helps mitigate difficulties controlling nanoparticle dispersion common when incorporating inorganic filler NPs into polymer (i.e., mixed matrix membranes (MMMs)). Previous work has shown that gas transport in pure GNP membranes can be strongly enhanced relative to that in the corresponding neat polymer. Additionally, we demonstrated that larger gases display greater degrees of permeability enhancement than smaller ones. This work explores the underlying mechanisms governing the unique gas transport behavior observed in GNPs, with the goal of designing materials possessing superior transport properties that can be known and manipulated a priori. We begin with the identification of transport mechanisms for penetrants of different sizes through an exploration of the heterogenous nature of GNPs. In the limit of moderate-to-high grafting density (the number of chains tethered per unit surface area), the chains are overcrowded near the surface and assume extended conformations termed “polymer brushes”. These brushes comprise two regimes: (1) a dry zone of higher polymer stretching closer to the NP surface and (2) the interstitial spaces in the multibody packing of lower polymer density. We find that larger penetrants such as CH₄, with low solubilities, preferentially sorb into the interstitial spaces in the NP packing prior to diffusing through stretched chains in the dry brush region. The nature of small gas permeability enhancement, on the other hand, is due primarily to enhancements in penetrant diffusion through the stretched chain region close to the NP surface – this is because these gases have high enough solubilities to be present everywhere in the polymer layer. Such solubility differences enable the direct control over penetrant transport through the disparate regions of the polymer brush in mixed-gas environments relevant to operation. Elevated CO₂ content, through increasing feed concentrations at higher pressures, yields increased CH₄ permeability and an associated reduction in mixed-gas selectivity relative to ideal gas analogs. Additionally, high-pressure conditioning with CO₂ evidently dilates the material (due to gas adsorption) in a manner that is apparently not recoverable after a pressure decrease. An alternative handle to control penetrant transport is to manipulate the physical brush structure. Such morphological control is accomplished through variations in preparation methodology; in particular, the rate of solvent evaporation in solution-cast samples plays a significant role in dictating the final structure of the jammed colloidal glass. Utilizing high-pressure conditioning in CO₂ as a concentration quench, we combine morphological control over the brush structure with selective penetrant manipulation to dilate the overcrowded brush regime and enhance gas transport performance. Leveraging the colloidal glass nature of GNPs in this way enables the formation of quasi-equilibrium structures with even greater amounts of “free volume”. The remaining chapters focus on employing our knowledge of the gas transport mechanisms in these materials to aid in future experimental design and to form mechanically resilient materials. Implementing a simulated design-of-experiments loop, we find that a surprisingly minimal amount of experimental data is necessary to effectively model the transport properties of new materials to within practical experimental error. Selectively altering the chemistry of specific chain regions achieved slight enhancement in membrane selectivity while significantly improving material toughness and ultimate utility. Our enhanced understanding of gas transport mechanisms in polymer-grafted nanoparticle membranes will aid in the design and implementation of membranes with tunable separation performance through direct control of how penetrants transport and via morphological changes to the brush structure.