Membranes for flue gas treatment : transport behavior of water and gas in hydrophilic polymer membranes

Fossil fuel fired power plants produce electricity and in addition to that large volume flows of flue gas, which mainly contain N2, O2, and CO2, but also large quantities of water vapor. To prevent condensation of the water vapor present in this flue gas stream, water needs to be removed before emission to the atmosphere. Commercial dehydration processes such as the use of a condenser or a desiccant system have several disadvantages and membrane technology is an attractive, energy efficient alternative for dehydration of gas streams. The work presented in this thesis focuses on the characterization of the molecular gas and water vapor transport properties of two different types of polymeric membranes. The fundamental understanding of water vapor and gas transport phenomena through these materials is particularly interesting since both materials are different in their chemistry and physical state:\ud - PEBAX® is a block copolymer which shows molecular transport through the soft\ud polyethylene oxide based rubbery phase.\ud - S-PEEK (sulfonated poly ether ether ketone) shows molecular transport through an amorphous glassy phase with ionic groups present which will preferentially be\ud hydrated over the apolar matrix.\ud The two polymeric systems vary strongly in relation to polymer/vapor interactions, relaxation phenomena, and separation performance of the membranes

Sorption induced relaxations during water diffusion in S-PEEK

This paper presents an analysis of the sorption kinetics of water vapor and liquid water in the glassy polymer sulfonated poly(ether ether ketone) (S-PEEK). Sorption isotherms are determined experimentally using a gravimetric sorption balance, and the relative contributions of Fickian diffusion and relaxational phenomena are quantified as a function of the water concentration in the polymer using the model of Hopfenberg and Berens.Analysis of the sorption isotherms and determination of the sorption kinetics prove the occurrence of both Fickian sorption behavior and relaxational phenomena already at very low water concentrations in the polymer. With increasing water concentration, the relative importance of relaxation phenomena increases, whereas the relative contribution of Fickian diffusion decreases.Based on the water vapor sorption kinetics only, the Fickian diffusion coefficient increases over two orders of magnitude with increasing water vapor concentration. Taking also the diffusion kinetics from liquid water sorption experiments into account reveals a change of even three orders of magnitude of the Fickian diffusion coefficient when the water concentration in the polymer increases

Accuracy and Prognostic Role of NCCT-ASPECTS Depend on Time from Acute Stroke Symptom-onset for both Human and Machine-learning Based Evaluation.

PURPOSE We hypothesize that the detectability of early ischemic changes on non-contrast computed tomography (NCCT) is limited in hyperacute stroke for both human and machine-learning based evaluation. In short onset-time-to-imaging (OTI), the CT angiography collateral status may identify fast stroke progressors better than early ischemic changes quantified by ASPECTS. METHODS In this retrospective, monocenter study, CT angiography collaterals (Tan score) and ASPECTS on acute and follow-up NCCT were evaluated by two raters. Additionally, a machine-learning algorithm evaluated the ASPECTS scale on the NCCT (e-ASPECTS). In this study 136 patients from 03/2015 to 12/2019 with occlusion of the main segment of the middle cerebral artery, with a defined symptom-onset-time and successful mechanical thrombectomy (MT) (modified treatment in cerebral infarction score mTICI = 2c or 3) were evaluated. RESULTS Agreement between acute and follow-up ASPECTS were found to depend on OTI for both human (Intraclass correlation coefficient, ICC = 0.43 for OTI < 100 min, ICC = 0.57 for OTI 100-200 min, ICC = 0.81 for OTI ≥ 200 min) and machine-learning based ASPECTS evaluation (ICC = 0.24 for OTI < 100 min, ICC = 0.61 for OTI 100-200 min, ICC = 0.63 for OTI ≥ 200 min). The same applied to the interrater reliability. Collaterals were predictors of a favorable clinical outcome especially in hyperacute stroke with OTI < 100 min (collaterals: OR = 5.67 CI = 2.38-17.8, p < 0.001; ASPECTS: OR = 1.44, CI = 0.91-2.65, p = 0.15) while ASPECTS was in prolonged OTI ≥ 200 min (collaterals OR = 4.21,CI = 1.36-21.9, p = 0.03; ASPECTS: OR = 2.85, CI = 1.46-7.46, p = 0.01). CONCLUSION The accuracy and reliability of NCCT-ASPECTS are time dependent for both human and machine-learning based evaluation, indicating reduced detectability of fast stroke progressors by NCCT. In hyperacute stroke, collateral status from CT-angiography may help for a better prognosis on clinical outcome and explain the occurrence of futile recanalization

Correction to: Accuracy and Prognostic Role of NCCT-ASPECTS Depend on Time from Acute Stroke Symptom-onset for both Human and Machine-learning Based Evaluation.

PURPOSE: We hypothesize that the detectability of early ischemic changes on non-contrast computed tomography (NCCT) is limited in hyperacute stroke for both human and machine-learning based evaluation. In short onset-time-to-imaging (OTI), the CT angiography collateral status may identify fast stroke progressors better than early ischemic changes quantified by ASPECTS. METHODS: In this retrospective, monocenter study, CT angiography collaterals (Tan score) and ASPECTS on acute and follow-up NCCT were evaluated by two raters. Additionally, a machine-learning algorithm evaluated the ASPECTS scale on the NCCT (e-ASPECTS). In this study 136 patients from 03/2015 to 12/2019 with occlusion of the main segment of the middle cerebral artery, with a defined symptom-onset-time and successful mechanical thrombectomy (MT) (modified treatment in cerebral infarction score mTICI = 2c or 3) were evaluated. RESULTS: Agreement between acute and follow-up ASPECTS were found to depend on OTI for both human (Intraclass correlation coefficient, ICC = 0.43 for OTI < 100 min, ICC = 0.57 for OTI 100–200 min, ICC = 0.81 for OTI ≥ 200 min) and machine-learning based ASPECTS evaluation (ICC = 0.24 for OTI < 100 min, ICC = 0.61 for OTI 100–200 min, ICC = 0.63 for OTI ≥ 200 min). The same applied to the interrater reliability. Collaterals were predictors of a favorable clinical outcome especially in hyperacute stroke with OTI < 100 min (collaterals: OR = 5.67 CI = 2.38–17.8, p < 0.001; ASPECTS: OR = 1.44, CI = 0.91–2.65, p = 0.15) while ASPECTS was in prolonged OTI ≥ 200 min (collaterals OR = 4.21,CI = 1.36–21.9, p = 0.03; ASPECTS: OR = 2.85, CI = 1.46–7.46, p = 0.01). CONCLUSION: The accuracy and reliability of NCCT-ASPECTS are time dependent for both human and machine-learning based evaluation, indicating reduced detectability of fast stroke progressors by NCCT. In hyperacute stroke, collateral status from CT-angiography may help for a better prognosis on clinical outcome and explain the occurrence of futile recanalization. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s00062-021-01110-5) contains supplementary material, which is available to authorized users

Comparing Poor and Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy in Acute Ischemic Stroke

Outcome prediction after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO) is commonly performed by focusing on favorable outcome (modified Rankin Scale, mRS 0–2) after 3 months but poor outcome representing severe disability and mortality (mRS 5 and 6) might be of equal importance for clinical decision-making

First application of dynamic oxygen-17 magnetic resonance imaging at 7 Tesla in a patient with early subacute stroke.

Dynamic oxygen-17 (17O) magnetic resonance imaging (MRI) is an imaging method that enables a direct and non-invasive assessment of cerebral oxygen metabolism and thus potentially the distinction between viable and non-viable tissue employing a three-phase inhalation experiment. The purpose of this investigation was the first application of dynamic 17O MRI at 7 Tesla (T) in a patient with stroke. In this proof-of-concept experiment, dynamic 17O MRI was applied during 17O inhalation in a patient with early subacute stroke. The analysis of the relative 17O water (H217O) signal for the affected stroke region compared to the healthy contralateral side revealed no significant difference. However, the technical feasibility of 17O MRI has been demonstrated paving the way for future investigations in neurovascular diseases

Combined Perfusion and Permeability Imaging Reveals Different Pathophysiologic Tissue Responses After Successful Thrombectomy.

Despite successful recanalization of large-vessel occlusions in acute ischemic stroke, individual patients profit to a varying degree. Dynamic susceptibility-weighted perfusion and dynamic T1-weighted contrast-enhanced blood-brain barrier permeability imaging may help to determine secondary stroke injury and predict clinical outcome. We prospectively performed perfusion and permeability imaging in 38 patients within 24 h after successful mechanical thrombectomy of an occlusion of the middle cerebral artery M1 segment. Perfusion alterations were evaluated on cerebral blood flow maps, blood-brain barrier disruption (BBBD) visually and quantitatively on ktrans maps and hemorrhagic transformation on susceptibility-weighted images. Visual BBBD within the DWI lesion corresponded to a median ktrans elevation (IQR) of 0.77 (0.41-1.4) min-1 and was found in all 7 cases of hypoperfusion (100%), in 10 of 16 cases of hyperperfusion (63%), and in only three of 13 cases with unaffected perfusion (23%). BBBD was significantly associated with hemorrhagic transformation (p < 0.001). While BBBD alone was not a predictor of clinical outcome at 3 months (positive predictive value (PPV) = 0.8 [0.56-0.94]), hypoperfusion occurred more often in patients with unfavorable clinical outcome (PPV = 0.43 [0.10-0.82]) compared to hyperperfusion (PPV = 0.93 [0.68-1.0]) or unaffected perfusion (PPV = 1.0 [0.75-1.0]). We show that combined perfusion and permeability imaging reveals distinct infarct signatures after recanalization, indicating the severity of prior ischemic damage. It assists in predicting clinical outcome and may identify patients at risk of stroke progression

First application of dynamic oxygen-17 magnetic resonance imaging at 7 Tesla in a patient with early subacute stroke

Dynamic oxygen-17 (17O) magnetic resonance imaging (MRI) is an imaging method that enables a direct and non-invasive assessment of cerebral oxygen metabolism and thus potentially the distinction between viable and non-viable tissue employing a three-phase inhalation experiment. The purpose of this investigation was the first application of dynamic 17O MRI at 7 Tesla (T) in a patient with stroke. In this proof-of-concept experiment, dynamic 17O MRI was applied during 17O inhalation in a patient with early subacute stroke. The analysis of the relative 17O water (H217O) signal for the affected stroke region compared to the healthy contralateral side revealed no significant difference. However, the technical feasibility of 17O MRI has been demonstrated paving the way for future investigations in neurovascular diseases