Cyp46a1−/− mice on high fat cholesterol-enriched diet from 1 to 14 months of age (control group) and at 12 months of age, started to treat a group of these animals with HPCD until the age of 14 months. We found that as compared with mature and regular chow-fed Cyp46a1−/− mice, control group had about 6-fold increase in the retinal total cholesterol content, focal cholesterol and lipid deposition in the photoreceptor-Bruch’s membrane region, and retinal macrophage activation. In addition, aged animals had cholesterol crystals at the photoreceptor-retinal pigment epithelium interface and changes in the Bruch’s membrane ultrastructure. HPCD treatment mitigated all these manifestations of retinal cholesterol dyshomeostasis and altered the abundance of six groups of proteins . Thus, aged Cyp46a1−/− mice on high fat cholesterol-enriched diet revealed pathological changes secondary to retinal cholesterol overload and supported further studies of HPCD as a potential therapeutic for age-related macular degeneration and diabetic retinopathy associated with retinal cholesterol dyshomeostasis.CYP46A1 is a CNS-specific enzyme, which eliminates cholesterol from the brain and retina by metabolism to 24-hydroxycholesterol, thus contributing to cholesterol homeostasis in both organs. 2-Hydroxypropyl-β-cyclodextrin (HPCD), a Food and Drug Administration-approved formulation vehicle, is currently being investigated off-label for treatment of various diseases, including retinal diseases. HPCD was shown to lower retinal cholesterol content in mice but had not yet been evaluated for its therapeutic benefits. Herein, we put  The retina is a multilayered neuronal tissue in the posterior part of the eye that absorbs light for subsequent image generation by the brain. Emerging evidence suggest that increased retinal cholesterol levels contribute to the pathogenesis of age-related macular degeneration (AMD) and diabetic retinopathy, two major blinding diseases , 2, 3. CCyp46a1−/− mice fed cholesterol-free regular rodent chow (contains 5% fat). These animals had almost a 2-fold increase in the levels of retinal cholesterol  , a metablesterol . In addi as well .Abca4−/−Rdh8−/− mice, methyl β-cyclodextrin was injected intravitreally and reduced the amount of lipofuscin, a byproduct of the visual cycle  is approved by the Food and Drug Administration as a drug delivery vehicle as this cyclic oligosaccharide can encapsulate hydrophobic compounds, thus enhancing their solubility, stability, and bioavailability , 13, 14.al cycle . In C57Bme point . Finallyme point , 27. Thume point , the bloCyp46a1−/− mice, which were put at 1 month of age on a chow high in fat (21% by weight) and enriched with cholesterol (0.2% by weight), that is, resembling a Western diet. In addition, to further increase human relevance, we aged Cyp46a1−/− mice to 12 months and started HPCD treatment while mice continued to receive high fat cholesterol-enriched (HFCE) diet. Notably, in our assessments of the retinal treatment effects, we focused on those that could provide novel mechanistic insights and could be of therapeutic value. We obtained data suggesting that aged Cyp46a1−/− mouse on HFCE diet is a suitable model for evaluating therapeutically relevant HPCD treatment effects. Also, this study expanded our understanding of the pathological retinal changes because of retinal cholesterol overload secondary to impaired cholesterol metabolism, diet, and age and demonstrated that HPCD treatment can mitigate these pathological changes.In the present work, we continued our investigation of HPCD as a potential pharmaceutical for retinal diseases associated with retinal cholesterol dyshomeostasis . We usedCyp46a1−/− mice on the C57BL/6J;129S6/SvEv background were used. These genotype was provided by Dr David Russell  and generated as described -dark cycle with food and water ad libitum. Before weaning, mice were fed regular rodent chow, and after weaning at 1 month of age, they were put on an HFCE diet . All animal experiments were approved by Case Western Reserve University IACUC and conformed to the recommendations of the American Veterinary Association Panel on Euthanasia. Littermates were selected from the pool of all available animals and randomly assigned to either the control group or the treatment group, which were matched by size and sex. Sample size was based on previous experience. The investigators were mostly not blinded with respect to HPCD treatment as they were involved in both animal treatment and subsequent retinal assessments. Only when CCs were imaged in the retina and then counted, investigators were blinded with respect to HPCD treatment. Half of retinal assessments was quantitative and hence could not be affected by investigators’ bias as all data were used and apparent outliers were not excluded. The nonquantitative half of the assessments pertained to histochemistry, immunohistochemistry, and electron microscopy (transmission electron microscopy [TEM] or scanning electron microscopy [SEM]). To minimize investigators’ bias in these assessments, retinal regions that were compared between the control and treatment groups were matched by the retinal location. For SEM, the whole retina was scanned, and equal number of pictures was taken at the same locations in untreated and treated retinas. Images were masked and analyzed in a blinded fashion.Fourteen-month-old female and male Mice were treated with 30% HPCD  from 12 to 14 months of age. This solution was prepared by diluting under the hood the 45% HPCD stock in sterile water for injections . The dilution was with phosphate-buffered saline sterilized by 0.22 μm filtration . HPCD was usually administered in the morning by subcutaneous injections at a 2 g/kg of body weight dose twice a week for 2 months, the treatment paradigm chosen based on our previous study .Mice were fasted overnight and the following morning were euthanized. Sterols were quantified as described , 30 by iThree dyes were used as described , 32. FluMouse eyes were enucleated and perforated with a 30-gauge needle 1 mm posterior to the limbus. Eyes were placed in freshly prepared 4% paraformaldehyde and kept at room temperature for 8–16 h. Eyes were then transferred to a refrigerator and stored at 4°C. Prior to SEM, eyes were placed in distilled water, lens and vitreous were removed, and eye cup containing retina/retinal pigment epithelium (RPE) was placed in a 24-well dish with distilled water. Retinas were cut with a double-edged razor blade, and the samples obtained were subjected to two different treatment protocols. Samples that we denoted “processed” were fixed for 1 h in 0.1 M sodium phosphate buffer, pH 7.4, containing 1% osmium tetroxide. These samples were next rinsed for 30 min in water and sequentially dehydrated for 15 min in each 25%, 50%, 75%, and 95% aqueous ethanol solutions followed by the three 15 min incubations in 100% ethanol. Samples were critical point dried in a Leica Microsystems model EM CPD300 critical point dryer  using carbon dioxide as the transitional fluid. Samples that we denoted “unprocessed” were obtained after retinas were placed in vapor fixation with 2% osmium tetroxide for at least 48 h. These samples were then mounted on aluminum stubs using high vacuum carbon abs  and coated with gold (≈30 nm thickness) in an Emscope Sputter Coater model SC 500  purged with argon gas. All samples were analyzed by a JEOL 6610LV (tungsten hairpin emitter) scanning electron microscope , and the identified crystals were then evaluated for elemental composition using energy-dispersive X-ray spectroscopy  . ElementThis was carried out as described  using thThe preparation of frozen retinal sections and subsequent incubations with rabbit polyclonal anti-Iba1  antibody  and Alexa Fluor 647-conjugated goat anti-rabbit IgG  were as described .P ≥ 0.05) in abundance between the treatment and control groups were excluded from the proteomics analysis as are the proteins with less than a 1.2-fold change in their relative abundance even if this change was significant. Protein grouping was based on a biological process as described by UniProt as well as in the literature.The relative protein abundance in the retina was assessed by the label-free approach as described , which wt-test. The sample size (n) is indicated in each figure or figure legend, which also include the breakdown of female and male animals. Statistical significance was defined as ∗P ≤ 0.05, ∗∗P ≤ 0.01, and ∗∗∗P ≤ 0.001. The data and statistical analysis comply with the recommendations on experimental design and analysis in pharmacology , UC, and EC was 181, 159, and 22 nmol/mg protein, respectively  , UC (123 vs. 159 nmol/mg protein), and EC (12 vs. 22 nmol/mg protein), and represented a -46, -36, and -10 nmol/mg protein change, respectively. The retina of mature (6–12 months old) wild-type mice on regular rodent chow usually contains 34–37, 29–31, and 6 nmol/mg protein of TC, UC, and EC, respectively  because of the high basal levels of retinal cholesterol.In control ectively . These vprotein) . Howeverectively , 40. AccTo gain insight into whether HPCD administration altered retinal cholesterol homeostasis, retinal content of lathosterol, desmosterol, 27-hydroxycholesterol (27HC), and 5-cholestenoic acid (27COOH) was measured . LathostCyp46a1−/− mice, the filipin fluorescence indicative of UC was bright in all retinal layers and was particularly visible in the apical and basal plasma membranes of the RPE  in contted mice .Fig. 2HPCyp46a1−/− mice had a similar pattern of the retinal Oil Red O staining with the POS being the most intensively stained layer in both groups  was assessed by retinal labeling with Oil Red O , 34. Conh groups D, H. TheCyp46a1−/− mice on HFCE diet as this retina is overloaded with cholesterol  and upregulating the proinflammatory gene expression in response to cholesterol overload , 51. Maclar chow . Therefoh Bodipy A–C, E–G,h Bodipy .Fig. 4HPCyp46a1−/− mice, the Iba1-positive cells  were found in all layers , a known macrophage function , which can be placed in six groups based on a Gene Ontology (http://geneontology.org/) biological process (Cyp46a1−/− mice on HFCE diet and four included the same processes affected previously in HPCD-treated C57BL/6J (wild-type mice) and Cyp27a1−/−Cyp46a1−/− mice  as well as an upregulation of Ccl2, Cox-2, Cxcl1, iNos, Il-1β, Il-6, and Tnfα, that is, a set of the proinflammatory genes, which is usually transrepressed by 24HC activation of LXRs   or increased by genetic ablation of the two cholesterol-related genes (/− mice) .Cyp46a1−/− mice on a chow with the elements of a western diet (high fat and enriched with cholesterol) and aged them until 12 months to further exacerbate their retinal phenotype. The retinal levels of TC in control Cyp46a1−/− mice almost tripled, that is, became 181 nmol/mg protein  on both sides of the RPE, which was an advantage as compared with available mouse models that exhibit EC accumulation only in BM  surrounded by a monolayer of amphipathic lipids (phospholipids and UC) and LD-associated proteins . When th the POS , and CCs the POS . Accordi the POS  could ei the POS .Cyp46a1−/− mice (CCs are avidly phagocytized by macrophages , consist−/− mice . However−/− mice , 50, 53.−/− mice . In addi−/− mice , 88.Cyp46a1−/− mice (The macrophage/microglia activation was reduced in HPCP-treated −/− mice , possibl−/− mice  and/or d−/− mice . Regardl−/− mice , 91. Sim−/− mice , 93.Finally, TEM, along with Oil Red O and Bodipy staining, showed improvements after HPCD treatment in the ultrastructure of the RPE-BM region , which iCyp46a1−/− mice on HFCE diet were used as a model of retinal cholesterol dyshomeostasis and cholesterol accumulations on both sides of the RPE. This model received subcutaneous injections of HPCD, which elicited multiple and therapeutically relevant effects. The observed effects included homeostatic responses leading to a reduction of the overall retinal cholesterol excess as well as decreases in focal cholesterol depositions in the pathophysiologically relevant AMD and diabetic retinopathy locations. Our animal model was discovered to have CCs at the POS-RPE interface, an important finding that enhances our understanding of the pathological mechanisms leading to retinal damage. The CC number was decreased after HPCD treatment leading to a reduction in retinal microphage/microglia activation and infiltration of these cells to the POS-RPE interface. Overall, this study supports further investigation of HPCD as a therapeutic agent for retinal diseases associated with retinal cholesterol dyshomeostasis.In conclusion, aged The data that support the findings of this study are contained within the article.The authors declare that they have no conflicts of interest with the contents of this article.


R2 = 0.82–0.84) in predicting cardiovascular strain, particularly at a group mean level (R2 = 0.97). The development of the CVR Model is aimed at providing the Fiala thermal Physiology & Comfort (FPC) Model and other complex thermophysiological models with improved estimations of cardiac strain and exercise tolerance, across a range of individuals during acute exposure to environmental stressors.The present research describes the development and validation of a cardiovascular model (CVR Model) for use in conjunction with advanced thermophysiological models, where usually only a total cardiac output is estimated. The CVR Model detailed herein estimates cardio-dynamic parameters , regional blood flow, and muscle oxygen extraction, in response to rest and physical workloads, across a range of ages and aerobic fitness levels, as well as during exposure to heat, dehydration, and altitude. The model development strategy was to first establish basic resting and exercise predictions for cardio-dynamic parameters in an “ideal” environment . This basic model was then advanced for increasing levels of altitude, heat strain, and dehydration, using meta-analysis and reaggregation of published data. Using the estimated altitude- and heat-induced changes in maximum oxygen extraction and maximum cardiac output, the decline in maximum oxygen consumption at high altitude and in the heat was also modeled. A validation of predicted cardiovascular strain using heart rate was conducted using a dataset of 101 heterogeneous individuals  during rest and exercise in the heat and at altitude, demonstrating that the CVR Model performs well , as well as a method to evaluate key principles influencing exercise- and thermoregulation in humans. Multisegmental modeling of human thermoregulation provides an established predictive tool for estimating changes in body temperature, as well as metabolic, vascular, sudomotor, and perceptual responses to thermal stress . Based oThe motivation for the present research was to advance the capabilities of the FPC Model and other multisegmental models of human thermoregulation to predict cardiovascular responses and associated constraints related to intense exercise and exposures to challenging environmental conditions. Although the new “Cardiovascular Response Model” (CVR Model) was developed as a separate, stand-alone, predictive tool, the underlying concept facilitates its implementation as a submodel in advanced thermophysiological simulation model networks. Such an incorporation bears prospects of extending the applicability of thermophysiological models to demanding athletic, military, occupational, and public health  settings, by providing a detailed description of the strains and limitations experienced by humans operating in such conditions. Predictions of thermophysiological body states may then be performed taking into account the upper bounds of cardiovascular factors, including maximum heart rate, maximum cardiac output, or maximum muscle oxygen extraction. This in turn provides a capacity to use thermophysiological models in the identification and prevention of occupational injury or harm in demanding environmental settings. A further benefit of incorporating cardiovascular parameters is the possibility for wide-ranging model performance testing against readily available, field-based validation metrics (such as heart rate), as opposed to limited and more complex laboratory measures, such as body temperature, sweat rates, or cardiac output. This in turn provides an additional means by which thermophysiological models, as well as our basic understanding of exercise- and thermoregulation in humans, can be mathematically validated.The primary purpose of the present research was to describe a cardiovascular model, i.e., the CVR Model, for the estimation of cardiovascular responses  to rest and exercise in various environmental conditions. The secondary and tertiary aim of the research was to devise a model that would allow subsequent integration into existing thermophysiological models and finally validate the CVR Model for its capacity to predict heart rate responses in healthy humans.o2 is oxygen consumption (L·min−1); CO is cardiac output (L·min−1); [blood]−1); SV stroke volume (L); HR heart rate (beats·min−1).The CVR Model estimates cardiovascular responses  to physical workloads, as well as by changes in age, aerobic fitness, heat strain, dehydration, and altitude. The model has been developed based on two fundamental physiological equations, i.e., the Fick principle (2 ([blood]−1), and venous blood, i.e., pulmonary artery O2 ([blood]−1), respectively:The arterial blood oxygen extraction is defined as the difference between the oxygen content of arterial blood, i.e., pulmonary vein OUsing the aforementioned equations, the general strategy was to first develop a “basic” CVR Model that establishes resting and exercise predictions for cardiac output (CO), stroke volume (SV), and heart rate (HR) parameters in the “ideal” laboratory environment, e.g., neutral temperature, sea-level, and low carbon dioxide conditions. Note that the term “basic” is used throughout this research paper to describe cardiovascular parameters that are not yet modulated for environmental strain .o2max). Using the predicted modulations of maximum SV (SVmax) and maximum cardiac output (COmax) in the heat, as well as reduction in o2max observed under heated and/or high-altitude conditions were modeled. To complete the CVR Model development, the redistribution of regional blood flows to different tissues was estimated.Upon establishing the fundamental relationships of the basic CVR Model, changes in both resting and maximum oxygen extraction at the muscle  and 100%, V̇o2max, i.e., it is the fraction of V̇o2max reserve (hereafter termed: FV̇o2max(reserve)). To calculate V̇o2rest, resting energy expenditure was estimated using the Mifflin–St Jour equation, then converted from kcal·day−1 to L·min−1 by rearranging the Weir formula, assuming a respiratory exchange ratio of 0.7  or exercise (L·min−1); RER is a respiratory exchange ratio of 0.7; and V̇o2max is the basic maximum oxygen consumption of that individual (L·min−1).In the CVR Model, the workload is defined as fraction of the difference between resting V̇o of 0.7 , 13. values, which are needed to estimate cardiodynamic responses to rest and exercise, and to define cardiac limitations to exercise. Thus, it was first necessary to develop an independent cardiac output model, which represents the cardiac function in response to rest and exercise in moderate temperature, well-ventilated environments. As noted earlier, these parameters are termed “basic,” as they are not yet modulated for environmental strains .Although several existing thermoregulatory models contain cardiac output metrics per se, this value is typically derived from the tissue oxygen needs, i.e., metabolic rate, assuming a fixed muscle oxygen extraction of 200 mL Oof blood , 6, and of blood . Neithero2max is a function of max  and absolute V̇o2max (L·min−1) was examined, with a view using V̇o2max as a predictor variable for SVmax. Absolute V̇o2max  was used as COmax (and thereby SVmax) are dependent on fitness level and body mass, as opposed to a mass normalized fitness level per se.The Fick principle dictates that V̇o2max and SVmax were aggregated from nine research studies  spanning a range of ages , sexes, fitness levels, and training statuses. Global group mean V̇o2max in these studies was 3.6 ± 1.1 L·min−1 (53.5 ± 16.5 mL·kg−1·min−1), ranging between 1.5 and 5.57 L·min−1 (22.2–84.1 mL·kg−1·min−1) (max is explained by changes in V̇o2max (max (o2max was developed.Data for V̇1·min−1) –22. Of t1·min−1) , carbon 1·min−1) , 22, wit1·min−1) . The res V̇o2max A. Using n = 206) to calculate resting SV  was used .The same process was then conducted on a reduced data set of 20 population groups , through modulations in cardiac parasympathetic and sympathetic activity (o2max) on HRrest, data from 12 studies were aggregated and re-analyzed, including both cross-sectional and longitudinal HRrest data  (o2max of 36.2 ± 10.3 mL·kg−1·min−1 (range: 19.0–60.9 mL·kg−1·min−1) and a HRrest values of 67 ± 10 beats·min−1 (range: 55–92 beats·min−1)  –36. Thess·min−1) –36.max, mass normalized V̇o2max  provided a better estimated of HRrest than absolute V̇o2max. A mild linear relation was observed, indicating that 44% of the variance in HRrest is explained by changes in body mass corrected V̇o2max ; and age is time passed since birth (years). HRmax is taken directly from Tanaka et al. , COmax, and intensity-dependent CO, as detailed as follows:max is the maximum stroke volume  indicates a strong correlation between SVmax (mL·beat−1) and COmax (L·min−1), with the majority (94%) of the variability in SVmax accounted for by changes in COmax (max was accounted for by changes in V̇o2max (L·min−1) (COmax = 4.20 + 5.41·V̇o2max) and vice versa. This indicates only 18% of the variability in V̇o2max is accounted for by changes in Using these equations, COin COmax D and vic2diffmax –22.o2max  for any given mechanical work performed at altitude, when compared with the same mechanical work performed at sea level  .max ; COrest the basic resting cardiac output .Thus, to effectively model changes in cardiovascular parameters at altitude, it is first necessary to estimate a basic  maximum oxygen extraction value , that this decline fits the function: decline in V̇o2max = −0.007·km2 –0.03·km. On the basis that Fulco et al. (1) the widest range of altitudes and 2) the largest number of observations (n = 67), this more complex curvilinear function was used to modulate the CVR Model for altitude. Using the Fulco et al. . Of note, both mean skin (Tskin) and core temperature (Tcore) increased nonlinearly, indicating neither variable on its own is the key causative factor behind the increase in SV during passive heating at rest . The rel et al. , 53 and l et al. , indicatntensity B. Much l−1 increase in Tbody . It is possible that individuals less adapted to physical exercise would exhibit a greater sensitivity to increases in Tbody, i.e., hyperthermia independently of dehydration per se. Thus, a simplified method of integrating dehydration percentage into the cardiac heat sensitivities, in which ΔTbody and dehydration contribute additively, was also explored  Tbody; 2) dehydration; and 3) the synergistic interaction between these factors  to the decline in SV, multiple linear regression without a constant was conducted on the SV data presented by González-Alonso et al. (r2 = 0.99), distributed over each parameter according to their standardized regression coefficients , relative to the sum of the standardized regression coefficients (sum = 1.072)  . The reso et al. .Tbody when using the heat sensitivities defined in Eqs. 23–26 thus, it was necessary to first normalize the decline in SV reported by González-Alonso et al.  above a reference of point of 36.54°C, calculated as 0.2·Tskin + 0.8·Tcore – 36.54  × 100. Note: A CHSI value of 3.9 provides the equivalent change in stroke volume (and cardiac output) to that of 3.9°C increase in mean body temperature when using the heat sensitivities defined in To scale heat-induced changes in SV and CO according to the relative contributions of dehydration, hyperthermia, and the synergism between these factors, a cardiac heat strain index (CHSI) was proposed. This CHSI was organized to directly replace Δo et al.  to rangeTbody independently of dehydration per se, a simple equal contribution from ΔTbody and dehydration was used (Tbody is the increase in mean body temperature (°C) above a reference of point of 36.54°C, calculated as 0.2·Tskin + 0.8·Tcore – 36.54  × 100.To develop the alternative additive CHSI model, in which cardiac strain exhibits a sensitivity to increases in max  heating, both SVrest and HRrest must increase to compensate the higher requirement for COrest. In contrast, due to the equal sensitivity of COmax and SVmax to heat, these equations mandate that the decline in COmax is entirely accounted for by changes in SVmax  is recalculated in rest is the basic model resting cardiac output value  the cardiac output when modulated for altitude only (The respective changes in CO and COEqs. 23–28), the heat, dehydration, and altitude modulated SV, CO, and HR are then calculated as:max is the maximum heart rate  is the heat, dehydration, and altitude modulated value of the CVR Model’s basic HR  reflects the heat, dehydration, and altitude modulated value for the CVR Model’s basic CO  is the heat, dehydration, and altitude modulated of the CVR Model’s basic SV  in the present CVR model is based on equations derived from a series of basic physiological studies examining cardiac function. Thus, it is useful to compare the outcomes of this prediction to other empirical data examining measured changes in V̇o2max during exercise in the heat. Aggregation of study data by Périard and Racinais (o2max of 11.9%·C−1 increase in Tbody (R2 = 0.91). Using the Havenith et al. , the CVR Model with the additive CHSI predicted an almost identical decline in V̇o2max to the 11.9%·°C−1 observed by Périard and Racinais .It is important to note that the effect of heat and dehydration on V̇Racinais  indicateRacinais  2 – 1.79·(CO/COmax) + 1.06, R2 = 0.99) with the relative demand placed on the heart , irrespective of the environmental condition in which exercise was performed  is the cardiac output modulated for heat, dehydration, and altitude /The CVR Model provides a refined estimate of CO with increasing exercise intensity, altitude, body temperature, and dehydration. The model can therefore also be used to estimate the proportion of CO required for regional blood perfusion rates in skin tissue, active muscles, and visceral organs during exercise, across different environmental conditions. To achieve this, the required core blood flow (CoreBF) at rest and during exercise was first estimated. While Stolwijk  estimate Leggett  estimate. Rowell , however. Rowell . Followi. Rowell , CoreBF erformed . Thus, t and CO). It should be recognized that when coupling thermoregulatory models with the CVR model, precise SkBF estimation is paramount to modeling heat transfer within the body, and between the body and the external environment. Thus, the calculation of SkBF  the cardiac output modulated for heat, dehydration, and altitude  the cardiac output when modulated for altitude only (Skin blood flow (SkBF) was estimated using an assumed resting, thermoneutral skin blood flow of 5% of cardiac output , plus th  is the cardiac output modulated for heat, dehydration, and altitude  was also calculated by subtracting SkBF ; −1); and MusBF the active muscle blood flow  active muscle oxygen extraction , CO, Tbody, dehydration that is greater than the maximum value achievable or tolerable, the model reports that the exercise is no longer aerobically sustainable, and task failure occurs. Lower HRmax thresholds and/or body temperature thresholds can also be applied to simulate, e.g., occupational work tolerability.An additional utility of the present model is the capacity to estimate the sustainability of a physical task. When the exercising workload necessitates either V̇o2max, age, body mass, height, and sex as well as information on the actual exposure including altitude, exercise time, workload V̇o2, total exercise time, the total body mass loss, and Tbody. For all validation purposes, progressive dehydration level was approximated by linear interpolation using The key inputs used for the validation of the CVR Model were personal characteristics of the simulated individual(s), including baseline V̇o2max. The results show the change in SV and CO  , during low-intensity cycling at a fixed intensity of 60 W, for 1 h, in a warm-humid environment   using low-intensity cycling at a fixed power output of 60 W, for 1 h, in a warm-humid environment . The second exercise modality was conducted by a population of 24 young individuals  at rest, followed by cycling at 25%, then 45% V̇o2max, in three different climates . These data also include 30-min rest in the experimental climate, followed by 60-min exercise, with data reported every 30 min . Both the synergistic and additive  was conducted using a data set of heterogeneous individuals during rest and exercise in the heat , 11. TwoR2 = 0.82–0.84) between measured and predicted HR, on the individual data and when using both the additive and synergistic models. When the data were stratified into group means by aerobic fitness level  and by climate , the agreement between measured and predicted HR is increased further (R2 = 0.97), but was underestimated across all fitness levels and climates  during rest and exercise in a cool high-altitude environment . The data included 30-min rest in the experimental climate, followed by 30-min low-intensity cycling at 35% V̇o2max and 30-min moderate-intensity cycling at 50% V̇o2max. Rest (5 HR samples) and each exercise intensity (each another 5 HR samples) was conducted once at sea level, and twice at 4,000 m altitude. At each visit to 4,000 m altitude, individuals either performed a workload that corresponds to 35% and 50% sea-level V̇o2max (same absolute workload), or 35% and 50% altitude V̇o2max (same relative workload). The data were reported for every 5 min, thereby totaling 45 heart rate data points per individual across normoxia and hypoxia, as well as across relative and absolute workloads . For the validation, progressive dehydration level was again approximated by linear interpolation over the exercise period using Eq. 37 and used in the calculation of the additive CHSI (Eq. 22).A validation of the CVR Model’s HR prediction was also conducted using a smaller data set of individuals at rest and during exercise at altitude . The data set examined cardiovascular and thermoregulatory responses in six males  between measured and predicted HR, which was increased further when the data were stratified by altitude and workload type . The validation shows that the model accounts well for the increase in HR induced by ascent to altitude.The results of the validation indicate a strong relationship , as well as increasing the HRresty-intercept by 10 beats·min−1  largely eliminates this underestimation. Although minor adjustments will ultimately serve to rectify estimation errors, it is proposed that further validations should be conducted to ascertain the error consistency across data sets. Whether the error is maintained when integrated with an advanced thermophysiological model and/or combined with a continuous measurement of fluid loss during rest and exercise in the heat will be an important question for future validation work.Another observation from the heat exposure validations was that the absolute prediction was an underestimation of HR across all fitness levels . The mosratories –54, and/As noted earlier, the present CVR Model would benefit from being combined with advanced thermophysiological models providing appropriate temporal input to which the CVR model can respond. If successfully integrated, such combined models would provide a convenient and inexpensive method for evaluating human cardiac strain under intense physical workloads, and stressful environmental conditions.o2max) are imposed, therefore allowing an estimation of whether a given exercise load is attainable. As such, utility of future models could be extended to simulate athletes’ physiological responses during running exercise in a range of environmental conditions, as well as the basis for interindividual prediction of work tolerability, occupational safety, and exercise performance modeling.A unique aspect of the present CVR model, as well as any future combined CVR-thermophysiological models, is that upper limits on HR, SV, and CO . This differs from the current method of assuming a predefined requirement for muscle oxygen extraction Basic arterial blood O2 extraction modulated for altitudeArterial blood O2 extraction Basic maximum arterial blood O2 extraction modulated for altitudeMaximum arterial blood O2diffrest Resting arterial blood O2 extraction AVO2 extraction modulated for altitudeArterial blood OBasicTerm to describe variables not yet modulated for environmental strains.CHSICardiac heat strain indexCOBasic cardiac outputCOBasic cardiac output modulated for heat, dehydration, & altitudeCOBasic cardiac output modulated for altitudemaxCOBasic maximum cardiac outputBasic maximum cardiac output modulated for heat, dehydration, & altituderestCOBasic resting cardiac outputBasic resting cardiac output modulated for heat, dehydration, & altitudeCoreBFCore (major organs and viscera) blood flowCVR ModelCardiovascular response ModelFPC ModelFiala Thermal Physiology & Comfort Model2rest and V̇o2maxWorkload as a fraction of the difference between V̇o2rest and V̇o2max when corrected for cardiac output changes associated with heat and altitudeWorkload as a fraction of the difference between V̇oHRBasic heart rateHRHeart rate modulated for heat, dehydration, & altitudemaxHRBasic maximum heart raterestHRBasic resting heart rateResting heart rate modulated for heat, dehydration, & altitudeMusBFActive leg muscle blood flowSkBFSkin blood flowSVBasic stroke volumeSVBasic stroke volume modulated for heat, dehydration, & altitudemaxSVBasic maximum stroke volumeBasic maximum stroke volume modulated for heat, dehydration, & altituderestSVBasic resting stroke volumeBasic resting stroke volume modulated for heat, dehydration, & altitudeTbodyTskin + 0.8 × TcoreMean body temperature (°C) is calculated as: 0.2 × TcoreCore temperatureTskinMean skin temperature2maxV̇oBasic maximum oxygen consumptionBasic maximum oxygen consumption modulated for heat, dehydration, & altitude2restV̇oBasic resting oxygen consumptionThe research presented was cofunded by the Adidas Sport Science Team, Germany, and the Environmental Ergonomics Research Center, Loughborough University, UK.No conflicts of interest, financial or otherwise, are declared by the authors.A.L., D.F., C.H., and G.H. conceived and designed research; A.L. performed experiments; A.L., D.F., and G.H. analyzed data; A.L., D.F., C.H., and G.H. interpreted results of experiments; A.L. prepared figures; A.L. drafted manuscript; A.L., D.F., C.H., and G.H. edited and revised manuscript; A.L., D.F., C.H., and G.H. approved final version of manuscript.


Here, we employ neutron spectroscopy to investigate PA membranes under precise hydration conditions, and a series of isotopic contrasts, to elucidate water transport and polymer relaxation, spanning ps-ns timescales, and Å-nm lengthscales. We experimentally resolve, for the first time, the multimodal diffusive nature of water in PA membranes: in addition to (slowed down) translational jump-diffusion, we observe a long-range and a localized mode, whose geometry and timescales we quantify. The PA matrix is also found to exhibit rotational relaxations commensurate with the nanoscale confinement observed in water diffusion. This comprehensive ‘diffusion map’ can anchor molecular and nanoscale simulations, and enable the predictive design of PA membranes with tuneable performance.While polyamide (PA) membranes are widespread in water purification and desalination by reverse osmosis, a molecular-level understanding of the dynamics of both confined water and polymer matrix remains elusive. Despite the dense hierarchical structure of PA membranes formed by interfacial polymerization, previous studies suggest that water diffusion remains largely  Polymeric membranes are extensively used in water desalination, but the effect of membrane nanostructure on water transport is still elusive. The authors, using quasi-elastic neutron scattering and contrast variation techniques, provide detailed insight into the dynamics of the polymer network and confined water across a wide range of length and timescales. Polymeric membranes are extensively used in separation and purification processes, including water desalination4. Reverse osmosis (RO) membrane processes, in particular employing thin-film composite (TFC) aromatic polyamide (PA) membranes, offer high-energy efficiency as well as comparatively high selectivity and permeability and play a key role in addressing this challenge1. The active layer of these membranes is generally a rough and crumpled, highly cross-linked PA film, formed by the interfacial polymerization (IP) at the aqueous/organic interface between an aromatic diamine  and trimesoyl chloride (TMC), with an overall thickness of a few hundred nm, supported by a thick, porous, non-selective layer. Despite the widespread use of RO, the discovery and engineering of novel materials6 as well as process design and efficiency optimization7, further improving separation performance has remained non-trivial. In part, this is due to a surprising lack of a molecular-level understanding of the water dynamics confined within the membrane, of the PA matrix relaxation, and their possible coupling, which we seek to resolve.The scarcity of “fresh” water, amounting to less that 1% of the Earth’s water supply8, which assume that the active layer is effectively non-porous and that water and salt partition into the membrane, diffuse along the chemical potential gradient and eventually desorb into the permeate. Such descriptive, engineering models are then parameterized by experimentally measured constants, enabling different membranes, preparation methods, and conditioning processes to be compared. The importance of the active layer nanostructure (or “geometry”) and intrinsic water transport within the polymer matrix is, however, widely recognized9 and has been incorporated in hybrid coarse-grained PA models.Transport through the active layer is generally described by solution-diffusion macroscale modelsinhomogeneous film structure with a distribution of pore sizes, functional group asymmetry and surface polarization18. TMC/MPD oligomeric “clusters” are thought to form and coalesce to yield a “coherent film” of dense clusters within lower-density structures, which have been analytically and numerically modeled20. Such “aggregate” and “network” pores, as well as “lagoons”, are thus expected to impose complex water transport processes, modulated by these regions of varying polymer density within the membrane24.PA membrane formation via IP proceeds dynamically via a mechanism of cluster formation, diffusion-limited aggregation, and percolation, resulting in a well-known 28, generally find diffusion coefficients approximately one order of magnitude lower than that of bulk water30. Kotelyanskii et al.25 reported two values for water diffusivity, D ≃ 0.2 and 0.7 × 10−5 cm2 s−1 at constant volume and pressure, at 300 K, with a  jump length of ~3 Å. More recent simulations observe a heterogeneous distribution of water diffusivity27, often described by a bimodal distribution, whose physical interpretation generally invokes dynamics within distinct pore types or interfacial vs. confined water. Ding et al.22 find D ≃ 0.2 and 0.6 × 10−5 cm2 s−1 for confined water and in the “interfacial region”, respectively, in broad agreement with recent work28; in addition, MD studies generally recover bulk dynamics in the external water “reservoirs”, as expected. Hughes and Gale13 propose that water within the membrane is arranged in pockets connected by “chains” of water molecules, while Kolev and Freger12 find strong next-neighbor correlations and random long-distance water–water correlations, associated with the presence of small and large pores. Positron annihilation lifetime spectroscopy (PALS) measurements infer pore sizes ≃ 2.1–2.4 and 3.5–4.5 Å, interpreted as due to network and aggregate pores, respectively21, in line with other membranes31, and in broad agreement with simulation27 and small-angle X-ray scattering32.Molecular dynamics (MD) simulations of water diffusion within PA membranes36 have found translational diffusion coefficients only slightly reduced (≃ 1.90 and 2.06 × 10−5 cm2 s−1 at 300 K) with respect to those of pure water, and no evidence of spatial confinement or bimodal diffusion mechanisms. We, therefore, seek to elucidate the nature of water dynamics with PA membranes, how its mechanism and kinetics are affected by confinement, and the relation between water diffusion and the heterogeneous PA nanostructure. We employ neutron time-of-flight (TOF) and backscattering (BS) spectroscopy to examine water diffusion and PA membrane dynamics, which we decouple by selective deuteration of water (H2O and D2O), and systematically investigate hydration level (0% and 100% relative humidity) and hydration procedure to resolve this conundrum. Further, differential scanning calorimetry (DSC) was carried out to discriminate between confined and “bulk” water, and our dynamics data were benchmarked with MD simulations, and macroscopic performance data. Informed by the spatial heterogeneity of PA membranes and simulation of water dynamics, it seems reasonable to expect water to exhibit a space-dependent distribution of diffusion coefficients. Our hypothesis is that water diffusion through the network (or “bulk” polymer matrix) and aggregate “pores” can be experimentally resolved with a judicious choice of complementary instrumental resolutions. Other physical pictures can, however, also be conceived, for instance in terms of interfacial and bulk water diffusion, sub-diffusive dynamics within the dense polymeric membrane, and possible spatio-temporal coupling with multiscale relaxation processes within the polymer network.Surprisingly, previous experimental investigations of water dynamics within PA membranesall hydrogen atoms, whose incoherent cross-section dominates the signal, within a sample. In order to separately resolve the polymer dynamics and water-diffusion signals, our experiment and analysis were decoupled in stages. Employing dry PA membranes and membranes hydrated with D2O, we first resolve the segmental dynamics of the dry and hydrated polymer alone; equipped with this knowledge, we can then isolate the water signal in PA membranes hydrated in H2O, and experimentally resolve the confined water dynamics. Significantly, in this work, we investigate two hydration procedures in both H2O and D2O contrasts: PA membranes were hydrated in the vapor phase, up to 100% hydration as measured by water uptake, as well as by direct immersion in water followed by careful drying of excess surface water, as customarily done experimentally (including in previous QENS studies34).Incoherent Quasi-Elastic Neutron Scattering (QENS) provides a direct measurement of the self-correlation function of Sinc = SV ⊗ ST ⊗ SR37. For isotropic, harmonic vibrations this simplifies to Hydrogen dynamics are decomposed into atomic vibrations, translations and rotations and, assuming these are uncorrelated, the measured scattering function becomes a convolution of these terms: E = 0 μeV) and inelastic  fixed window scans, as a function of temperature (2–380 K) using the high-resolution backscattering spectrometer IN16B. The upper temperature was chosen to exceed typical RO operating conditions (up to 318 K), yet below the glass transition temperature Tg of PA  motions can be discriminated by the Q-dependence or -independence, respectively, of the characteristic maximum. Significantly, these results demonstrate that data from PA membranes hydrated with H2O yield information from H2O diffusion, while those from PA hydrated with D2O isolate the polymer dynamics in the hydrated state, permitting their decoupling in the scattering data.Dry and hydrated PA films were first analyzed by elastic ) in the cross-linked sub-Tg PA network. Since not all H atoms in the polymer are mobile at a given temperature, we define a fraction of mobile protons δ(ω) within the measurement time window.QENS measurements of dry PA membranes, shown in Fig. SA relaxation (predominantly visible by TOF), and a slower, large-amplitude relaxation LA (predominantly visible by BS). A combination of TOF and BS experiments, probing complementary timescales, is able to resolve both relaxations. We, therefore, write the scattering law describing the polymer P signal as:f) undergoes solely SA motions, and fraction f undergoes both SA and LA motions. Equation , characteristic of the geometry of the rotational motions, illustrated in Fig. SA and LA measurements, in Eqs. ; for SA motions, occurring at shorter timescales (ps), well-resolved in TOF, this angle decreases to α ≃ 15°, and d = 2.5 ± 0.1 Å. Parameters p1 and p2 denote the occupation probabilities between the two sites, and we find the best agreement with the data for p1 = 40% and p2 = 60% for both LA and SA motions, indicating a slight preference for one conformation. The presence of high- and low-amplitude motions at different frequencies is corroborated by MD simulations , the model above ) hol) hol2O-hve  and water (φW), and the additional signal arising from the water dynamics. In the vapor-hydrated membranes, we find gravimetrically φP = 0.67 and φW = 0.33  is given above Eqs.  is the dynamic structure factor for water. As above, the fraction of mobile water molecules can be expected to vary with temperature, and respond to confinement. Experimentally, combining BS and TOF measurements, we resolve two distinct motions which we assign to translational diffusion (tr) and long-range diffusion (lr), as detailed in Supplementary Note tr motions, and lr and tr motions. Within measurement uncertainty, in TOF data, one Lorentzian profile, with Q-dependent width, accounts for the additional water contribution to the signal  shown in Fig. The Hmentclass2pt{minimatures ≥20 K, the 41, and additional diffusive processes43. Dynamic confinement results in the appearance of an elastic component in the dynamic structure factor44, and in the effective invariance of the linewidth Γ at low-Q. We thus re-write Eq.  which, according to the chemistry of the surface and hydration level, can be either higher or lower than the macroscopic diffusion coefficient Dtr45. The confinement radius a, on the other hand, can be estimated from both the experimentally measured EISF, and from the maximum Q-value beyond which Γ is no longer constant. While Dianoux et al.46 extended the model to anisotropic confinement, including a cylinder, we found the simpler spherical model to suffice in describing all data within measurement uncertainty.Confined water generally exhibits longer residence times for translational diffusion, deviations in bulk structurerite Eq.  as:9\doclows Eq. , as the dynamic confinement of water in PA membranes. This effective pore size is consistent with the length scale obtained from the maximum Q-value beyond which Γ is no longer constant  in Fig. Dtr) as a function of temperature, which is found to vary from ≃ 0.5 to ≃ 2.4 × 10−5 cm2 s−1 between 250 and 330 K, respectively  yields similar results within measurement uncertainty. The temperature-dependent profiles Dlr) coefficient for water wihin the PA matrix can be estimated. Values of Dlr are found to be approximately one order of magnitude smaller than Dtr at the same temperature. Further, from the initial plateau of Dloc, and is found to increase with temperature (from 1.9 to 3.4 × 10−5 cm2 s−1 between 250 and 270 K).Employing high-energy-resolution BS, we resolve principally mentclasspt{minima47, as well as those computed by MD simulations of water in PA membranes25. Since water diffusion in PA confinement remains Arrhenius in the entire temperature range, while bulk water exhibits non-Arrhenius diffusion toward the supercooled regime, water diffusion is slowed down within PA membranes above 0 °C  but is actually faster than bulk water below 0 °C, where the two cross-over, as shown in Fig. l  temperatures, differing markedly from bulk water behavior. The mobile water fraction 48.These water-diffusion mechanisms are tentatively illustrated in Fig. Dlr ≃ 0.23 × 10−5 cm2 s−1 at 330 K, more than one order of magnitude lower than bulk water diffusion . The spread of diffusion coefficients observed by MD likely reflects sub-diffuse behavior of water within this confined (“crowded”) system, and other frameworks for analysis can potentially be compatible with the data. Nevertheless, our work reports the first experimental evidence of the distribution of water-diffusion processes within PA membranes relevant for RO water treatment, providing a comprehensive relaxation map of water dynamics over pico to tens of nanoseconds, and enabling the validation of transport simulations at the molecular scale, as well as reaction models for PA membrane formation by IP.We have associated with the various diffusion processes to the spatially heterogeneous nature of PA membranes, characterized by aggregate and network pores, and supported by MD simulations, thus corresponding to a space-dependent distribution of diffusion coefficients  compared to that found in vapor hydrated membranes . The proton fraction of water (φW) thus increases to 0.76  to infer molecular diffusion parameters from permeance data, subject to a series of assumptions49. While gravimetric approaches  and transmission electron microscopy (TEM) can be employed to approximate uptake and effective thickness in corrugated membranes, we opt to employ planar nanofilm membranes24 for which film thicknesses can be accurately determined from neutron reflection or atomic force microscopy, and perform ‘inverse’ calculations. Specifically, we estimate macroscopic permeance of representative PA membranes from molecular diffusion data and utilize the same diffusion coefficients, obtained in this work, to calculate the macroscopic performance of diverse membranes of similar chemical structure. We consider membranes with different void fractions and water uptake and take a weighted average of Dtr for diffusion through the “bulk” polymer and Dlr for “pore”-diffusion, to obtain a forward prediction for water permeance , in agreement with MD simulation. We decouple the local polymer relaxation from the water translational diffusion, which we find to be multimodal and elucidate the transport mechanisms and associated diffusion coefficients characterizing water confined within the PA matrix. To access the water dynamics in confinement, we hydrate the membranes via the vapor phase, building on our previous synthetic workDtr which is approximately half of that of bulk water, crossing over at lower temperatures, due to the fact that PA-confined water diffusion remains Arrhenius down to temperatures where supercooled bulk water diffusion becomes strongly non-Arrhenius. The jump-diffusion length remains l ≃ 1.2 Å in agreement with bulk water near ambient conditions, while residence time τ0 increases upon confinement yet exhibits Arrhenius behavior at all temperatures, by contrast with supercooled water. We obtain a direct evidence of confined translational diffusion at an effective length scale of ≃1 nm, compatible with the inferred “pore size” from separation measurements. Further, this dimension is comparable to the amplitude of polymer rotational relaxation of MPD rings, which might indicate a coupling between polymer relaxation and water dynamics within PA membranes. We obtain a comprehensive water-diffusion map, spanning two orders of magnitude in D and approximately 100 °C in temperature, encompassing the operating conditions of RO membranes, and experimentally resolving bulk, local, confined, and long-range diffusion processes. We expect that our findings will enable the development and validation of accurate molecular models for high-performance RO membranes and the predictive computation of their macroscopic, engineering performance.We find that water translational diffusion is well described by a jump-diffusion model with a diffusion coefficient 2O (>99.7% D) was supplied by Goss Scientific Instruments Ltd. .Trimesoyl chloride (TMC) 98% and m-phenylenediamine (MPD) flakes ≥99% were purchased from Sigma-Aldrich Ltd. . N-hexane ≥98.5% was supplied by VWR International Ltd.; DI water at 18 MΩ residual-specific resistance was employed. D24 at the liquid interface. In a 1-L reservoir containing the aqueous phase , the organic solution (250 mL of n-hexane with 0.5wt% TMC) was carefully poured laterally to form a planar, stable interface. The reaction was allowed to take place over 1 min, after which the crumpled polymer film was collected from the interface, and thoroughly washed with n-hexane to remove any unreacted TMC. To ensure the complete removal of any water and/or solvent residues, the membranes were dried under vacuum for 18 h at 30 °C. Films were then cold-pressed into coupons of 4  × 5 cm and 300–400 μm thick. Membrane stoichiometry was estimated from XPS measurements53). We opted to employ crumpled films instead of stacked nanofilms in order to attain QENS statistics required to quantify the multimodal diffusion coefficients , and minimize interstitial (bulk) water between films, which could invalidate our approach; finally, we believe that this procedure approximates more closely the ubiquitous RO membranes fabricated by IP. Three different hydration procedures were compared: (i) fully dried, measured immediately after removal from a vacuum; (ii) hydrated in water vapor, H2O or D2O, (using in a humidity chamber where the hydration level is controlled by the temperature difference between the liquid water reservoir and the sample chamber set to room temperature23); and (iii) hydrated by immersion in liquid water. Following 18 h of exposure, the PA membrane reached full hydration, as measured gravimetrically (detailed in 54: after the procedure (ii), the membrane was dipped in liquid water (either H2O or D2O) and allowed to soak for a further 4 h; the excess surface water was then gently pad dried to attempt its complete removal. Membrane samples were weighted before and after each step to quantify water uptake  following procedures reported previouslyλ = 6.271 Å (covering a Q-range between 0.2 and 1.8 Å−1) and an instrumental energy resolution of 1 μeV : this configuration allows probing motions in the ns timescale (0.4 < τ < 1 ns). Dynamic processes with longer characteristic times appear “elastic” while faster processes contribute to a background in the data. Elastic and inelastic fixed window scans (EFWS and IFWS)38 were recorded at ΔE = 0 and 2 μeV energy at a heating rate of 0.13 K min−1 from 2 to 380 K, and QENS profiles were acquired at selected temperatures. In order to investigate faster processes (which would appear as background in a BS experiment), complementary TOF experiments were performed from 150 to 330 K using λ = 6 Å (0.2 ≤ Q ≤ 1.6 Å−1) and energy resolution of 45 μeV, thus probing motions in the ps timescale (1 < τ < 50 ps). Samples were contained within a flat aluminum can  to achieve a neutron transmission of 90% or higher, thus minimizing multiple scattering. Vanadium reference and empty can measurements were carried out for data normalization and sample correction, respectively.QENS experiments were performed using both a TOF (IN5) and a high-resolution BS (IN16B) spectrometer at the Institut Laue Langevin . BS experiments were performed using the standard unpolished strained Si(111) monochromator and analyzer corresponding to an incident wavelength of Supplementary InformationPeer Review File


The effect of substrate and deposition temperature on the growth of AZO films and their preferential orientations were investigated. The crystallographic characteristics of AZO films were characterized by X-ray diffraction (XRD). The surface morphology of AZO films was studied by scanning electron microscopy (SEM) and atomic force microscopy (AFM). It is found that the lattice mismatch between AZO and substrate determines the growth of AZO films and their preferential orientations. The thermoelectric properties are strongly dependent on the crystal grain shape and the grain boundaries induced by the preferred orientation. The highly connected and elongated grains lead to high thermoelectric properties. The in-plane anisotropy performances of thermoelectric characteristics were found in the (112̄0) preferential oriented ZnO films. The in-plane power factor of the (112̄0) preferential oriented ZnO films in the [0001] direction was more than 1.5 × 10−3 W m−1 K−2 at 573 K, which is larger than that of the (0002) preferential oriented ZnO films.In this work, using a conventional magnetron sputtering system, Al-doped ZnO (AZO) films with (112̄0) and (0002) preferential orientations were grown on  r-sapphire and a-sapphire substrates, respectively.In this work, using a conventional magnetron sputtering system, Al-doped ZnO (AZO) films with (112̄0) and (0002) preferential orientations were grown on  Therefore, various dopants were introduced into ZnO to improve its thermoelectric properties.3,8,13–15 Among these works, it is found that Al-doped ZnO (AZO) is one of the best thermoelectric materials for high-temperature thermoelectric application.12,16 Thermoelectric materials in low-dimensional are promising to possess better thermoelectric performance than their bulk materials.1,17,18 A promising approach to achieve the low-dimensional thermoelectric materials is to deposit thin films, which are suitable for small-scale thermoelectric applications.19 This is why so many research group focused on the investigation on the growth of high quality ZnO thin films for thermoelectric applications. ZnO thin film, a versatile multifunctional material,20–22 which has been widely used in solar cells,23 surface acoustic waves,24–27 dilute magnetic semiconductors,28 resistive memory,29etc. Generally, ZnO is known to readily exhibit (0002)-preferred with the c-axis perpendicular to the substrate due to the lower surface free energy for the (0002) plane on single-crystalline substrates and even on amorphous substrates such as glass, and polymer substrate18,30_. Unusual, some researchers reported theoretical and experimental works concerning other crystalline planes such as (112̄0)- and (1000)-oriented ZnO films31–36 and ZnO films with different crystalline orientations possess different electronic, optical and acoustic properties. The thermoelectric anisotropic properties between ab-plane and along the c-axis of ZnO based films or ceramics with the c-axis perpendicular to the substrate has been reported. However, to our knowledge, the thermoelectric properties of (112̄0)-oriented ZnO films have been rarely reported and their thermoelectric characteristics of ZnO films with different crystalline orientations have not been reported in detail yet. Generally, specific deposition techniques are used to deposit ZnO films with good quality, for example pulsed laser deposition technique.37,38 In this work, we use a simple magnetron sputtering technology to deposit AZO films. The growth of AZO thin films with (112̄0) and (0002) preferential orientations and their thermoelectric characteristics of ZnO films with different grain shape and size was investigated. In general, the sapphire is the most commonly used substrate for growing ZnO films with different preferred-orientations. Furthermore, sapphire has low thermal conductivity, which is good for thermoelectric application. Therefore, r-sapphire and a-sapphire substrates were used to grow AZO films with (112̄0) and (0002) preferential orientations respectively. It is found that AZO films deposited on r-sapphire and a-sapphire substrates exhibit different grain size and orientation which, in turn, leads to the difference in thermoelectric performance.With the increase in the energy crisis and environmental pollution, sustainable energy technology has attracted more and more attention.2.r-sapphire and a-sapphire substrates was used. The substrate was cut into rectangular pieces and ultrasonically cleaned in acetone, alcohol and deionized water for 8 minutes, respectively. The sputtering chamber was pumped to a base pressure of 1.0 × 10−4 Pa, and then a mixture of highly pure argon (99.999%) and oxygen (99.999%) gases was introduced into the chamber. The working pressure was kept at 0.5 Pa with 40 sccm of Ar and 5 sccm of O2. Prior to deposition, a 15 min pre-sputtering process was performed to remove native oxides and contaminants on the surfaces of the ZnO : Al target. The distance between the target and substrates was fixed at 70 mm. The sputtering power was kept at 100 watts and the deposition rate was about 20 nm min−1. According to our previous work, the stress of the thin films would be minimum when the thickness of AZO films is around 600 nm. Therefore, the deposition time was fixed at 30 minutes. After deposition, the thicknesses of the AZO films were measured using a stylus profilometer and all the ZnO films have similar thickness (∼600 nm).AZO thin films were deposited by radio frequency magnetron sputtering using a ZnO : Al (with 2 at% Al) ceramic target (99.995% pure). The single crystalline α (λα = 0.15406 nm) radiation with the conventional θ–2θ mode. XRD Phi-scans was employed to investigate the epitaxial relationship between ZnO films and the substrate diffraction. The surface morphology of the deposited AZO films were examined by scanning electron microscope (SEM) and atomic force microscopy (AFM). The room temperature carrier concentrations and mobility of rectangular AZO thin film samples along the length and width direction, respectively, were evaluated using Hall measurement system in a four-probe van der Pauw configuration. The electrical conductivity of the AZO films were measured by the home-made four-point-probe technique. The four point measurements are co-linear and the conductivities of all the rectangular samples were measured along length and width, respectively. Seebeck coefficient was measured with the temperature gradient method (ΔT = 20 K) using a SDFP-1 measurement system and the Seebeck coefficient of all the rectangular samples were measured along length and width, respectively. All the measurement temperature was changed from room temperature to 573 K.The structure of the prepared AZO films was studied by X-ray diffraction (XRD) using Cu-K3.r-plane sapphire substrates with the substrate temperatures of 500 °C, 600 °C and 700 °C. The reflections observed corresponding to ZnO plane centered at 56.6°, with two additional substrate reflections arising from the sapphire (22̄04) and (33̄06) plane. No other peaks can be seen in the patterns under the detection limit of XRD, indicating that the deposited ZnO films have preferred (112̄0) orientation with c-axis parallel to the substrate. From these reflections, it is suggested that the out of plane epitaxial relationship between ZnO films and the sapphire substrates is (112̄0)‖(22̄04). And the epitaxial relationship does not change with the increase of substrate temperature. However, the peak intensity of ZnO (112̄0) increases and the full-width at half-maximum (FWHM) value of ZnO (112̄0) decreases a little with the increase of substrate temperature, indicating that ZnO film has relative stronger (112̄0) texture and better crystalline at the elevated temperature.The crystal structures of all the deposited AZO films were investigated by XRD. r-sapphire substrate. Since ZnO films deposited at the substrate temperature of 700 °C has the best crystalline, a-plane shows two-fold symmetry. Based on the phi-scans of r-sapphire, we conclude that the in-plane epitaxial relationship between ZnO film and substrate is [0001]ZnO‖[1̄101]2O3Al and [1̄100]ZnO‖[1̄1̄20]2O3Al, which is coincident to the previous literatures.34,39Azimuthal scans (phi-scans) were performed to investigate the in-plane epitaxial relationship between ZnO film and c-axis of ZnO (ZnO [0001] direction), the in-plane lattice parameters of ZnO [0001] and sapphire [1̄101] are 5.2069 and 5.1272 Å, respectively,34 and the mismatch of ZnO thin film in-plane along [0001] direction is 1.55% ((5.2069−5.1272)/5.1272). For the direction along ZnO [1̄100], the lattice parameters of ZnO [1̄100] and sapphire [1̄1̄20] are 5.629 and 4.756 Å respectively,34 and the mismatch of ZnO thin film in-plane along [1̄100] direction is 18.36% ((5.629−4.756)/4.756). It can be seen that ZnO thin film has structure anisotropy in-plane and the mismatch along the [0001] direction is much smaller than along [1̄100] direction. The mismatch along [1̄100] direction can be made up by the two alternate domains of ZnO thin films, namely five ZnO (11̄00) planes matches with six sapphire (112̄0) planes, as well as six ZnO (11̄00) planes matches with seven sapphire (112̄0) planes.a-sapphire at 500 °C, 600 °C and 700 °C showed in 33 There is another peak centered at ∼37.7° arising from the (112̄0) planes of the a-sapphire substrate. No other peaks exhibited in the patterns under the detection limit of XRD, indicating that the deposited ZnO films have preferred (0002) orientation with c-axis perpendicular to the substrate. The peak intensity of ZnO (0002) increases and the FWHM value of ZnO (0002) decreases from 0.46° to 0.34° with the substrate temperature increase from 500 °C to 700 °C, indicating that ZnO film has better crystalline with the increase of substrate temperature. In addition, the microstructure and crystalline preferred orientation do not change with increasing in substrate temperature. Therefore, we chose ZnO films with better crystallinity deposited at 700 °C to investigate the epitaxial relationship between ZnO film and sapphire using Phi-scans. a-sapphire (112̄3) plane. The figure shows six-fold symmetry with about 60° intervals, indicating a good hexagonal symmetry. Two peak positions of ZnO (112̄4) match good with that of sapphire substrate with (112̄3) reflections, yielding an in-plane epitaxial relationship of [1̄100]ZnO‖[1̄100]2O3Al.The XRD patterns of the AZO thin films grown on 15 which result in different thermoelectric performance. The grain size of AZO films can be calculated using Scherrer equation:k is a constant, λ is the wavelength of the X-ray, here we used Cu-Kα (λα = 0.15406 nm), β is the FWHM, θ is the diffraction angle. Based on the above formula, the grain size of AZO films deposited on different substrates at 500 °C, 600 °C and 700 °C are shown in It is reported that the different substrate caused different grain size and shape of AZO thin films,a-sapphire at 500 °C, 600 °C and 700 °C, respectively. a-sapphire and AZO films deposited at 700 °C has denser and uniform grains than that deposited at 500 °C and 600 °C. r-sapphire at 500 °C, 600 °C and 700 °C, respectively. It shows elongated grains morphology commonly observed on ZnO film with (112̄0) preferred orientation.40,41 The elongated direction is parallel to [0001] usually seen on ZnO film with (112̄0) preferred orientation.42Furthermore, SEM and AFM were used to characterize the surface morphology of AZO films. a-sapphire at 500, 600 and 700 °C, which (d)–(f) show the AFM images of AZO films deposited on r-sapphire at 500, 600 and 700 °C, respectively. AZO films deposited on a-sapphire exhibits rounded and uniform grains as shown in r-sapphire show the elongated grains with different sizes as shown in We also used AFM to confirm the influence of substrate on the grain shape of AZO films. σ of AZO thin films with different orientation depends on the testing temperature is shown in σ values of all the films decrease slightly with the increase of measuring temperature, indicating the metallic electrical conductivity behaviour. The carrier concentrations of AZO films shown in 20 cm−3, which are similar to that of metal conductor. The prepared AZO films are n-type semiconductor and the carrier concentration is so high that the Fermi energy is approaching or entering the conductive band. Therefore, AZO films become n-type degenerate semiconductor. It is well known that the degenerate semiconductor exhibit metallic electrical conductivity behavior. Similarly, the deposited AZO thin films exhibit metallic electrical conductivity behavior. The conductivity of AZO (112̄0) thin films along [0001] is larger than all the other films and AZO (112̄0) thin films show anisotropic electrical conductivity in plane along [0001] and [1̄100] direction. All the AZO films deposited at 700 °C shows similar carrier concentrations regardless of preferred orientation, however, AZO films deposited at 700 °C shows larger carrier concentrations than that of AZO films deposited at 500 °C as shown in ab plane. The larger amount of grain boundaries in-plane induces stronger scattering of electrons. Therefore, the carrier mobility as shown in 35 Therefore, although it has similar carrier concentration, the carrier mobility is smaller as shown in The electrical conductivity et al.43 They found that AZO thin films deposited on Al2O3 substrate exhibited c-axis oriented and larger electrical conductivity than deposited on SrTiO3 and fused silica.In short, we believe that the different grain shapes and sizes induced by the preferred orientation results in different conductivities. The substrate effects on the conductivity of AZO thin films were also reported by Saini S indicates that all of the AZO films are n-type semiconductor thermoelectric materials. This is expected since Al dissolved in the ZnO crystal lattice acting as donor, which will create extra electrons. In general, Seebeck coefficient S can be expressed as following:19k is Boltzmann constant, e is the electron charge, Nc is the effective density of states, n denotes carrier concentration and A is a transport constant. One can find from the formula that when the carrier concentration decrease the Seebeck coefficient S increase. As AZO (112̄0) thin films along [1̄100] direction have smaller carrier concentration and mobility, the absolute value of S of AZO (112̄0) thin films along [1̄100] direction is larger than others. The S of other samples does not exhibit too much difference as shown in −3 W m−1 K−2 at 573 K because of the large electrical conductivity, which is larger than all the other preferential oriented ZnO films. The PF in our work is comparable to the previously reported values.12,44,45 The PF of AZO (0002) thin film deposited at 700 °C is slightly larger than that of AZO (0002) thin film deposited at 500 °C, indicating that PF depends slightly on orientation degree in AZO (0002) thin films. Saini et al.43 reported that AZO thin film deposited on fused silica substrate showed as large as −200 μV K−1, however, the small σ limited its PF. Fortunately, the formation of the seed layer lead to the significant decrease of thermal conductivity, which improved the thermoelectric figure.From the values of Seebeck coefficient and electrical conductivity, we have calculated the PF of thin films depends on the testing temperature as shown in 4.r-sapphire and a-sapphire substrates using a conventional magnetron sputtering method. AZO film shows relative stronger preferred orientation and better crystallinity with the increase of substrate temperature. The electrical conductivity is strongly depended on the crystal grain shape and the grain boundaries induced by preferred orientation. Due to the elongated grains and less grain boundaries, the electrical conductivity of (112̄0) oriented ZnO films along [0001] direction is much larger than that of all other preferential oriented ZnO films. The in-plane PF of (112̄0) preferential oriented AZO films in [0001] direction was more than 1.5 × 10−3 W m−1 K−2 at 573 K, which are larger than that of all the other preferential oriented AZO films.AZO thin films with (112̄0) and (0002) preferential orientations were respectively grown on There are no conflicts to declare.