Long-ordered and continuous graphene layers were then embedded into the amorphous SiOC phase. The oxygen-rich SiOxC4−x units were more prone to forming than carbon-rich SiOxC4−x units in SiOC after the introduction of reduced graphene oxide, which we attributed to the bonding of Si atoms in SiOC with O atoms in reduced graphene oxide during the pyrolysis process.Dispersing graphene nanosheets in polymer-derived ceramics (PDCs) has become a promising route to produce exceptional mechanical and functional properties. To reveal the complex nanodomain structures of graphene–PDC composites, a novel reduced graphene oxide aerogel embedded silicon oxycarbide (RGOA-SiOC) nanocomposite was fabricated bottom-up using a 3D reduced graphene oxide aerogel as a skeleton followed by infiltration of a ceramic precursor and high-temperature pyrolysis. The reduced graphene oxide played a critical role in not only the form of the free carbon phase but also the distribution of SiO Proper integration between graphene and PDC is of high practical value, taking advantage of the beneficial properties of both. For instance, adding PDCs to graphene can improve its thermal stability, especially at high temperatures ,2. PDCs 3N4 ) matrix 3N4  or SiC [3N4 . Graphen storage ,9,19. Thronments ,11,17. Aronments .xC4−x (0 ≤ x ≤ 4) tetrahedral structures are surrounded by a fraction of free carbon (Cfree) [However, there are two main challenges in the field of graphene–PDC composites that have not yet exhibited substantial progress. First, controllable dispersion of the graphene nanosheets, especially with high loadings, in the PDCs is extremely difficult using conventional top-down physical mixing or chemical bonding methods due to the strong van der Waals force between the 2D graphene nanosheets. Thus, graphene tends to agglomerate in the PDC matrix, deteriorating the mechanical, electrical, or shielding properties of the composites. The second challenge is that the nanodomain structures of graphene–PDC material systems, which are critical in clarifying structure–property relationships and ultimately in determining their properties for specific engineering applications, are not yet fundamentally understood . Most wo (Cfree) ,22,23. T (Cfree) , while ffree and SiOxC1−x tetrahedral units of reduced graphene oxide embedded SiOC nanocomposites, were investigated using several characterization techniques, including HR-TEM, Raman, XPS, and NMR. The insights into the nanodomain structure of graphene–SiOC composites allow for a greater understanding of structure–property relationships and describe an efficient pathway for designing high-performance graphene–PDCs nanocomposites.In this work, we put forward a universal and delicate bottom-up processing strategy to uniformly disperse graphene into SiOC ceramic by using a 3D reduced graphene oxide aerogel as a skeleton to infiltrate polysiloxane precursors. This strategy has great potential to enable both mechanical reinforcement and multifunctionalization, to which a more controllable design of the geometrical morphology and material constituents is fundamentally attributed. The nanodomain structures, especially CThree-dimensional reduced graphene oxide aerogel (RGOA) was synthesized using a hydrothermal method, followed by freeze-drying and thermal reduction. First, graphene oxide (GO) was prepared according to our previous work  and then3)3OH); RGOA samples (RGOA-600 and RGOA-1000) were then immersed into this solution under vacuum for 2 h to facilitate precursor penetration into the aerogel and eliminate bubbles. Subsequently, the polymeric precursor-loaded RGOA (hereafter denoted as RGOA-600-P and RGOA-1000-P) samples were removed from the solution and freeze-dried for 12 h to remove the TBA. The obtained RGOA-P cylinders were further cross-linked at 250 °C for 2 h and pyrolyzed at 1000 °C for 3 h in a tube furnace under flowing argon at a heating rate of 100 °C/h to obtain the final 3D RGOA-SiOC materials. The obtained ceramic nanocomposite materials after pyrolysis of RGOA-600-P and RGOA-1000-P are denoted hereafter as RGOA-600/SiOC and RGOA-1000/SiOC, respectively. The final weight ratio  of RGOA in RGOA-600/SiOC and RGOA-1000/SiOC was 22.3 and 20.5 wt%, respectively. For comparison, unmodified SiOC material was prepared by the pyrolysis of preceramic polymer H62C at the same heat-treatment conditions.Commercial preceramic polymer precursor methylphenylvinylhydrogen polysiloxane  was infiltrated into the as-prepared RGOA frameworks under vacuum to fabricate 3D graphene-polymer-derived ceramic architectures. We prepared 25 mg/mL polymeric solution by dissolving 100 mg polymeric precursor into 4 mL tert-butanol  at a resonance frequency of 199.13 MHz for 29 29Si using dipole decoupling magic angle spinning (DD/MAS) and high-power 1H decoupling. The powder samples were placed in a pencil-type zirconia rotor with an outer diameter of 4.0 mm. The spectra were obtained at a spinning speed of 8 kHz (4 μs 90° pulses) and a recycle delay of 10 s. The Si signal of tetramethylsilane (TMS) at 0 ppm was used as the reference 29Si chemical shift. The scanning number was 5000. Solid-state 13C CP/MAS NMR spectra were recorded on an Agilent 600 DD2 spectrometer  at a resonance frequency of 150.72 MHz for 13C using cross-polarization (CP), magic-angle spinning (MAS), and high-power 1H decoupling. The powder samples were placed in a pencil-type zirconia rotor with an outer diameter of 4.0 mm. The spectra were obtained at a spinning speed of 10 kHz (4.2 μs 90° pulses), a 2 ms CP pulse, and a recycle delay of 3 s. The C signal of tetramethylsilane (TMS) at 0 ppm was used to reference the [The morphology and microstructure of RGOA and RGOA-SiOC composites were investigated with scanning electron microscopy (SEM) using a Leo Gemini 1530 and transmission electron microscopy (TEM) using a JEOL 2100F. X-ray photoelectron spectroscopy (XPS) was performed on a Thermo Fisher Scientific ESCALAB 250Xi to investigate the surface chemical states of different elements in SiOC and reduced graphene oxide modified SiOC nanocomposites. Raman spectra of RGOA and RGOA-SiOC composites were measured using a micro-Raman spectrometer (RENISHAW inVia) with an excitation wavelength of 532 nm. Solid-state -Three-dimensional reduced graphene oxide aerogels (RGOAs) were prepared from GO and PPy via a typical hydrothermal process at 150 °C for 6 h, followed by freeze-drying for 24 h and thermal reduction at 600–1000 °C for 1 h, as illustrated in The TEM images of SiOC pyrolyzed at 1000 °C a,b show −1 could be attributed to disordered sp2-hybridized modes in the carbon rings and in-plane bond stretching of sp2 carbon, respectively. In addition to the typical D and G bands (at 1320 and 1600 cm−1) in the pure SiOC sample, the 2D, D + G, and 2D’ bands were observed in the second-order Raman spectra at around 2610, 2900, and 3195 cm−1, respectively, which could be assigned to the overtones and combinations of different Raman vibration modes in PDC materials [3 band [4 band was observed as a shoulder of the D1 band at ca. 1190 cm−1 in the spectra of all SiOC, RGOA-600, RGOA-1000, and RGOA-SiOC nanocomposites, which could be attributed to the disordered graphitic lattice (C−C and C=C stretching vibrations and sp2-sp3 bonds) in soot and related carbon materials. The D3 band at 1500–1510 cm−1 could be assigned to the amorphous carbon fractions [Micro-Raman spectroscopy was used to analyze the structure of the carbon phase within reduced graphene oxide aerogels, SiOC, and reduced graphene oxide embedded SiOC samples. aterials . Because [3 band ,28. As sractions .D1/IG) of RGOA, which indicates the reduction degree of graphene oxide, decreased from 1.14 to 1.08 with increasing reduction temperature. This result revealed the removal of defects and recovery of conjugated domains in the reduced graphene oxide, especially at higher thermal reduction temperatures. The extracted ID1/IG intensity ratio can also be used to determine the lateral crystallite size of free carbon . Until now, two correlations between ID1/IG and La have been proposed, as shown in Equations (1) and (2) [0 + λC1 (C0 = −12.6 nm and C1 = 0.033), C’(λ) ≈ 0.55 nm−2. λ is the wavelength of the laser; and ID1 and IG are the intensities of the D1 and G band, respectively.The intensity ratio (I and (2) .ID1/IG La values higher than 2 nm, while the Ferrari–Robertson equation (Equation (2)) is valid for La values lower than 2 nm [2La value is about 1.48 nm, which is theoretically acceptable. However, the TK correlation is more suitable for evaluating the La value of graphene–SiOC nanocomposites, which was 4.63 and 4.81 nm for the RGOA-600/SiOC and RGOA-1000/SiOC samples, respectively.Generally, the Tuinstra and Koenig (TK) correlation (Equation (1)) is valid for carbon clusters with han 2 nm . In the xC4−x units after the introduction of graphene [The elemental composition and chemical environment of C and Si on the surface of the samples were examined by XPS to gain insight into not only the reduction progress of graphene oxide , but alsgraphene . As show4 (103.6 eV), SiO3C (102.8 eV), SiO2C2 (101.8 eV), SiOC3 (100.8 eV), and SiC4 (99.5eV) groups [4, SiOC3, and SiO2C2 units decreased and the content of oxygen-rich SiOxC4−x units (SiO3C and SiO4) increased after the incorporation of RGOA. Especially in the case of lower reduction degrees of RGOA-600, SiC4 and SiOC3 units almost disappeared, and the contribution of SiO2C2 decreased, whereas the proportion of SiO3C and SiO4 increased. These results suggested that RGOA can tailor the structure of SiOxC4-x units in SiOC ceramic by converting the carbon-rich SiOxC4-x units into oxygen-rich SiOxC4−x units  groups . It is w−x units c.29Si MAS-NMR spectroscopy was further used to probe the structure of SiOxC4−x tetrahedra present in the amorphous network of SiOC and RGOA-SiOC nanocomposites. Four different environments were evident in the SiOC sample obtained by pyrolysis at 1000 °C (4 (−110 ppm), SiO3C (−74 ppm), SiO2C2 (−37 ppm), and SiC4 (−12 ppm) structural units [3 (7 ppm) along with SiO4 (−107 ppm), SiO3C (−75 ppm), SiO2C2 (−42 ppm), and SiC4 (−13 ppm) units, as shown in 4 unit decreased, while those of the of SiO2C2 and SiO3C units increased  units due to the interaction between RGOA and SiOC. These interactions caused Si atoms to bond with O atoms from remaining oxygen groups in reduced graphene oxide during the pyrolysis process. The 29Si MAS-NMR spectrum of RGOA-600/SiOC nanocomposite (4 (−110 ppm), SiO3C (−74 ppm), SiO2C2 (−41 ppm), and SiC4 (−10 ppm) units. The relative concentration of SiC4 unit further decreased, and that of SiO4 unit increased. These results further confirmed the interaction between Si atoms of SiOC and O atoms of RGOA and that graphene oxide plays a critical role in the distribution of SiOxC4−x structural units in SiOC. The oxygen-rich SiOxC4−x units are more prone to forming than carbon-rich SiOxC4−x units in SiOC via the modification of graphene oxide, and the lower reduction degree of graphene oxide results in a higher concentration of oxygen-rich SiCxO4−x units. 1000 °C a, which al units ,32, as sal units . Howeverncreased , indicatomposite c obtaine13C MAS NMR spectra of SiOC and RGOA-SiOC nanocomposites. In the case of SiOC sample (3-hybridized carbon within SiOxC4-x units and sp2-hybridized carbon (Cfree), respectively [xC4-x units and carbon bonded to other carbon atoms forming nanodomains of turbostratic carbon, consistent with the findings in a previous work [free, which was present as both turbostratic carbon and graphene sheets and was dominant in RGOA-1000/SiOC and RGOA-600/SiOC nanocomposites  resulted in a higher reduction degree of graphene oxide aerogel with fewer remaining oxygen groups. A novel reduced graphene oxide aerogel containing SiOC ceramic was prepared by the infiltration of a preceramic polymer and a subsequent high-temperature pyrolysis process. The as-prepared RGOA-SiOC presented a highly porous structure with a uniform distribution of graphene into SiOC. After the introduction of RGOA, the carbon-rich SiO


The results indicated that the recovered nanomaterials endure 4 times recyclability retaining up to 89% lead uptake efficiency. To complement the experimental study, DFT calculations were performed to investigate the stability of the formed G–CdO composite compared to CdO NPs; the reactivity of G–CdO compared to plain graphene as well as the interaction insights between graphene and CdO clusters were studied using natural-bond-orbital (NBO), electron-localization-function (ELF) and reduced-density-gradient (RDG) analyses.Graphene-based metal oxide nanocomposites are interesting and promising kinds of nanocomposites due to their large specific area, fast kinetics, and specific affinity towards heavy metal contaminants. In this work, a facile and cost-effective route was used to synthesize CdO nanoparticles (CdO NPs) and graphene-based CdO nanocomposite (G–CdO). The prepared nanomaterials were characterized and explored for lead removal from water. Both CdO NPs and G–CdO composite exhibited excellent sorption capacity of 427 and 398 mg g Graphene-based metal oxide nanocomposites are interesting and promising kinds of nanocomposites due to their large specific area, fast kinetics, and specific affinity towards heavy metal contaminants. Until now, conventional methods to remove heavy metals include coagulation,4 precipitation, chemical reduction,5 ion exchange,6 biological treatment,7 membrane separation,8 and filtration.9 Nevertheless, such techniques have drawbacks such as high cost, low purification efficiency, and difficulty in regeneration. The removal method is regarded as preferable to other methods when it has some features such as low cost, prolonged durability, and simple operation.10 Various materials have been used such as resin,11 carbon,12 zeolites,13 metal oxide,14 clays,15 biopolymers,16 and rice husk.17 However, such materials still have drawbacks because of their relatively low chemical stability and low adsorption capacity for heavy metals. Recently, graphene, single layer graphite, holds great promise for potential applications in many technological fields, especially as an adsorbent for heavy metals owing to its huge surface area, excellent thermal and conductivity due to its unique two-dimensional lattice structure.18 Despite the superior properties of graphene, it has a strong preference for aggregation due to strong van der Waals forces between layers of graphene sheets. Such a drawback inhibits various graphene applications but it can be eliminated by hybridizing graphene with inorganic nanomaterials, especially, with those having a higher surface to volume ratio. Thereby, a composite of graphene with inorganic nanomaterials such as metal oxides can potentially obtain a much-enhanced surface area. Therefore, it has attracted much attention in the scientific community.19 Various metal oxide NPs have been anchored onto graphene sheets' surfaces to act as a stabilizer against the agglomeration of these sheets due to van der Waals forces.20 Graphene-based metal oxide nanocomposites are an interesting and promising type of nanocomposites because of their properties that exceed the properties of their individual phases.21 Also, individual metal oxide nanoparticles still do not have commercial applications due to a strong tendency to aggregate as a result of van der Waals interactions. Such interactions lead to a significant reduction of selectivity and adsorption capacity with prolonged use.22 To overcome these shortcomings, metal oxide nanoparticles are anchored at a supporting surface as graphene, and thereby the size of metal oxide NPs is stabilized on the matrix of the nanocomposite. As a result, the total surface area increases and the adsorption capacity will improve. Moreover, incorporating graphene with metal oxide NPs will prevent the loss of metal oxide nanoparticles due to the stabilization or anchoring of the nanoparticles onto the surface of graphene sheets,23 which makes the application of graphene-based metal oxide nanocomposites becoming increasingly popular in environmental applications.24 In literature, graphene has been hybridized with metal oxides such as Ni/Fe2O3,25 MnO2,26 Fe3O4,27 SiO2,28 ZnO29 to formulate adsorbents for heavy metal removal. Our group designed a facile, cheap, and eco-friendly graphene-based CdO nanocomposites via a green approach.30 Green route synthesis has many great advantages to make it outstanding among all preparation routes to remove heavy metals from aquatic medium.31 Although there are many experimental studies have investigated the potential of graphene-based metal oxides for application as efficient adsorbents for various pollutants, experimental information is not enough to explain the whole picture of the interaction between graphene and metal oxides. In this context, computational chemistry can provide many detailed insights into the interaction between metal oxides and graphene as well as the reactivity and stability of the composite compared to individual graphene. Density functional theory (DFT) as a tool can provide deeper insights to better understand interactions and reactivity in graphene composites.32Pollution of water streams with heavy metals is considered a critical environmental risk all over the world owing to their highly toxic and non-biodegradable nature.ii), reaction time, temperature, pH, and solid dose on Pb(ii) uptake, was studied using batch techniques. The thermodynamic, kinetic, and isotherm studies were performed to elucidate the mechanism of the sorption process. Regeneration efficiency and recyclability were studied as well. The interaction between CdO and graphene will be discussed by DFT calculations as well as the reactivity of formed nanocomposite compared to single graphene towards the removal of lead ions from water.In this study, a graphene–CdO composite was prepared and characterized using various techniques and its adsorption efficiency towards lead removal from the water was explored. The impact of various sorption factors, such as the initial concentration of Pb2·2H2O, 99.5%, ethanol, HCl, HNO3, NaOH and Pb(CH3COO)2 were purchased from LOBA CHEMIE. Hp pencil cores were used as a source of graphite. All chemical reagents were pure and used without purification.Na30 In brief, two graphite pencil cores were installed as cathode and anode electrodes in an electrochemical cell and 1 M Na2SO4 solution was used as a conductive electrolyte. The exfoliation process was applied under 12 volts. The obtained graphene sheets that precipitated as black debris, were washed with de-ionized water, and then sonicated for about 30 min for complete exfoliation. Exfoliated graphene sheets were washed and dried at 60 °C for about 6 h.Graphene was prepared by the electrochemical exfoliation method.Red onions (100 g) were sliced, and dipped in aqueous ethanol (50 : 50 v/v), for 2.5 days. Then the onion residue was removed and the solution was stored at 20 °C for further use.3COO)2·2H2O solution was added to about 300 mL extract under stirring. A yellow precipitate was formed immediately. The reaction solution was aged for 24 h at room temperature and pH 5.5 and then centrifuged and washed several times with deionized water and then ethanol. Afterward, the obtained material was dried at 60 °C then calcined at 400 °C for 2 h.3050 mM of aqueous Cd, UV-Vis spectrophotometer , X-ray diffractometer (Philips – PW1710), transmission electron microscopy – TEM; (JEOL – JEM-100 CXII), scanning electron microscopy – SEM; (QUANTAFEG 250 with energy-dispersive X-ray spectroscopy – EDX attachment) and Raman spectrometer (WITEC Alpha300 laser) were utilized.ii) solutions with initial concentrations of 550 mg L−1 at pH 4.8 and the residual lead ions concentration was measured (at time = 0–24 h) using an ICP-OES . For the thermodynamic studies, 0.025 g of nanoadsorbent was added to 25 mL of 550 mg L−1 Pb(ii) solution at pH 4.8 for 24 h at various temperatures (25–37 °C). The pH during the sorption experiments was regulated by dropwise addition of 0.1 M HNO3 or 0.1 M NaOH.All tests were performed at 29 °C using 25 mL of lead ion solution in a batch mode. The effects of pH (1.55–7.02), nanoadsorbent dose (0.015–0.03 g), and lead initial concentration (25–1500 mg) on the sorption behavior were studied. The kinetic study was performed by adding 0.025 g of nanoadsorbent to Pb(ii) ions to investigate the service life of nanomaterials and % removal.Specific amounts of lead-loaded nanomaterials were eluted with dilute hydrochloric acid solution and then washed until the pH was neutral. Hence, the spent materials were dried at 75 °C to constant weight, and then re-loaded with Pb and the percent removal or uptake (R%) of lead ions at equilibrium were calculated using C0 and Ce (mg L−1) are the lead concentrations in the liquid phase before and after adsorption, respectively. V (L), t (min), and m (g) are the volume of the liquid phase, time, and mass of the dry nanoadsorbent used, respectively.The sorption capability (33qe and qt are the Pb(ii) concentration of sorbed by nanomaterial (mg g−1) at equilibrium phase and predetermined time interval t, respectively. K1 is the pseudo-first-order rate constant (min−1).The results of adsorption kinetic experiments were studied by four models: the pseudo-first- and second-order, intraparticle, and Elovich models. Pseudo-first-order, 34K2 (mg g−1 min−1) is the rate constant of the pseudo-second-order. Another model is Elovich, which is symbolized as 35α is the initial adsorption rate parameter of lead ions (mg g−1 min−1) while β (g mg−1) is Elovich constant correlates activation energy and the surface coverage included in chemisorptions.The pseudo-second-order kinetic model, 36Kint (mg g−1 min−1/2) is the rate constant of the model. Values of C describes the boundary thickness. This means the larger is the intercept (C), the greater is the effect of the boundary layer in the solution. The values of Kint (slope) reflect the sorption rate of lead ions onto the nanomaterial surface.The intraparticle diffusion equation is expressed as 37qL is the maximum sorption capability (mg g−1) of nanomaterial adsorbents and KL is a constant (L mg−1) describing sorption affinity for the nanoadsorbent. The basic characteristic of that model could be described in terms of a dimensionless factor, RL, which is expressed as Cmax is the highest Pb(ii) concentration.After completion of adsorption isotherm tests, four models, Langmuir, Temkin, Freundlich, and Dubinin–Redushkevich (D–R) were applied to depict all isothermal features of G–CdO nanoadsorbent. The four models can be written (linear form) as in 38 and defined as KF parameter, (mg g−1) (L mg−1)n1/ is a constant corresponding to the Pb(ii) multilayer sorption capacity. The constant n is defined as the heterogeneity factor.Freundlich describes a heterogeneous surface of nanoadsorbentii) sorption is gradually reduced linearly with surface interaction39 and the linear form is better for the sorption process rather than the logarithmic, A (L g−1) is the Temkin isotherm equilibrium binding constant while B corresponds to equilibrium adsorption heat. The gas constant is R (J mol−1 K−1) and the absolute temperature is T.Temkin isotherm model depicts that the heat of Pb−1/2), while ε (J mmol−1) is Polanyi potential defined as The D–R isotherm was approached from the following G0, kJ mol−1), standard entropy (ΔS0 J K−1 mol−1), and standard enthalpy  as:Kd represents linear sorption coefficient, defined as a ratio between the surface concentration of adsorbed Pb(ii) and its concentration in the solution at equilibrium.The data of the thermodynamic experiments were analyzed to get the change in free energy  and affinity (A) are written as:All computational calculations were performed on a personal computer and Gaussian 09W program package. The B3LYPμ), global hardness (η), electronegativity (χ), electrophilicity index (ω), index of softness (σ), maximal charge acceptance (ΔNmax) and energy change (ΔE) are stated as:Global potential (E2) were calculated using the NBO 5.9 software (in Gaussian) at level DFT/B3LYP/LANL2DZ of the theory to determine importantly donor–acceptor interactions in the G–CdO complex. Multiwfn, Gauss Sum and VMD programs were also used at the same level of theory.The interactions between graphene and CdO in the formed composite were explored using natural-bond-orbital (NBO) analysis, electron-localization-function (ELF) and reduced-density-gradient (RDG) analyses. Perturbation delocalization or stabilization energies of second-order (−1), C–H (at 2924 cm−1), C PBM data was replaced with SVG by xgml2pxml:<glyph-data id="z.dbd" format="PBM" resolution="300" x-size="8" y-size="10" xml:space="preserve">00000000000000000000000000000000111111110000000011111111000000000000000000000000</glyph-data><svg xmlns="http://www.w3.org/2000/svg" version="1.0" width="13.200000pt" height="16.000000pt" viewBox="0 0 13.200000 16.000000" preserveAspectRatio="xMidYMid meet"><metadata>Created by potrace 1.16, written by Peter Selinger 2001-2019</metadata><g transform="translate scale" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg>C (at 1634 cm−1), and C–O (1090 cm−1). Onion extract spectrum showed peaks attributed to O–H and N–H at 3440 cm−1, C–H asymmetric at 2928 cm−1, carbonyl vibration at 1636 cm−1, CC aromatic at 1425 cm−1, and C–O at 1055 cm−1. These data reflected the complex nature of the extract derived from polyphenols, carbohydrates, proteins, and lipids. For the prepared nanomaterials spectra, a similarity is displayed with slight changes in intensities or positions, which depict the presence of onion organic species as capping and complexing agents. The Cd–O vibrational stretching appears at 603 and 556 cm−1 in composite and single cadmium oxide spectra, which affirms the formation of nanomaterials.The FT-IR spectrum of graphene, UV-vis absorptions, θ = 33.01, (200) at 2θ = 38.33, (220) at 2θ = 55.34, (311) at 2θ = 65.8, (222) at 2θ = 69.31 and (400) at 2θ = 82.03 the cubic structure of CdO (JCPDS 65-2908). The XRD analysis of graphene showed an intense peak at 26.56° related to the (002) plane that confirms the exfoliation of graphite into graphene layers. The XRD analysis of G–CdO is similar to both hybrid CdO NPs and graphene reflect the anchoring of CdO nanoparticles onto the nanosheets of graphene. The mean particle sizes calculated from the Scherrer equation were 21.94 and 26.09 nm for CdO and G–CdO, respectively. The peak sharpness of the prepared nanomaterials indicates their high crystalline nature. Such finding is harmonious with the SEM analysis, The XRD analysis, shown in The TEM analysis of CdO NPs and G–CdO are shown in −1 (D-band) and 1585 cm−1 (G-band), attributed to a primary in-plane vibration of k-point phonons belonging to A1g symmetry and first-order in-plane stretching vibration belongs to E2g phonon from sp2 carbon rings, respectively.42 The Raman spectrum of G–CdO shows a clear redshift for both D and G peaks by 10 and 8 cm−1, respectively, which confirm the anchoring of CdO on the graphene surface. The intensity ratio (IG/ID) usually measures the degree of defects in the graphene system.43 The calculated IG/ID ratio was increased from 1.03 (G) to 1.08 (G–CdO) implies a high degree of defects. This finding adds to the proof that the G–CdO composite was formed.To provide additional evidence on G–CdO formation, Raman analysis was carried out for the prepared graphene and G–CdO nanocomposite. Raman spectroscopy is an effective tool to distinguish ordered and disordered carbonaceous materials. The spectrum of graphene shown in ii) ions for 24 h contact time at 550 mg L−1 as an initial lead concentration and solid/liquid ratio of 1g L−1. The highest adsorption capacity was noted for the G–CdO nanocomposite compared to CdO NPs and graphene, which may be attributed to the synergistic effects of CdO NPs and graphene. The adsorption capacity of the graphene was found to be the lowest in an acidic medium and increased with increasing solution pH. As seen in ii) and graphene rings. Besides, the chelate formation of Pb(ii) with CdO that decorated the graphene surface could have been involved. However, as moving from acidic to a neutral solution, the interaction with lead ions is favorable, resulting in the enhancement of the removal capacity until Pb(ii) ions tend to hydrolyze.44 Owing to the subsequent hydrolysis and precipitation of lead ions in basic solution, the pH of the medium was set to 4.8 for all experimental studies to avoid Pb(ii) precipitation.2+ adsorption. Hence, different doses of nanoadsorbents were used for the lead removal. As shown in ii) adsorbed layer at the adsorbent surface. Again, the removal efficiency was higher for G–CdO nanocomposite followed by CdO NPs.The amount of nanoadsorbent affects the rate of Pb−1, the sorption capacities almost remained constant. This is possibly attributed to the lack of adequate active sites to accommodate additional Pb(ii) ions. The maximum lead adsorption capacities for G–CdO, CdO NPs, and G are 400, 370, and 67 mg g−1, respectively.The influence of lead concentration on the removal capacity of prepared adsorbents is displayed in ii) concentration reached 200, 100, and 50 mg g−1 for G–CdO, CdO and G, respectively. During the increase in initial lead concentration, the surface areas of the three nanoadsorbents available for the removal are insufficient, hence, the rate of lead removal decreases with increasing lead concentration. At lead concentration = 200 mg L−1 for G–CdO, 100 mg L−1 for CdO NPs and 50 mg L−1 for graphene, equilibrium was attained since all the adsorption sites on the surface of the nanomaterials were bonded by lead ions. As illustrated in The lead removal% for three prepared nanoadsorbents, shown in R2, the kinetics data of lead adsorption onto G, CdO and G–CdO were better supported by the pseudo-second-order model than by other models, as shown in R2 > 0.990). Deviation from linearity for the rest models reflects the lack of fitting of these models to the experimental kinetic data.Kinetics parameters were calculated and are shown in −1 for G–CdO, CdO NPs and G, respectively) were very close to the calculated values . This finding indicates that the pseudo-second-order model can accurately express lead adsorption onto prepared nanomaterials.In general, the pseudo-second-order model was employed to represent chemisorption, with ionic force relating to the electron sharing or exchange between the lead cations and nanomaterial as covalent interaction, and ion exchange. As a result, the chemisorption process governed the rate of lead removal by G, CdO and G–CdO. Furthermore, it was found that the experimental values of adsorption capacities . Adsorption is either favorable (0 < RL < 1), linear (RL = 1), unfavorable (RL > 1), or irreversible (RL = 0) based on the RL value. The better-fitting Langmuir isotherm model suggested the homogenous adsorption of lead cations with all adsorption active sites of equal affinity. The separation factor, RL, values determined from the Langmuir model for lead removal were in the range of 0.095–0.018 suggesting that the removal process was favorable. The Langmuir monolayer adsorption capacities for lead removal systems increased from 79 mg g−1 (for G) to 427 mg g−1 (for G–CdO), demonstrating that the modified G–CdO is capable of removing lead from the aqueous solution.Dubinin–Redushkevich, Freundlich, Langmuir, and Temkin sorption isotherms were utilized to clarify the lead removal mechanism. Calculated results from various adsorption isotherms, n, for the adsorption of lead are higher than 1, indicating that the uptake process was favorable. Therefore, the uptake of lead ions by G–CdO, Cd NPs and graphene surface proceed with some heterogeneous inactive sites.From B and A, −1, 10.4 J mol−1 and 59.5 L g−1 and, 1.76 J mol−1, respectively) than graphene  indicating that the heat of sorption refers to a physical process.According to the calculated Temkin parameters E in Although the Dubinin–Redushkevich model does not fit the sorption process, the values of ii) cations compared to various nanoadsorbents  in-depth, typical thermodynamic parameters were determined. For pristine graphene, the calculated parameters in H0 < 0) reaction.1 The negative ΔS0 suggests a decrease in the randomness in the graphene/Pb(ii) system during the removal process. Positive values of ΔG0 under various temperatures denoted that the reaction was a nonspontaneous process.1 The same finding was reported for the adsorption of Pb(ii) by reduced graphene oxide.49 From G0 value for both CdO and G–CdO adsorbents are negative indicating that the two reactions are a spontaneous and thermodynamically feasible process. As illustrated in H0 are positive.To investigate the sorption process of Pb solution interface increased as the process progressed. The values of ΔH0 were ranged from 37 to 43 kJ mol−1, illustrating a physisorption reaction.In a similar work, Ren To complement experimental results, DFT calculations were performed to respond to three questions: (1) the stability of formed G–CdO nanocomposite compared to CdO, (2) the reactivity of the composite compared to plain graphene and CdO, and (3) the interaction insights between G and CdO clusters in the prepared composite. For easy calculations, a dimer of CdO cluster was considered and a graphene sheet was built as a hexagonal pattern with 7 benzene rings (24-C atoms). CdO was added to the graphene sheet at the central benzene ring. Egap for CdO, G, and G–CdO systems are demonstrated in 51 Also, an increase in Egap from 1.896 eV (CdO) to 2.182 eV (graphene–CdO complex) has been recorded due to the interaction. Such an effect suggests that the formed G–CdO complex is more stable than isolated CdO nanoparticles.52 The calculated dipole moment (DM) at the same level of theory for the G–CdO composite was found to be 3.97 Debye compared to 0 Debye for single G and CdO systems. The dipole moment is an important electronic property that measures the charge distribution asymmetry and the intermolecular interactions inside the molecule. The difference in electronegativity between Cd atom (1.69) and C atom (2.55) leads to induce a charge transfer from the Cd atom to the sheet, which in turn induces the dipole moment. Accordingly, the energy change in the electron transfer of the G–CdO composite decreased to −8.516 e. V, which indicates that the charge transfer interaction is energetically favorable (as ΔE < 0). In the same context, the value of ΔNmax (=3.623 eV) emphasizes the presence of intramolecular charge transfer within the composite, which elucidates its reactivity. When the ratio (ΔE/ΔNmax) = 0 this means the compound is saturated with electrons and no charge transfer occurs. The calculated total electron energy of the ground state for the G–CdO complex is −31 789.8 eV showing minimum total energy among all three systems (−25082.1 eV for graphene and −6707.2 eV for CdO).To characterize the chemical stability and reactivity of the G–CdO complex, the energies of electronic parameters; HOMO, LUMO and their electronic gaps, I, and affinity properties A are so important to calculate the absolute hardness η and the electronegativity χ. The CdO has the largest absolute affinity value, so that will be a better electron acceptor during the interaction with plain graphene, which will be the electron donor. G–CdO has the lowest potential ionization value of 5.042 eV, so it is a better Lewis base (electron donor). Thus, according to DFT calculations, G–CdO is predicted to have a % removal efficiency for lead ions higher than individual graphene and CdO. The global electrophilicity index (ω) is a measure of energy lowering during accepting electrons. The electrophilicity value of G–CdO was the lowest, which strengthens its ability to act as an electrophile compared to single graphene and CdO. Therefore, the G–CdO composite is speculated to bind with lead ions and act as a nucleophile more than plain graphene and CdO systems.As listed in 53 and demonstrated in For a better understanding of the deposition of CdO onto graphene sheets and its effect on the electronic properties of the formed composite, the total and partial density of states plots of the G–CdO complex was calculated and analyzed. The energy gap and energy level for both graphene and graphene–CdO molecules have been demonstrated in 54 The MEP plots at G and G–CdO surfaces are represented in ii) would preferentially attack G–CdO at oxygen positions. The yellowish color near localized at the pi system of graphene represents the area of less electrophilicity of the compound as compared to oxygen atoms, while the blue regions of the composite are spread on the cadmium atoms. The MEP contour map of G–CdO confirmed that oxygen atoms are electrophilic sites to remove cationic Pb(ii) ions, It initially used to predict relative reactivity. It is the total interaction of the net charge distribution (electrons + nuclei) with partial charges, dipole moments, reactivity sites and electronegativity of a compound. Also, MEP explains the relationship between the structure and reactivity in molecule.E2 resulting from the second-order Fock-matrix analysis. Therefore, the greater extent of donor–acceptor interaction and conjugation the greater is the values of E2 and the charge transfer between the orbitals (filled and empty) of the whole system. Such interaction leads to a decrease in the occupancy from the idealized Lewis structure (lone pair or bonding) to a non-Lewis virtual orbital (anti-bonding or Rydberg). The most important interactions between Lewis type and non-Lewis type NBO along with, E2, their stabilization energies are calculated and listed in Table S1.−1, respectively. Other significant intramolecular interactions are from LP*(6)Cd38 to LP*(8)Cd37 corresponds to stabilization energy 87.7 kJ mol−1. The charge transfer from LP*(1) C4 to BD*(2) C5–C6, from LP (1) C13 to BD*(2) C11–C12 and from LP*(1) C33 to BD*(2) C30–C35 corresponds to 84.64, 82.26 and 82.16 kJ mol−1, respectively. Such results match well with those previously conducted after optimization and correlate with the fatal function of density donation during the anchoring of CdO onto graphene sheets. However, the graphene system could also accept electronic sharing from Cd atoms via the back-donation process besides its tendency to give electrons.Natural bond orbital (NBO) analysis is an efficient way to explore inter-and intramolecular bonding within the molecule such as charge transfer or conjugative process, charge distribution and donor–acceptor interactions. This analysis investigates the relationship between the filled NBOs (donors) and virtual or empty NBOs (acceptors). Such interaction is proportional to the stabilization energy ρ(r) and its derivatives to analyze the various kinds of intermolecular forces and can be expressed as:The RDG analysis is a non-covalent intermolecular identification and visualization tool. It is a dimensionless function based on the density λ2) of the Hessian matrix and ρ(r) in each point of the isosurface as it equals to the product of ρ and signs of λ2.55 Each specific value of RDG on the Y-axis has a region on the X-axis that can be classified into three types, strong attraction corresponds to sign λ2(r)ρ(r) < 0, strong repulsion corresponds to sign λ2(r)ρ(r) > 0 and weak interaction corresponds to sign λ2(r)ρ(r) ≈ 0. Therefore, to study the non-covalent reaction within the G–CdO composite, the RDG(r) vs. sign(λ2)ρ(r) function plot (scatter graph) is investigated at low gradient regions and is compared to the G scatter graph, λ2(r)ρ(r) > 0 due to the steric clash in the ring structures. The RDG scatter graph of G–CdO, λ2(r)ρ(r) > 0 indicating a steric interaction inside the graphene rings, as elucidated in the G scatter graph. In addition, the spike at negative density values indicates the attractive stabilizing dipole–dipole interaction due to the binding of CdO onto the G surface. To visualize the non-covalent interaction locations, λ2(r)ρ(r) value. The red regions show destabilizing repulsive steric nonbonding positive clashes while the blue region depicts the negative attractive dipole–dipole forces. The green region with values close to zero indicates weak dispersion-stabilizing interactions such as π stacking and van der Waals interactions. The obvious significant changes in the G isosurface features after the interaction with CdO indicate that the graphene/CdO interactions were strong and the system displays strong van der Waals interactions. Therefore, the RDG analysis is in good agreement with that conducted with NBO analysis.There is a direct correlation between the magnitude of the intermolecular interactions and both second derivative eigenvalue  mean regions with delocalized electrons, while high ELF values (>0.5) describe domains with localized bonding and antibonding. Domains with perfect localization take the value of 1. n = 8) was performed to evaluate the precision of removal. The precision expressed as percentage relative standard deviations (% RSDs) was 1%, The intra-day repeatability  metal is still more than 89.6% after repeated four cycles, indicating that the prepared nanomaterials have good recyclability as adsorbents. Thus, the surface of the nanoadsorbent under investigation gained positive charges and Pb(ii) ions almost desorbed into the acidic solution, indicating that the mechanism of ion exchange may be included in the sorption reaction. It can be concluded that, significantly, graphene-based CdO nanocomposite shows reusability and durability properties even after 4 regenerations. The marked regenerability of G–CdO can be assigned to its stable structure, facilitating its application in environmental treatment as no cadmium was detected in the solution, demonstrating that the nanocomposite was stable under the employed experimental conditions.The two most pivotal features, which a good adsorbent should show are reusability and durability. To assess the possibility of regeneration and reusability of prepared nanomaterials as adsorbents, desorption experiments were carried out with 0.1 N HCl as an eluent and pH kept >2 to prevent leaching of CdO out of graphene. After extraction in an acidic medium, the recycled G–CdO was washed and reused again. The impact of four consecutive adsorption–desorption cycles was studied, The mechanism of lead uptake onto nano G–Cd composite is based on the adsorption isotherm and kinetics data discussed previously, as well as experimental FTIR data shown before and after the lead adsorption process.G–CdO and CdO were successfully prepared using reducing and stabilizing agents present in the onion extract. FTIR analysis of the onion extract and nanomaterials is similar to some shifts due to the capping of nanoparticles with onion compounds. Thus, CdO NPs induced the coating of graphene sheets with many organic moieties. Also, FTIR confirmed the covalent bonding between graphene sheets and the modified CdO surface, while the SEM/TEM images showed the CdO NPs anchored at the surface of graphene sheets.−1 (stretching vibration of H-bonded and N–H bond) and 1634 cm−1 (carboxylic) decreased and shifted after lead adsorption, −1 appeared.56 The above analysis revealed the reduction of N–H and H-bonds in the functional groups and the replacement of lead ions in these active sites during the adsorption process. Similar results have been reported47 and confirmed a mechanism based on the formation of complexes or ion exchange with organic groups that wrapped nanomaterials. In the other work, Zhang et al.57 confirmed that both amine and carbonyl/hydroxyl groups within N doped adsorbent are responsible for lead adsorption. Li et al.57 used a polydopamine and MnO2 coating to remove Pb(ii) ions and they observed that the N contained groups in polydopamine also bind with lead ions. Besides, they have conducted that both amine and carbonyl/hydroxyl groups contribute to lead uptake through chelation. ii) from the environment.To study the mechanisms of as-prepared nanoadsorbents for Pb removal, an FTIR study was carried out. Comparing the FT-IR analysis before and after adsorption, it was found that the intensities of the peaks at around 3440 cm−1, respectively. Pseudo-second order kinetic model and Langmuir isotherm explained the process. The thermodynamic studies were conducted through spontaneous, physical, and endothermic sorption reactions. The experimental results of %lead removal matched well with the DFT theoretical study of the nanocomposite tested. The energy of the perturbation of the Fock matrix depicted strong intramolecular interactions. Various kinds of donor Lewis–acceptor and non-Lewis interactions play a great function in composite stabilization. The RDG analysis is in good agreement with that conducted with NBO analysis as a significant change in the G–CdO isosurface features after the interaction with CdO indicates that graphene/CdO interactions were strong and the system displays strong van der Waals interactions. Also, the study confirmed that the uptake of lead ions onto prepared nanomaterials was mainly attributed to the electrostatic attraction forces and surface complexation. Additionally, CdO NPs and G–CdO composites could be regenerated and used repeatedly at least four times without significant loss in performance, allowing the as-prepared nanoadsorbents to be potentially applied to in situ lead removal from aqueous solutions.CdO NPs and G–CdO composite were prepared and characterized. Results of FT-IR, SEM, EDX, TEM, XRD, UV-Vis analyses demonstrated that CdO NPs and G–CdO composites were successfully synthesized. Taken together, the integration of graphene and CdO NPs created a novel nanomaterial that potentially removes lead from an aqueous solution. The results of the batch adsorption experiments implied that the maximum adsorption capacities of CdO and G–CdO were 398 and 427 mg gThere are no conflicts to declare.RA-011-D1RA04754J-s001


R2 = 0.973), which were far superior to their QCM counterparts. The underlying mechanism was revealed and discussed.Humidity sensors with comprehensive performance are of great interest for industrial and environmental applications. Most sensors, however, have to compromise on at least one characteristic such as sensitivity, response speed, and linearity. This paper reports a gravimetric humidity sensor based on a capacitive micromachined ultrasonic transducer (CMUT) with exceptional all-around performance, and presents a side-by-side comparative investigation of two types of gravimetric humidity sensors for a better understanding of their characteristics and sensing mechanisms. For these purposes, a circular CMUT and a quartz crystal microbalance (QCM) with a resonance frequency of 10 MHz were designed and fabricated. Poly (PVA) was employed as the humidity sensing layer for its hydrophilicity and ease of film formation. The electrical properties of the sensors, including the electrical input impedances and quality factors, were characterized by a vector network analyzer. The relative humidity (RH) sensing performance of the sensors was evaluated and compared from RH levels of 11% to 97%. Both sensors exhibited good repeatability and low hysteresis. The unique microscale resonant structure of the CMUT humidity sensor contributed to a high sensitivity of 2.01 kHz/%RH, short response and recovery times of 8 s and 3 s, respectively, and excellent linearity ( Humidity detection plays a crucial role in various applications, including environmental control and industrial processing ,2. For eGravimetric sensors are widely adopted for humidity sensing due to their high sensitivity and fast response. They work by converting the mass change of water molecules into the shift of the resonance frequency. The quartz crystal microbalance (QCM) is the most popular of the gravimetric sensor types for its maturity, low cost, and capability of detecting mass changes down to the nanogram level ,7. The aIn recent years, an attractive candidate for humidity sensor platforms, the capacitive micromachined ultrasonic transducer (CMUT), has emerged to compete with QCMs. As another type of gravimetric sensor, CMUT is developed from micro-electro-mechanical system (MEMS) technology . Hence, In most situations, a more competitive humidity sensor is the one that has comprehensive performance of sensitivity, repeatability, linearity, response speed, and hysteresis. This requires the sensor and the functional material to work synergistically. Poly (PVA) is a low-cost, non-toxic, and biodegradable polymer with outstanding mechanical and film-forming properties, chemical and thermal stability, and water-solubility . These fAs an increasing number of chemical sensors are emerging, comparative studies are necessary for a better understanding of their characteristics and sensing mechanisms. Robinson et al. compared capacitive- and resistive-based transduction mechanisms using single-walled carbon nanotubes , and conIn this paper, we developed a high-performance CMUT-based humidity sensor and presented a side-by-side comparison with a QCM counterpart to provide more insights into the two types of gravimetric sensors. The CMUT and QCM humidity sensors based on the PVA active layer were designed, fabricated, and characterized. The RH sensing properties of the two sensors, including the sensitivity, linearity, reproducibility, repeatability, response speed, and long-term stability were experimentally studied and compared. The underlying mechanism that caused the distinct sensing characteristics was revealed and discussed.As presented in Here, a 10 MHz AT-cut QCM with silver electrodes was derived from Wuhan Hitrusty Electronics Co., Ltd.,  the photograph of which is shown in 3N4) was selected as the membrane material due to the fabrication process. Consequently, the structural parameters of the membrane governed the resonance frequency of the device. As the resonance frequency was designed as 10 MHz, the thickness and radius of the membrane were determined accordingly to be 520 nm and 15 μm, respectively. A 100 nm thick electrode layer was deposited on the top of each membrane. The cavity depth was designed to be 180 nm to allow free vibration of the resonant membrane. The insulation layer was designed as 450 nm to avoid breakdown of the device. The CMUT was composed of 5380 units connected in parallel.A 10 MHz circular CMUT was designed for comparison with the commercial QCM. The diameter of the CMUT was designed to be 3 mm, which ensured the fabrication yield and was also close to that of the QCM electrode for a relatively fair comparison. The resonance frequency of the CMUT is determined by :(1)fc=0.2) layer. The substrate was then bonded in a vacuum with a silicon-topped wafer, which was deposited with an LPCVD Si3N4 layer on both sides. Subsequently, the resonant nitride membrane was released by removing the backside nitride layer and the silicon handling layer on the top wafer. After exposing the bottom electrodes, Cr/Al metal electrodes and contact pads were deposited and patterned. 3N4 membrane, the SiO2 insulation layer, and the silicon substrate can be identified in the image.The CMUT was fabricated by the MEMS fabrication process based on the nitride-to-oxide wafer bonding technique . To starThe PVA powders with a viscosity of 54.0 mPa·s were derived from Sinopharm Chemical Reagent Co., Ltd., . Then, 10 mg of the PVA powder was dispersed in 19.99 g ultrapure water and stirred by a magnetic stirring bar at 90 °C for 3 h until the powders were completely dissolved. Afterward, the dispersion was left at room temperature for 12 h for cooling down and degassing. Then, 7 μL of the 0.05 wt% PVA dispersion was drop-casted on the surface of the CMUT and the QCM, respectively. Lastly, the sensing films were dried by baking at 60 °C for an hour.11 parameters of the sensors were measured by the VNA and converted to electrical impedances and admittances.The surface morphology of the PVA layers on the CMUT and QCM sensors were examined by SEM . The electrical properties of the sensors were characterized by a vector network analyzer (VNA). As the CMUT requires a bias voltage to bring its resonating membrane close to the substrate for higher efficiency, it was biased at 35 V by a DC power supply  and connected to a streamline USB VNA  through a bias tee, while the QCM was directly connected to the VNA. The S3COOK, MgCl2, K2CO3, NaBr, NaCl, KCl, and K2SO4, respectively [The humidity sensing measurements were conducted by monitoring the sensors’ frequency changes while alternating the RH environments at room temperature. RH levels of 11%, 23%, 33%, 43%, 58%, 75%, 84%, and 97% were generated by saturated salt solutions of LiCl, CHectively . Figure From Generally, a high quality factor of 300–500 is achievable by the CMUT despite the massive parallelism , becauseReproducibility, Sensitivity, and LinearityIt is known that both the CMUT and the QCM sensors rely on the detection of resonance shifts in response to the loaded mass equation :(3)Δfq=−From Equations (2) and (3), the theoretical mass sensitivity of the CMUT was calculated to be 4.2 Hz/fg, which was six orders of magnitude higher than that of the QCM (1.15 Hz/ng). Within the RH level of 58%, however, it is observed from From Dynamic response and hysteresisResponse/Recovery time and RepeatabilityThe dynamic frequency responses of the CMUT and QCM sensors were evaluated as the RH switched between 11% and 84%. The repeatability of the sensors was examined by switching the RH from 11% to 58%, 75%, and 84% for five cycles. As shown in Temperature dependence and long-term stabilityIt is well known that the properties of semiconductors and quartz are temperature-dependent. Therefore, the temperature dependence of the CMUT and QCM sensors was studied. The long-term stability of the sensors was investigated by measuring their frequency shifts in different RH environments a few times over 45 days. This work reports a high-performance CMUT-based humidity sensor using PVA as the sensing film. In addition, to the best of our knowledge, this work provides the first side-by-side comparative study of the CMUT and QCM sensor platforms. The two types of gravimetric humidity sensors were designed and fabricated. Their electrical properties were characterized by a VNA and the humidity sensing performance was examined over a wide RH range from 11% to 97%. Although the working principles of both sensors were based on the mass-loading effect, the QCM worked as a single element while the CMUT involved massive parallelism, which led to a huge difference between their effective oscillation areas of four orders of magnitude. Consequently, a considerable discrepancy between their RH sensitivity and theoretical mass sensitivity was observed. Despite the small effective oscillation area of each unit, the CMUT humidity sensor exhibited a high RH sensitivity of 2.01 kHz/%RH, which was about three orders of magnitude higher than that of the QCM sensor. In addition to the high sensitivity, the unique microstructure has also provided the CMUT humidity sensor with excellent all-around performance, including a short response/recovery time of 8 s/3 s, good reproducibility and linearity, and low hysteresis. The experimental results demonstrated the superiority of the CMUT sensor platform over the QCM counterpart. The major drawback of the CMUT sensor was the need for a DC bias voltage to pre-displace the resonant membrane. The bias voltage was 35 V in this work. It could be improved by optimizing the structural parameters of the device. For instance, by minimizing the cavity depth, reducing the bias voltage to 6-8 V is possible, which would be favorable for portable humidity sensing applications.


Children start to run after they master walking. How running develops, however, is largely unknown.We assessed the maturity of running pattern in two very young, typically developing children in a longitudinal design spanning about three years. Leg and trunk 3D kinematics and electromyography collected in six recording sessions, with more than a hundred strides each, entered our analysis. We recorded walking during the first session (the session of the first independent steps of the two toddlers at the age of 11.9 and 10.6 months) and fast walking or running for the subsequent sessions. More than 100 kinematic and neuromuscular parameters were determined for each session and stride. The equivalent data of five young adults served to define mature running. After dimensionality reduction using principal component analysis, hierarchical cluster analysis based on the average pairwise correlation distance to the adult running cluster served as a measure for maturity of the running pattern.Both children developed running. Yet, in one of them the running pattern did not reach maturity whereas in the other it did. As expected, mature running appeared in later sessions . Interestingly, mature running alternated with episodes of immature running within sessions. Our clustering approach separated them.An additional analysis of the accompanying muscle synergies revealed that the participant who did not reach mature running had more differences in muscle contraction when compared to adults than the other. One may speculate that this difference in muscle activity may have caused the difference in running pattern. Independent walking is a major developmental milestone for children. In typically developing children it commonly occurs between 9 and 15 months of age . While mIn a previous work we studied 5-9-year-old children . There wAs it turns out, there is no immediate agreement between the chronological age and the maturity of treadmill walking and running patterns . Yet, thTackling such commonalities is a challenge, which may fail when following more traditional routes in studying locomotion, namely from either a sole neuromuscular e.g.,  or a solAnswering the relation between the onset of independent walking and the development of running requires longitudinal assessments spanning several years. To quantify the influence of time since onset of independent walking, one must assess participants at the very onset of independent walking (in fact assesement have to start even before that). And recordings must be frequent enough to properly sample the development of running. We monitored two typically developing children for about three years after their first independent walking steps. We conducted seven experimental sessions during each of which we guaranteed more than 100 running strides when recording leg and trunk 3D kinematics and electromyography (EMG). Using the aforementioned shotgun method that encompasses kinematics and neuromuscular data, we investigated the earliest development of running. Possible mechanisms underlying the coordinated locomotion were explored through muscle synergy analysis and by integrating some of the corresponding outcome parameters in the shotgun approach. We expected this approach to allow for determining the degree of maturity also in very young children who just learned / are learning to run. We expected the development of running maturity to be similar, if not identical, to the onset of independent walking when stratifying its time course.We recruited two children and five adults. The two children  were recruited before taking their first independent steps as part of a larger study . The aduThe first recording session of each child participant took place within 9 days of taking at least four consecutive steps without support. The time of first indpendent steps were relayed by the parents to the researchers.Seven sessions were recorded from first steps (FS) to ∼ 32 months after onset of independent walking for each of the two children (P1 and P2). The initial plan was to record each child every three months from their first independent steps until one year after onset of independent walking with a follow-up every six months from that timepoint. As this was not achieved with the first child, we matched the second child to the spacing of the recordings of the first child. As sketched in The experiments consisted of locomoting overground and on a pediatric treadmill  with either no support or trunk/hand support. During the first session (FS), only walking was recorded. During the subsequent sessions, we recorded both walking and fast walking and/or running. Children were tasked to move from one end of the lab to the other end. They were instructed to either walk or run, sometimes enticed with toys or food. When the child was instructed to run, but the speed was between their normal running and walking speed, then the trial was noted as “fast walking”. For sessions +6, +9, +13, +19, and +32, only the trials labelled as fast walking or running were retained for further analysis.All children sessions, except one, were recorded in the BabyGaitLab of the Department of Human Movement Sciences at the Vrije Universiteit Amsterdam, The Netherlands; the remaining session was recorded at the clinical gait laboratory of the Department of Rehabilitation Medicine at the Amsterdam UMC (location VUmc). The adults were recorded in the laboratory of the Santa Lucia Foundation, Rome, and included in a previous publication .The children were barefoot during all recordings and wore only diapers or underpants. When locomoting overground, they were encouraged by researchers/parents to walk/run in a straight line. Sometimes they were supported by handhold. When on the treadmill, the speed was adjusted to a comfortable speed and type of locomotion . On the treadmill, the children were supported on trunk or by handhold by the researcher/parent. Adults were running at 7 and 9 km/h on a treadmill  wearing shoes.2), placed at the approximate location of the muscle belly on the cleaned skin, with interelectrode spacing of ∼1.5 cm. The placement followed the SENIAM recommendations  with 10 (12 for the session recorded at VUmc) infrared cameras affixed to the ceiling, sampled at 100 Hz and one (four for the session recorded at VUmc) video camera  sampled at 100 Hz (50 Hz for the session recorded at VUmc). Reflective markers (14 mm) were placed bilaterally on the acromion (SHO), iliac crest (IL), greater trochanter (GT), lateral femur epicondyle (LE), lateral malleolus (LM) and fifth metatarsal (VM). For each session, a static trial was recorded where the participant was standing still to be used for correction of the joint angles. We recorded electromyography (EMG) bilaterally from the following 16 muscles: tibialis anterior (TA), medial gastrocnemius (MG), lateral gastrocnemius (LG), soleus (SOL), rectus femoris (RF), vastus medialis oblique (VMO), vastus lateralis oblique (VLO), semitendinosus, biceps femoris (BF), tensor fascia latae (TFL), gluteus maximus (GLM), erector spinae level L2 (ES), latissimus dorsi, trapezius, deltoid, and biceps brachii. EMG was recorded using mini-golden reusable surface EMG disc-electrode pairs  provided to the children during treadmill trials were estimated as the percentage reduction of the mean vertical forces compared to  walking . Thus, oData acquisition has been described previously in v), leg length (l), and the gravitational constant (g) using: Fr = v2/(g ⋅ l). Kinematic parameters were calculated based on the 3D kinematics of the lower legs and trunk. The body was modeled as an interconnected chain of rigid segments: SHO-IL for the trunk, IL-GT for the pelvis, GT-LE for the thigh, LE-LM for the shank, and LM-VM for the foot. The main limb axis was defined as the virtual line connecting GT and VM. Joint and elevation angles were generated accordingly. A total of 101 parameters were estimated for each gait cycle using a custom-written algorithm  in the children. For the adults, foot contact was defined as the local minima of the heel marker and foot off as the lift-off of the VM marker by 2 cm from the minimum detected at stance . Strideslgorithm  to provind-order bi-directional Butterworth around k⋅50 Hz, k = 1,…,10, with half-bandwidth of 0.5 Hz), the EMG data were rectified using the modulus of the analytic signal and finally low-pass filtered  to obtain the corresponding EMG envelopes  muscles TA, MG, LG, SOL, RF, VMO, VLO, BF, TFL, GLM, and ES were retained for further analysis. EMG data were visually inspected, and artifacts were removed using a custom-written burst-detection algorithm . After hnvelopes . These e6 iterations, and a completion threshold of 10–6) to account for missing strides (C) and weighting coefficients (W):Before applying the muscle synergy analysis, the amplitude of the EMG activity was normalized to the mean activity for each muscle, interpolated in case of missing values (for a maximum of 50% of the stride) within one stride, and finally concatenated for each session in a [#strides × #samples] × #muscles matrix ([n × 200] × 11). Post-hoc analysis of the interpolation revealed that the mean interpolation was 4.5% for P1 (range: 0.5%-19.5%) and 4.6% for P2 (range: 0.5%-34%) in approximately 22% and 22.6% of the total number of strides, respectively. The gaps were not necessarily consecutive. No interpolation was done on the adult data. Muscle synergies were calculated using weighted non-negative matrix factorization (WNMF) algorithm . For the synergy analysis, the grand average of all strides for each synergy was determined per session.To quantify differences in the duration of the temporal activation patterns of the muscle synergies, we estimated the full width at half-maximum (FWHM) per activation pattern and stride. Here we first subtracted the minima of the activity patterns – in the case of several peaks, the FWHM was calculated for the main peak, i.e., the peak with the highest amplitude and in case of boundary peaks, an assumption was made that the shape of the peak was symmetric . Timing t = 200 samples). The FWHM and the CoA for the extracted synergies were retained and added to the list of gait parameters for further analysis to have a spatial as well as temporal measure for the activation patterns of the muscle synergies  were included. We chose for this ‘blind’ approach as our previous research revealed that in very young children the presence of a flight phase is not a solid indicator for the presence of running . We empln = 107 parameters.For every participant, parameters were combined in a [(number of sessions × number of strides) × number of parameters] matrix [1730 × 107] and z-scored prior to PCA, see Finally, we applied hierarchical clustering with correlation distance . We firsMeans and standard deviations are provided unless otherwise specified. To investigate whether the dimensionless speed Fr and the FWHM of the muscle activation patterns were different between sessions for each participant and comparable to the adults, we used a non-parametric test, the Kruskal-Wallis test, as the data were not normally distributed, confirmed using a Kolmogorov-Smirnov goodness-of-fit hypothesis test. If a statistically significant effect was found, a Bonferroni correction was applied to account for multiple comparisons. With 7 mixed within-between participants (6 sessions for the toddlers and 1 session for the adults), the used significance threshold was α=0.05/7=0.007.Our child participants were comparable in terms of age as well as time in months since first independent steps. P2 started walking at 10.6 months whereas P1 started walking at 11.9 months. Both children were relatively early walkers. The median age of independent walking lies between 11.4 months  and 13.02.2 Setup for further details) were analyzed.The first sessions, the FS sessions, were recorded within 9 days of when the children performed at least four independent strides, and for these sessions only walking was recorded. In the subsequent sessions, the children were instructed to either walk or run, but only strides from trials when instructed to run . The +2 months sessions were excluded due to insufficient data quality or an insufficient amount of data recorded. See The mean number of strides included per session was (mean ± std) 133 ± 73 strides for the toddlers’ sessions and a total of 105 strides for the adults (range 14-24 per participant). The FS session for P1 had an exceptionally large number of strides that could be included. To make the number of strides more balanced across sessions, only overground strides with a velocity of more than 0.5 km/h were retained, reducing the total number of strides from 729 to 254 strides for this specific session. Several strides with a Froude number exceeding 1.5 were excluded from the sessions +19 and +32 for both P1  and P2  as they were deemed to be sprinting and as such were not comparable to the other data.p < 1 × 10−14 for all sessions for both participants). The normalized speeds ranged between 0.34 and 0.69 for the running sessions and three sessions of P1  and two sessions of P2  were significantly different from the adults, cf. The FS sessions had only strides with double support phases whereas the remaining sessions had a mixture of strides with double support and flight phase. The double support and flight phases were expressed as a percentage of the gait cycle. Double support phases were present in all sessions (after the FS sessions) of P1 and P2, with a tendency towards an increased amount of flight phase in the last sessions. The flight phase was shorter than in the adults. The linear regression of the double support phase revealed a significant effect of session, no effect on participant, and only a small interaction effect between session and participant cf., . The linLike the presence of a flight phase, the Froude number might also not be a good indicator of whether a child is running. The Froude number, the normalized speed, is useful to determine the optimal speed at which to transition from walking to running or vice versa, and in adults this transition occurs at a Froude value of 0.5  which thCI95 except for three. The three parameters not contributing were parameters 74, 79, and 88, i.e., the phase relationship between the two limbs (a measure for interlimb coordination), projection of 1st eigenvector on the shank axis  accounted for > 45% of the total variance of the data. The scatterplots in We found three clusters, see The differences in the developmental trajectories shown in The reconstruction accuracy (RA) revealed different numbers of muscle synergies between sessions with median of three muscle synergies (IQR: 3:4.5) across all sessions. The RA was 64.2 ± 1.8, 64.1 ± 2.6, and 66.3 for P1, P2, and the adults, respectively, for three synergies. The temporal activation patterns of the first of the three synergies had the most activity at foot contact, the weight acceptance phase, with the knee extender muscles  being the predominant influencers both for toddlers and adults with some contribution also of the TFL and GLM muscles cf. . The secp < 0.0001 for synergy 1, +6, +13, +32 were all p < 0.001 for synergy 2) with some in-between significant differences between the sessions within P1 and P2. Synergy 3 of P2 had a characteristic pattern of a reduction of the FWHM from the first running session (+6) to the last running session (+32) with significant p-values of p < 0.0001 for the +6 session compared to +19, +32, and adults and p = 0.0067 for the +6 session compared to the +13 session.FWHM and CoA mark the ability to quickly contract a muscle and the timing of the muscle contraction, respectively. The FWHM of the temporal patterns of the three synergies was comparable across sessions with a large variance between strides cf. . The mosp < 6 × 10−4 and p < 2 × 10−16, respectively). Here, the adult patterns were similar with a mean of 13.3% ± 3.6% of the gait cycle for the second component.The CoA of the synergies were way more variable in the children than in the adults. In the latter the CoAs were within the same 25% of the gait cycle across strides . For the first and third pattern, the range of the CoA for P1 and P2 covered all percentages of the gait cycle for all sessions. Most noteworthy is the mean CoA for the second temporal pattern which occurred later in the FS sessions (31.6% ± 18.5% and 56.3% ± 18.7% of the gait cycle) for P1 and P2, respectively, compared to the mean over the other sessions, which ranged from 13.8% to 16.0% for P1 and 13.6% to 20.2% for P2 , already in PC1-PC2 space the first step session (very dark blue) was indeed close to the adults. In a future study we will compare new walkers to very experienced runners. There we will also include adult walking, i.e., experienced walking, and expect that the FS strides will becloser to this cluster than to adult running.In the current two children we cannot pinpoint a moment when the running pattern differs from the walking pattern and becomes like the adult running pattern. This is mostly due to a substantial variability between and within sessions in the majority of outcome variables. We would like to stress anyway that we were able to show that the two toddlers seemingly display different paths towards running maturity.We determined three muscle synergies. This number is smaller than in many other studies on running where the number is usually four or more . We chosSynergy 2 shows a phase shift as evidenced in the CoA from 30-50% of the gait cycle for the FS session to around ∼15% of the gait cycle for the later sessions. The phase shift occurs from the +6 session and is stable across the running sessions, which indicates that a contraction of the foot flexors matching the shorter stance phase is important for even early running patterns.The analysis of FWHM of the temporal activation patterns of the muscle synergies allowed us to quantify the duration of activity of the muscles contributing to this particular synergy. FWHM of motor primitives or muscle synergies has previously been hypothesised to be a measure for robustness of the motor control . For botThe EMG was processed by normalizing the amplitude to the mean of the data across strides. According to The main limitation of this study is the lack of power by only having two participants. Without a doubt this limits the ability to generalize our results. Despite the lack of generalizability, we consider it a valuable starting point, first in methods and – more importantly, in clarifying that time since onset of independent walking does not appear to be a solid indicator of the maturity of running patterns in very young children.The two clusters, C3 “walking” and C2 “immature running” were so close to each other that they are just overlapping in terms of our measure of maturity, the mean pairwise correlation distance to that of the adults. This may suggest that a cluster solution with three clusters may not have been optimal. However, the mean pairwise distance to the adults did not change with an altered number of clusters. We are hence convinced that our measure can be used for determining the “order of maturity”. On the other hand, the FS session of P1 can be considered more mature than +6 and +9, two sessions containing running strides. Apparently, the distance measure and linkage method used to create the dendrogram was less optimal than in our previous study . HoweverFuture research should be focused on investigating larger number of children. When doing so, we advocate combining many kinematic and neuromuscular parameters to fully investigate the development of the running patterns in very young children.Our study is unique in that the development of running was monitored longitudinally over a three-years span with highly frequent assessments of kinetics, kinematics, and electromyography. It provides a first view on the effect of time since onset of independent walking on the development of running. Running development followed different trajectories that we quantified ‘blindly’ via a shotgun approach after combining various biomechanical and neuromuscular parameters. Evidently, the development of running can take different trajectories including the co-existence of immature and mature running within the same session in a child. Muscle synergy analysis may help explaining why the development can differ between children, though there is a long way to clarifying this with statistical robustness.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Scientific and Ethical Review Board of the Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Netherlands (File number: VCWE-2016-082) and the Ethics Committee of the Santa Lucia Institute, Rome, Italy (Prot. CE-AG4-PROG.99-155). Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin. Written informed consent was obtained from the minor(s)’ legal guardian/next of kin for the publication of any potentially identifiable images or data included in this article.MB: conceptualization, formal analysis, investigation, data curation, writing – original draft, writing – review and editing, and visualization. CZ: conceptualization, investigation, and writing – review and editing. GC and FL: investigation and writing – review and editing. YI: investigation, funding acquisition, and writing – review and editing. AD: writing – review and editing, supervision, and visualization. ND: conceptualization, formal analysis, investigation, writing – review and editing, supervision, and funding acquisition. All authors contributed to the article and approved the submitted version.


Hypoxia is a sentinel feature of idiopathic pulmonary fibrosis (IPF). The IPF microenvironment contains high lactate levels, and hypoxia enhances cellular lactate production. Lactate, acting through the GPR81 lactate receptor, serves as a signal molecule regulating cellular processes. We previously identified intrinsically fibrogenic mesenchymal progenitor cells (MPCs) that drive fibrosis in the lungs of patients with IPF. However, whether hypoxia enhances IPF MPC fibrogenicity is unclear. We hypothesized that hypoxia increases IPF MPC fibrogenicity via lactate and its cognate receptor GPR81. Here we show that hypoxia promotes IPF MPC self-renewal. The mechanism involves hypoxia-mediated enhancement of LDHA function and lactate production and release. Hypoxia also increases HIF1α levels, and this increase in turn augments the expression of GPR81. Exogenous lactate operating through GPR81 promotes IPF MPC self-renewal. IHC analysis of IPF lung tissue demonstrates IPF MPCs expressing GPR81 and hypoxic markers on the periphery of the fibroblastic focus. We show that hypoxia enhances IPF MPC fibrogenicity in vivo. We demonstrate that knockdown of GPR81 inhibits hypoxia-induced IPF MPC self-renewal in vitro and attenuates hypoxia-induced IPF MPC fibrogenicity in vivo. Our data demonstrate that hypoxia creates a feed-forward loop that augments IPF MPC fibrogenicity via the lactate/GPR81/HIF1α pathway. Idiopathic pulmonary fibrosis (IPF) is a lethal progressive fibrotic lung disease, where the unrelenting scarring of alveolar gas-exchange units results in progressive hypoxia and death by asphyxiation –6. AlthoIn a hypoxic environment, lactate production increases as the anaerobic cycle is utilized for energy production. While lactate has long been known to play an essential role in cellular metabolism, more recently, lactate has been discovered to serve as a signal molecule regulating a variety of cellular processes associated with cancer progression and cardiovascular disease –15. In tHere, we show that the highly cellular region at the periphery of the fibroblastic focus contains IPF MPCs expressing hypoxic markers. We show that, under normoxic conditions, the intrinsically fibrogenic IPF MPCs display increased levels of markers of glycolysis and lactate compared with control MPCs. Importantly, we demonstrate that hypoxia markedly enhances lactate production and release in IPF MPCs. We show that hypoxia increases HIF1α levels. In turn, HIF1α binds to the lactate receptor GPR81 promoter, thereby increasing the expression of GPR81, suggesting that, in response to hypoxic conditions, HIF1α promotes GPR81 expression via increasing GPR81 transcription. We demonstrate that exposure to hypoxic conditions promotes IPF MPC self-renewal. Similar to hypoxia, exogenous administration of lactate promotes IPF MPC self-renewal. Knockdown of GPR81 abrogates hypoxia-induced IPF MPC self-renewal in vitro, and loss of GPR81 function markedly diminishes IPF MPC fibrogenicity in both a humanized mouse model of sustained interstitial fibrosis and in a zebrafish fibrosis model. Our results indicate (a) that cells on the periphery of the fibroblastic focus display markers of hypoxia that codistribute with IPF MPCs and (b) that hypoxia creates a feed-forward loop that enhances IPF MPC fibrogenicity via augmenting lactate production, release, and signaling via the GPR81 lactate receptor. These results identify the lactate/GPR81 axis as a potential therapeutic target to arrest IPF fibrotic progression.We previously discovered that the IPF lung contains intrinsically fibrogenic MPCs that cause nonresolving interstitial lung fibrosis in a humanized mouse xenograft model . We foun2 concentrations vary widely in tissues, at the cellular level, physiological O2 concentrations are generally in the 1%–11% range . These data indicate that IPF MPCs, which are intrinsically fibrogenic, display increased glycolysis and higher levels of lactate compared with control MPCs under normoxic conditions and that hypoxia markedly enhances intracellular lactate levels in IPF MPCs.Since hypoxia enhanced IPF MPC self-renewal, we next sought to elucidate the mechanism. Prior work indicates that IPF lung tissue contains high lactate levels  and thatSince hypoxia enhances lactate production and release in IPF MPCs, we next examined the effect of exogenous lactate  on IPF MPC self-renewal. Compared with no exogenous lactate, both 5 mM and 10 mM lactate stimulated IPF MPC self-renewal, while IPF MPC self-renewal was slightly lower with 20 mM lactate . TherefoWe next examined the effect of LDHA loss of function on IPF MPC lactate levels and self-renewal in response to hypoxia. Knockdown of LDHA decreased LDHA expression and activity and reduced lactate levels in IPF MPCs in response to hypoxia . Loss ofOur in vitro data indicate that hypoxia enhances lactate production and release and exogenous lactate promotes IPF MPC self-renewal. GPR81 is the cognate receptor for lactate, and lactate signaling through GPR81 can regulate a variety of cellular processes –19. Ther+ MPCs expressing GPR81 were present on the periphery of the fibroblastic focus  pathway and target the cAMP response element-binding protein (CREB) to affect cell function. To begin to assess the pathways downstream of GPR81 that affect IPF MPC self-renewal, we quantified PKA and phosphorylated CREB (pCREB ser133) levels in IPF MPCs in response to exogenous lactate. Lactate increased both PKA and pCREB levels . FurtherThe HIF1α transcription factor is a major regulator of protein expression in response to hypoxia , 43. Sin2) conditions (10% was the lowest O2 concentration permitted by the University of Minnesota IACUC). Lungs were harvested 4 weeks later. LDHA activity as a surrogate marker of lactate production was quantified. LDHA activity in the lungs of mice transduced with scrambled shRNA and exposed to hypoxia was increased compared with mice exposed to normoxia  mice pretreated with intratracheal bleomycin results in nonresolving interstitial lung fibrosis . To initWe next quantified the level of fibrosis in mice treated with IPF MPCs and exposed to normoxic and hypoxic conditions. We found that the collagen content and lung fibrosis score in mice receiving IPF MPCs transduced with scrambled shRNA and exposed to hypoxia were increased compared with mice receiving IPF MPCs transduced with scrambled shRNA and maintained under normoxic conditions  comparedWe next compared the fibrogenicity of IPF MPCs transduced with GPR81 to those transduced with scrambled shRNA in the humanized mouse model under hypoxic conditions. The collagen content and lung fibrosis score were significantly lower in mice receiving IPF MPCs in which GPR81 had been knocked down and exposed to hypoxia compared with mice receiving IPF MPCs transduced with scrambled shRNA and exposed to hypoxia  comparedTo quantify the number of human cells in mice receiving IPF MPCs transduced with GPR81 shRNA or scrambled shRNA, at the time of engraftment and at lung tissue harvest, we used a real-time PCR method shown to be sensitive for the detection and quantification of human cells in mice . The lun2 (the concentration of O2 used in the in vivo studies) on induction of apoptosis in vitro by quantifying caspase 3 levels. No significant change in caspase 3 levels was found  or normoxic conditions for 48 hours. The lungs were harvested and stained with Hydroxyprobe . Cell lines were derived from lungs, characterized as mesenchymal cells, and cultivated as previously described , fulfilling diagnostic criteria for IPF including a pathological diagnosis of usual interstitial pneumonia  at the tescribed .+ and CD44+   were collected. To generate sufficient numbers of MPCs for the in vivo mouse studies, SSEA4+CD44+ cells were expanded by culture in DMEM + 10% FCS for 7 days prior to use. The resulting MPC cultures were reanalyzed for SSEA4 expression by FACS analysis and for colony formation in vitro. In total, 97% of day 7 MPCs were SSEA4+ and formed colonies in methylcellulose indicating retention of progenitor self-renewal properties during in vitro expansion.For isolation of IPF and control MPCs, primary IPF mesenchymal cells were labeled with mouse anti–human SSEA4 antibody conjugated to Alexa Fluor 647  and mouse anti–human CD44 conjugated to FITC . Cells were sorted on a FACS Aria Cell Sorter (BD Biosciences). Cells that were SSEA42) or normoxic (21% O2) conditions for the duration of the experiment. For lactate stimulation, lactate (MilliporeSigma) in the indicated amounts was added to the media. Cells were cultured for 24 hours for most experiments, except where indicated.IPF or control MPCs were cultured under hypoxic . Briefly, IPF MPCs were cultured in RPMI-1640 for 18 hours and were then washed twice with PBS, followed by incubation for 30 minutes in basic RPMI-1640 . The cells were next cultured in Krebs-Ringer-Phosphate-Hepes (KRPH) buffer for 40 minutes, followed by incubation with the glucose analog 2-deoxyglucose (2-DG) for 20 minutes. Following steps per the manufacturer’s instructions, 2-deoxy-D-glucose-6-phosphate (2DG6P) levels were quantified at 420 nm with a SpectraMax M3 microplate reader (Molecular Devices). Lactate levels in IPF MPC lysates and conditioned medium were quantified using a lactate assay kit, per the manufacturer’s instruction (Abcam).2) or normoxic (21% O2) conditions. Enumeration of colonies was performed microscopically, and colony size was quantified by ImageJ (NIH). In some self-renewal assays, the cells were treated with the indicated concentrations of lactate (MilliporeSigma).Single-cell suspensions of IPF MPCs were incorporated into methylcellulose gels (Stemcell Technologies) and were maintained in MSC SFM CTS (Thermo Fisher Scientific) for 1 week under hypoxic (2% O4 IPF MPCs were added to the top of a filter insert (8 μm pore size) containing 100 μL of serum free DMEM in a 96-well plate. A total of 150 μL of DMEM was added to the lower chamber, and the cells were allowed to migrate for 16 hours under hypoxic (2% O2) or normoxic conditions (21% O2). The number of migrating cells were quantified using CyQuant GR dye and a fluorescence plate reader (SpectraMax M3). Alternatively, in some experiments, DMEM containing lactate was added to the lower well and migration was assessed.The effect of hypoxia or lactate (MilliporeSigma) on the migration of IPF and control MPCs was examined using the QCM Chemotaxis Cell Migration Assay Kit following the manufacturer’s instructions (EMD Millipore). Briefly, 2 × 10PLUS SYBR Green I Kit (Roche). Primer sequences were as follows: LDHA Forward: 5′-GCCCGACGTGCATTCCCGATTCCTT-3′; LDHA Reverse: 5′-GACGGCTTTCTCCCTCTTGCTGACG-3′; GPR81 Forward: 5′-AATTTGGCCGTGGCTGATTTC-3′; GPR81 Reverse: 5′-ACCGTAAGGAACACGATGCTC-3′; HIF1α Forward: 5′-TTGATGGGATATGAGCCAGA-3′; HIF1α Reverse, 5-TGTCCTGTGGTGACTTGTCC-3′; GAPDH Forward: 5′-TGTTGCCATCAATGACCCCTT-3′; and GAPDH Reverse: 5′-CTCCACGACGTACTCAGCG-3′.LDHA, GPR81, and HIF1α gene expression was conducted by quantitative PCR (qPCR) as previously described . Total RSamples were quantified at the log-linear portion of the curve using LightCycler analysis software and compared with an external calibration standard curve.For loss of function, LDHA, GPR81, and HIF1α were knocked down using shRNA . Scrambled shRNA served as control. Cells were transduced with LDHA, GPR81, or HIF1α shRNA or scrambled shRNA with 5 ng/mL of Polybrene (MilliporeSigma).g for 15 minutes at 4°C, and the lysates were precleared for 1 hour at 4°C with protein A/G beads and immunoprecipitated for 2 hours at 4°C with the appropriate primary antibody.Western blots were performed as previously described . For imm× 106 cells (with the treatment indicated or vehicle control) were used for chromatin fragment preparation. The experiment was conducted following the manufacturer’s instruction. ChIP-PCR was performed using GPR81 forward primer 5′-CAAGGCAGTCAGGCAAAG-3′ and GPR81 reverse primer 5′-CTTGTTTGTCCTCCCTCCT-3′.ChIP Assay kit  was used. In total, 6 IHC was performed on 4 μm paraffin-embedded serial sectioned IPF lung tissue and mounted on polylysine-coated slides. The sections were deparaffinized in xylene, rehydrated through a graded Methanol series, quenched with 0.3% hydrogen peroxide in methanol, and immersed in a 98°C water bath for 30 minutes in citrate buffer (pH 6.0) for antigen retrieval. Sections were placed in 5% normal horse serum (Jackson ImmunoResearch) to block nonspecific binding of secondary antibodies. A multiplex IHC kit was used for antigen detection according to the manufacturer’s instructions . The tissue specimens were incubated overnight  with the following primary antibodies: anti–rabbit GPR81 monoclonal antibody (1:800) , anti–human CAIX antibody (1:500) , and anti–human SSEA4 antibody (1:100) . Specimens were cover-slipped with a Prolong Antifade Kit (Invitrogen/Molecular Probes) and stored overnight at room temperature without light before image analysis.To assess IPF MPC fibrogenicity in vivo, we utilized 2 assays. Antibodies are listed in Cells stained with a vital dye  were grafted into the central portion of the zebrafish embryo blastoderm at the oblong-sphere stages as previously described. Embryos were immobilized with Tricane after 48 hours. Fluorescence and corresponding bright-field imaging of the PKH26-stained grafts in live embryos were performed with a Zeiss Axiovert upright microscope (Carl Zeiss). After image acquisition, embryos were fixed with 4% paraformaldehyde, infiltrated with increasing concentrations of sucrose/PBS, and cryoembedded in OCT. The size of the fibrotic reticulum was quantified as previously described .× 106 cells/100 μL) and injected via tail vein. Following cell administration, the mice were maintained under normoxic (21% O2) or hypoxic conditions  for the duration of the experiment. Mice were euthanized 4 weeks after adoptive transfer of human cells, and the lungs were harvested. Collagen content was quantified in the left lung tissue by Sircol assay and served as the primary endpoint. Histological (H&E and trichrome staining) and IHC analysis was performed on paraffin-embedded and frozen right lung tissue. The presence of lung fibrotic lesions by histological analysis served as the secondary endpoint. Cells positive for human procollagen  were identified as human. IHC using the human procollagen antibody and GPR81 antibody was performed to assess the distribution of GPR81-expressing cells with human procollagen I expressing cells. The antibody used does not cross-react with mouse collagen.NSG male and female mice (The Jackson Laboratory), average 10 weeks of age, were administered low-dose intratracheal bleomycin (1.25 U/kg) . Two wee× 106 IPF MPCs was used as reference control in qPCR.Mice were euthanized 4 weeks after adoptive transfer of human cells, and the lungs were harvested. The lungs were digested, and genomic DNA was isolated using a PureLink Genomic DNA Mini Kit according to the manufacturer’s instructions (Invitrogen). Real-time PCR was used to quantify human IPF cells in the mouse lungs by measuring the amount of human-specific DNA sequence using human specific primers per a previously published protocol . PCR asst test and 1-way ANOVA, as indicated. P < 0.05 was considered significant.Comparisons of data among experiments were performed using the 2-tailed Student’s Deidentified patient samples were obtained by our tissue procurement service (Bionet) under a waiver of informed consent from the University of Minnesota IRB (no. 1504M68341). Fresh IPF lungs were obtained at the time of lung transplantation, and control lung tissue was obtained by VATS biopsy or lobectomy. Animal protocols were approved and conducted in accordance with the University of Minnesota IACUC regulations .LY conceived, designed, and directed the studies with input from PBB and CAH. LY and CAH wrote the manuscript with assistance from all the authors. LY established primary human mesenchymal cell lines, cultured MPCs, performed flow cytometry for isolation of MPCs, performed qPCR, completed Western blot analyses, and performed gain- and loss-of-function experiments, mouse studies, and IHC. AG and HX assisted with isolation and culture of MPCs and assisted with mouse studies. ER provided slides for IHC. HX and JH also assisted with IHC analyses. KS designed and constructed expression constructs, and AB performed zebrafish xenotransplantation of MPCs.