Insight into modified CeMn based catalysts for efficient degradation of toluene by in situ infrared.

Trace activated carbon (AC) and diatomaceous earth (DE) were used as structural promoters to be incorporated into Ce-Mn-based solid-solution catalysts by the redox precipitation method. The modified catalysts exhibit superior reducibility, with abundant Ce3+, Mn3+and reactive oxygen species, which are facilitated to the migration of oxygen and the generation of oxygen vacancies. In particular, the catalytic combustion temperatures of 90 % toluene (3000 ppm) on Ce1Mn3Ox-AC/DE were 84 °C (dry) and 123 °C (10 vol% H2O), respectively. The role of lattice oxygen and adsorbed oxygen was revealed by in situ DRIFTS. Additionally, in situ DRIFTS was employed to verify that the degradation of toluene by Ce1Mn3Ox-AC/DE satisfied the Langmuir-Hinshelwood (L-H) mechanism and the Mars-Van Krevelen (MvK) mechanism. The possible reaction pathway was elucidated (toluene → benzyl alcohol → benzoic acid → maleic anhydride → CO2 + H2O). Furthermore, final products attributed to toluene oxidation were detected by in situ DRIFTS at 50 °C in the absence of oxygen, confirming that the catalyst possessed outstanding performance at low temperatures beyond mere adsorption.

Preparation of highly dispersed SnO/TiO2 catalysts and their performances in catalyzing polyol ester.

A series of stannous oxide supported on rutile titanium dioxide (SnO/TiO2) were prepared by a conventional incipient wetness impregnation method, and their performance as catalysts for fatty acid esterification reactions was investigated. The effects of Sn precursors (SnCl2·2H2O or SnC2O4), loading amounts (5-15%), and treating ambiences (air and N2) were explored. The optimized 10% SnO/TiO2-Cl with SnCl2·2H2O as the Sn precursor and thermal treatment in N2 showed the best esterification performance. Specifically, 10% SnO/TiO2-Cl catalyzed the esterification process of trimethylolpropane and n-octanoic acid with a conversion of 99.6% over 5 h at 160 °C, and 10% SnO/TiO2-Cl was efficient for six catalytic cycles. Based on the results of X-ray diffraction (XRD), Raman spectra, high-resolution transmission electron microscopy (HRTEM), infrared spectra of pyridine adsorption (Py-IR), and ammonia temperature programmed desorption (NH3-TPD), the improved catalytic performance is supposed to be attributable to the high dispersion of the Sn species on 10% SnO/TiO2-Cl as the moderate Lewis acid sites.

Regional-Lag Signed Delay Multiply and Sum Beamforming in Ultrafast Ultrasound Imaging.

Ultrafast ultrasound imaging provides very high frame rates but provides poor imaging quality due to unfocused beams. The delay multiply and sum (DMAS) beamformer has been used to improve ultrafast ultrasound imaging contrast but is always accompanied by oversuppression, which produces low-quality speckle images and degrades the contrast performance. A smaller maximum lag in the signed DMAS (sDMAS) contributes better speckle preservation but lower resolution for hyperechoic scatters. To overcome this tradeoff, a regional-lag signed delay multiply and sum (rsDMAS) beamformer is proposed in this article. Innovatively, a region discrimination tool realized by the generalized coherence factor (GCF) is used to limit the maximum lag for spatial coherence estimation. Subaperture coherence smoothing estimates the short-lag coherence instead of multiplication in pairs, thereby reducing calculation complexity and smoothing the speckle texture. Normalization and sign correction are also introduced to achieve better beamforming output. The simulated, phantom, and in vivo data are adopted to evaluate the effectiveness of the proposed beamformer. Numerical results show that the proposed method achieves improvements of the contrast ratio (CR) by 9%, contrast-to-noise ratio (CNR) by 41%, speckle signal-to-noise ratio (sSNR) by 41%, and generalized contrast-to-noise ratio (gCNR) by 0.0004 compared with DMAS (in simulation). Resolution experiments show that the proposed method obtains a loss of 0.07 mm in the full width at half maximum (FWHM) and the same separability of close point scatters as DMAS. These findings indicate that the proposed method achieves higher contrast performance at less obvious sacrifice of the lateral resolution than DMAS.

United Wiener postfilter for plane wave compounding ultrasound imaging.

Plane wave compounding (PWC) is a valid method for ultrafast ultrasound imaging. Its imaging quality depends on the beamforming method. The coherence factor (CF) and Wiener postfilter are effective signal processing schemes for aberration correction. However, the CF usually causes over-suppression and brings artifacts. Additionally, the conventional CF and Wiener postfilter cannot fully utilize the spatial coherence in the PWC, which limits the imaging performance and increases the computation. In this paper, we propose a united Wiener postfilter specially for the PWC. The signal and noise power are both estimated through the echo signal matrix, rather than array signal vectors. The method also accords with the theoretical relationship between the CF and Wiener. To evaluate the performance of the proposed method, we conduct simulations, phantom and in vivo experiments and make comparisons with the delay-and-sum (DAS), the CF, the generalized coherence factor (GCF), the conventional Wiener and the scaled Wiener beamformers. Results indicate that our method can offer the better resolution and contrast than the DAS and Wiener. It also solves the over-suppression drawback of the CF. Specifically, the contrast ratio and contrast-to-noise ratio achieve 26.7% and 25.2% improvements in simulations, 28.7% and 32.4% in phantom experiments, respectively. The proposed method also performs well in terms of the speckle signal-to-noise ratio and the generalized contrast-to-noise ratio. Consequently, we believe that the proposed method is effective in enhancing the imaging quality of the PWC.

High Resolution, High Contrast Beamformer Using Minimum Variance and Plane Wave Nonlinear Compounding with Low Complexity.

The plane wave compounding (PWC) is a promising modality to improve the imaging quality and maintain the high frame rate for ultrafast ultrasound imaging. In this paper, a novel beamforming method is proposed to achieve higher resolution and contrast with low complexity. A minimum variance (MV) weight calculated by the partial generalized sidelobe canceler is adopted to beamform the receiving array signals. The dimension reduction technique is introduced to project the data into lower dimensional space, which also contributes to a large subarray length. Estimation of multi-wave receiving covariance matrix is performed and then utilized to determine only one weight. Afterwards, a fast second-order reformulation of the delay multiply and sum (DMAS) is developed as nonlinear compounding to composite the beamforming output of multiple transmissions. Simulations, phantom, in vivo, and robustness experiments were carried out to evaluate the performance of the proposed method. Compared with the delay and sum (DAS) beamformer, the proposed method achieved 86.3% narrower main lobe width and 112% higher contrast ratio in simulations. The robustness to the channel noise of the proposed method is effectively enhanced at the same time. Furthermore, it maintains a linear computational complexity, which means that it has the potential to be implemented for real-time response.

A Low-complexity Minimum-variance Beamformer Based on Orthogonal Decomposition of the Compounded Subspace.

Minimum-variance (MV) beamforming, as a typical adaptive beamforming method, has been widely studied in medical ultrasound imaging. This method achieves higher spatial resolution than traditional delay-and-sum (DAS) beamforming by minimizing the total output power while maintaining the desired signals. However, it suffers from high computational complexity due to the heavy calculation load when determining the inverse of the high-dimensional matrix. Low-complexity MV algorithms have been studied recently. In this study, we propose a novel MV beamformer based on orthogonal decomposition of the compounded subspace (CS) of the covariance matrix in synthetic aperture (SA) imaging, which aims to reduce the dimensions of the covariance matrix and therefore reduce the computational complexity. Multiwave spatial smoothing is applied to the echo signals for the accurate estimation of the covariance matrix, and adaptive weight vectors are calculated from the low-dimensional subspace of the original covariance matrix. We conducted simulation, experimental and in vivo studies to verify the performance of the proposed method. The results indicate that the proposed method performs well in maintaining the advantage of high spatial resolution and effectively reduces the computational complexity compared with the standard MV beamformer. In addition, the proposed method shows good robustness against sound velocity errors.

Image Quality Enhancement Using a Deep Neural Network for Plane Wave Medical Ultrasound Imaging.

Plane wave imaging (PWI), a typical ultrafast medical ultrasound imaging mode, adopts single plane wave emission without focusing to achieve a high frame rate. However, the imaging quality is severely degraded in comparison with the commonly used focused line scan mode. Conventional adaptive beamformers can improve imaging quality at the cost of additional computation. In this article, we propose to use a deep neural network (DNN) to enhance the performance of PWI while maintaining a high frame rate. In particular, the PWI response from a single point target is used as the network input, while the focused scan response from the same point serves as the desired output, which is the main contribution of this method. To evaluate the performance of the proposed method, simulations, phantom experiments and in vivo studies are conducted. The delay-and-sum (DAS), the coherence factor (CF), a previously proposed deep learning-based method and the DAS with focused scan are used for comparison. Numerical metrics, including the contrast ratio (CR), the contrast-to-noise ratio (CNR), and the speckle signal-to-noise ratio (sSNR), are used to quantify the performance. The results indicate that the proposed method can achieve superior resolution and contrast performance. Specifically, the proposed method performs better than the DAS in all metrics. Although the CF provides a higher CR, its CNR and sSNR are much lower than those of the proposed method. The overall performance is also better than that of the previous deep learning method and at the same level with focused scan performance. Additionally, in comparison with the DAS, the proposed method requires little additional computation, which ensures high temporal resolution. These results validate that the proposed method can achieve a high imaging quality while maintaining the high frame rate associated with PWI.

A Mixed Transmitting-Receiving Beamformer With a Robust Generalized Coherence Factor: Enhanced Resolution and Contrast.

Adaptive beamforming has been widely studied for ultrasound imaging over the past few decades. The minimum variance (MV) and generalized coherence factor (GCF) approaches have been validated as effective methods. However, the MV method had a limited contribution to contrast improvement, while the GCF method suffered from severe speckle distortion in previous studies. In this article, a novel ultrasound beamforming approach based on MV and GCF beamformers is proposed to enhance the spatial resolution and contrast in synthetic aperture (SA) ultrasound imaging. First, the MV optimization problem is conceptually redefined by minimizing the total power of the transmitting and receiving outputs. Estimation of the covariance matrices in transmit and receive apertures is carried out and then utilized to determine adaptive weighting vectors. Second, a data-compounding method, viewed as a spatial low-pass filter, is introduced to the GCF method to optimize the spatial spectrum of echo signals and obtain better performance. Robust principal component analysis (RPCA) processing is additionally employed to obtain the final output. Simulation, experimental, and in vivo studies are conducted on different data sets. Relative to the traditional delay-and-sum (DAS) beamformer, mean improvements in the full-width at half-maximum and contrast ratio of 89% and 94%, respectively, are achieved. Thus, considerable enhancement of the spatial resolution and contrast is obtained by the proposed method. Moreover, the proposed method performs better in terms of the computational complexity. In summary, the proposed scheme effectively enhances ultrasound imaging quality.

Image Quality Improvement of Hand-Held Ultrasound Devices With a Two-Stage Generative Adversarial Network.

As a widely used imaging modality in the medical field, ultrasound has been applied in community medicine, rural medicine, and even telemedicine in recent years. Therefore, the development of portable ultrasound devices has become a popular research topic. However, the limited size of portable ultrasound devices usually degrades the imaging quality, which reduces the diagnostic reliability. To overcome hardware limitations and improve the image quality of portable ultrasound devices, we propose a novel generative adversarial network (GAN) model to achieve mapping between low-quality ultrasound images and corresponding high-quality images. In contrast to the traditional GAN method, our two-stage GAN that cascades a U-Net network prior to the generator as a front end is built to reconstruct the tissue structure, details, and speckle of the reconstructed image. In the training process, an ultrasound plane-wave imaging (PWI) data-based transfer learning method is introduced to facilitate convergence and to eliminate the influence of deformation caused by respiratory activities during data pair acquisition. A gradual tuning strategy is adopted to obtain better results by the PWI transfer learning process. In addition, a comprehensive loss function is presented to combine texture, structure, and perceptual features. Experiments are conducted using simulated, phantom, and clinical data. Our proposed method is compared to four other algorithms, including traditional gray-level-based methods and learning-based methods. The results confirm that the proposed approach obtains the optimum solution for improving quality and offering useful diagnostic information for portable ultrasound images. This technology is of great significance for providing universal medical care.

Ultrafast Plane Wave Imaging With Line-Scan-Quality Using an Ultrasound-Transfer Generative Adversarial Network.

In the medical ultrasound field, ultrafast imaging has recently become a hot topic. However, the diagnostic reliability of ultrafast high-frame rate plane-wave (PW) imaging is reduced by its low-quality images. The medical ultrasound equipment on the market usually adopts the line-scanning mode, which can obtain high-quality images at a very low frame rate. In addition, many proven data-driven ultrasound image processing methods are trained by line-scan images. Since the gray-level distributions of line-scan images and PW images are very different, these gray-level distribution-sensitive methods cannot be generalized to ultrafast ultrasound imaging, which limits further applications. Hence, we propose an ultrasound-transfer generative adversarial network to improve the quality of PW images and extend the existing image processing methods to ultrafast ultrasound imaging by reconstructing PW images into line-scan images. This network adopts a residual dense generator with a self-attention system that fully uses the hierarchical features and generates details from all the relevant physiological information. A projection discriminator and spectral normalization are introduced to increase the discernibility and to maintain a balance between the generator and the discriminator. Moreover, we reorganize the transmit sequence of the transducer array to eliminate the negative influence of human movements and facilitate the convergence of the proposed model. The experimental results are evaluated with five metrics, which confirm the feasibility of the proposed method to obtain a line-scan-quality image with a very high frame rate. This technology could significantly popularize ultrafast medical ultrasound imaging.

Short-lag spatial coherence imaging using minimum variance beamforming on dual apertures.

BACKGROUND: Short-lag spatial coherence (SLSC) imaging, a newly proposed ultrasound imaging scheme, can offer a higher lesion detectability than conventional B-mode imaging. It requires a high focusing quality which can be satisfied by the synthetic aperture imaging mode. However, traditional nonadaptive synthesis for the SLSC still offers an unsatisfactory resolution. The spatial coherence estimation on the receive aperture cannot fully utilize the coherence information in two-dimensional (2D) echo data. METHODS: To overcome these drawbacks, an improved SLSC scheme with adaptive synthesis on dual apertures is proposed in this paper. The minimum variance (MV) beamformer is applied in synthesizing both the receiving and transmitting apertures, while the SLSC function is estimated on both apertures as well. In this way, the resolution is enhanced by the MV implementation, while the coherence in dual apertures is fully utilized. RESULTS: Simulations, phantom experiments, and in vivo studies are conducted to evaluate the performance of the proposed method. Results demonstrate that the proposed method achieves the best performance in terms of the contrast ratio (CR), contrast-to-noise ratio (CNR), and the speckle signal-to-noise ratio (SNR). Specifically, compared with the delay-and-sum (DAS) method, the proposed method achieves 42.5% higher CR, 412.7% higher CNR, and 402.9% higher speckle SNR in simulations. The resolution is also better than the DAS and conventional SLSC beamformers. CONCLUSIONS: The proposed method is a promising technique for improving the SLSC imaging quality and can provide better visualization for medical diagnosis.

2-D Minimum Variance Based Plane Wave Compounding with Generalized Coherence Factor in Ultrafast Ultrasound Imaging.

Plane wave compounding (PWC) is an effective modality for ultrafast ultrasound imaging. It can provide higher resolution and better noise reduction than plane wave imaging (PWI). In this paper, a novel beamformer integrating the two-dimensional (2-D) minimum variance (MV) with the generalized coherence factor (GCF) is proposed to maintain the high resolution and contrast along with a high frame rate for PWC. To specify, MV beamforming is adopted in both the transmitting aperture and the receiving one. The subarray technique is therefore upgraded into the sub-matrix division. Then, the output of each submatrix is used to adaptively compute the GCF using a 2-D fast Fourier transform (FFT). After the 2-D MV beamforming and the 2-D GCF weighting, the final output can be obtained. Results of simulations, phantom experiments, and in vivo studies confirm the advantages of the proposed method. Compared with the delay-and-sum (DAS) beamformer, the full width at half maximum (FWHM) is 90% smaller and the contrast ratio (CR) improvement is 154% in simulations. The over-suppression of desired signals, which is a typical drawback of the coherence factor (CF), can be effectively avoided. The robustness against sound velocity errors is also enhanced.

High Spatial-Temporal Resolution Reconstruction of Plane-Wave Ultrasound Images With a Multichannel Multiscale Convolutional Neural Network.

In recent years, plane-wave imaging (PWI) has attracted considerable attention because of its high temporal resolution. However, the low spatial resolution of PWI limits its clinical applications, which has inspired various studies on the high spatial resolution reconstruction of PW ultrasound images. Although compounding methods and traditional high spatial resolution reconstruction approaches can improve the image quality, these techniques decrease the temporal resolution. Since learning methods can fully reserve the high temporal resolution of PW ultrasounds, a novel convolutional neural network (CNN) model for the high spatial-temporal resolution reconstruction of PW ultrasound images is proposed in this paper. Considering the multiangle form of PW data, a multichannel model is introduced to produce balanced training. To combine local and contextual information, the multiscale model is adopted. These two innovations constitute our multichannel and multiscale CNN (MMCNN) model. Compared with traditional CNN methods, the proposed model uses a two-stage structure in which a cascading wavelet postprocessing stage is combined with the trained MMCNN model. Cascading wavelet postprocessing aims to preserve speckle information. Furthermore, a feedback system is appended to the iteration process of the network training to solve the overfitting problem and help produce convergence. Based on these improvements, an end-to-end mapping is established between a single-angle B-mode PW image and its corresponding multiangle compounded, high-resolution image. The experiments were conducted on simulated, phantom, and real human data. The advantages of our proposed method were compared with a coherent PW compounding method, a conventional maximum a posteriori-based high spatial resolution reconstruction method, and a 2-D CNN compounding method, and the results verified that our approach is capable of attaining a better temporal resolution and comparable spatial resolution. In clinical usage, the proposed method is equipped to satisfy with many ultrafast imaging applications, which require high spatial-temporal resolution. i.

Joint Subarray Coherence and Minimum Variance Beamformer for Multitransmission Ultrasound Imaging Modalities.

Multitransmission modalities, such as plane wave compounding and synthetic aperture imaging, are promising techniques for ultrafast ultrasound imaging. Adaptive beamformers have been proposed to improve the imaging quality. Two common categories of adaptive beamformers are the minimum variance (MV)-based beamformers and the coherence factor (CF)-based beamformers. The MV can significantly improve the resolution while lacking robustness. It is also computationally expensive for multitransmission modalities. The CF can increase the contrast while over-suppressing some desired signals. In this paper, we propose a novel beamformer for better imaging quality in multitransmission ultrasound modalities. Specifically, the MV weighting process is applied to the receiving and transmitting beamforming. The spatial smoothing technique is modified for both dimensions to enhance the robustness. Then, the CF-based weights are calculated using the MV beamformed output. The submatrix technique is also used in the CF process to avoid over-suppression. Simulations and experiments are conducted to evaluate the performance of the proposed method. The results show that it can preserve the high resolution of MV and the high contrast of CF. Compared with the traditional compounding method, the full-width at half-maximum is smaller and the contrast ratio is significantly increased. Anatomic structures of an in vivo human carotid artery are more distinguishable. Because of the spatial smoothing in both dimensions, the proposed beamformer also has high robustness against the channel noise and sound velocity errors.

Magnetic chitosan-based adsorbent prepared via Pickering high internal phase emulsion for high-efficient removal of antibiotics.

A novel magnetic chitosan-g-poly(2-acrylamide-2-methylpropanesulfonic acid) (CTS-g-AMPS) porous adsorbent was prepared by grafting the AMPS onto the CTS in the Fe3O4 stabilized Pickering high internal phase emulsions (Pickering-HIPEs) and used for the adsorptive removal of the antibiotics tetracycline (TC) and chlorotetracycline (CTC). The results of the structure characterization showed that porous structure of the adsorbent can be tuned easily by altering amount of Fe3O4-MNPs-M and the electrostatic attraction of between SO3- and CTC, TC was the main adsorption driving force. The adsorption capacities of the adsorbent for TC and CTC can be reached to 806.60 and 876.60mg/g in a wide pH ranged from 3.0 to 11.0, respectively. And the adsorption equilibrium can be reached within 90min for TC and 50min for CTC. The magnetic porous adsorbent had good reusability, which can still attain a high adsorption capacity of 759.82 and 842.99mg/g for TC and CTC after five consecutive adsorption cycles, respectively. Therefore, the as-prepared CTS-g-AMPS magnetic adsorbent is potential to be used for adsorption removal of antibiotics from water.

Efficient Charge Separation between Bi and Bi2 MoO6 for Photoelectrochemical Properties.

Herein, porous Bi/Bi2 MoO6 nanoparticles have been prepared by a facile in-situ reduction approach. Moreover, the morphology and Bi content of product could be controlled by varying the reaction time. By controlled fabrication, the desired porous Bi2 MoO6 nanostructure with incorporation of Bi was obtained and exhibited high photoelectric and photocatalytic activity. In particular, the samples yield a photocurrent density of 320 µA cm(-2) , which is 3.2 times that of the pure Bi2 MoO6 nanosheet (100 µA cm(-2) ) under the same conditions. UV/Vis diffuse reflectance spectroscopy analysis confirmed the surface plasmon resonance in the as-prepared porous nanoparticles. The improved photoelectric properties could be the synergistic effect of the porous structure with large surface area and effective electron-hole separations between Bi and Bi2 MoO6 .

Bi2MoO6/BiVO4 heterojunction electrode with enhanced photoelectrochemical properties.

Herein, we demonstrate the synthesis of a Bi2MoO6 nanorod array followed by the deposition of a BiVO4 absorber layer. This heterojunction yielded a photocurrent density of 250 µA cm(-2) at 0.8 VSCE, which is 21 times that produced by a planar Bi2MoO6 array under the same conditions. Moreover, in situ X-ray photoelectron spectroscopy clearly confirmed the improvement of the electron transport and charge separation afforded by the heterostructure, features that efficiently enhanced the photoelectrochemical properties of the array.

Hierarchical Bi2MoO6 nanosheet-built frameworks with excellent photocatalytic properties.

Herein, we demonstrate for the first time the fabrication of one-dimensional (1D) Bi2MoO6 inter-crossed nanosheet-built frameworks by using MoO3 nanobelts as the growth templates and molybdate source. Especially, this novel Bi2MoO6 framework structure exhibits remarkably enhanced photocatalytic activity toward the degradation of organic dyes under visible-light irradiation, far exceeding that of conventional Bi2MoO6 nanoplates and nanoparticles. The photoelectrochemical study suggests that the hierarchical framework structure could facilitate the photoinduced charge separation and transfer from the inter-crossed Bi2MoO6 nanosheets, which may make a significant contribution to the enhanced photocatalytic activity.

Investigation of a Branchlike MoO(3)/polypyrrole hybrid with enhanced electrochemical performance used as an electrode in supercapacitors.

A branchlike MoO3/polypyrrole conductive nanocomposite was facilely prepared by wrapping a homogeneous polypyrrole (PPy) layer around MoO3 nanobelts via the in situ oxidative polymerization of a self-assembled pyrrole monomer. X-ray powder diffraction characterization demonstrated that the PPy polymer does not hinder the crystallization of the MoO3 nanobelts substrate. The electrochemical tests show that the specific capacitance of 129 F g(-1) for the MoO3/PPy hybrid is higher than both pristine MoO3 and pure PPy. Moreover, the hybrid electrode with good electrical conductivity displays good cyclic stability of 90% retention after 200 cycles of charge/discharge. These results indicate a promising potential application of the MoO3/PPy nanocomposite for use as an effective electrode material in supercapacitors.

Selective adsorption of silver ions from aqueous solution using polystyrene-supported trimercaptotriazine resin.

Trimercaptotriazine-functionalized polystyrene chelating resin was prepared and employed for the adsorption of Ag(I) from aqueous solution. The adsorbent was characterized according to the following techniques: Fourier transform infrared spectroscopy, elemental analysis, scanning electron microscopy and the Brunauer-Emmet-Teller method. The effects of initial Ag(I) concentration, contact time, solution pH and coexisting ions on the adsorption capacity of Ag(I) were systematically investigated. The maximum adsorption capacity of Ag(I) was up to 187.1 mg/g resin at pH 0.0 and room temperature. The kinetic experiments indicated that the adsorption rate of Ag(I) onto the chelating resin was quite fast in the first 60 min and reached adsorption equilibrium after 360 min. The adsorption process can be well described by the pseudo second-order kinetic model and the equilibrium adsorption isotherm was closely fitted by the Langmuir model. Moreover, the chelating resin could selectively adsorb more Ag(I) ions than other heavy metal ions including: Cu(I), Zn(II), Ni(II), Pb(II) and Cr(III) during competitive adsorption in the binary metal species systems, which indicated that it was a highly selective adsorbent of Ag(I) from aqueous solution.