Elaboration and characterization of nanoplate structured alpha-Fe2O3 films by Ag3PO4

A new strategy for surface treatment of hematite nanoplates for efficient photoelectrochemical (PEC) performances is proposed. Silver orthophosphate (Ag₃PO₄) has been adopted to mediate the formation of α-Fe₂O₃ films. Phosphate ions in Ag₃PO₄ is found to cause a significant morphology change during annealing process, from β-FeOOH nanorod arrays to hematite nanoplates. Meanwhile, Ag ions is doped into α-Fe₂O₃ film. The obtained nanoplate structured Fe₂O₃ –Ag–P films demonstrate much higher photoelectrochemical performance as photoanodes than the bare Fe₂O₃ nanorod thin films. The effects of phosphate and silver ions on the morphology, surface characteristics and the PEC properties of the photoanodes are investigated

In situ growth of ultrathin Co-MOF nanosheets on Α-Fe2O3 hematite nanorods for efficient photoelectrochemical water oxidation

Efficient charge transport is an important factor in photoelectrochemical (PEC) water splitting. The charge transfer at the semiconductor/electrolyte interface is of great importance, especially for the complex water oxidation reaction. In this study, we explored the feasibility of improving charge transfer efficiency at the interface of semiconductor/electrolyte by in situ growth of Co based Metal-Organic Frame work (Co-MOF) through a facile ion-exchanging method. Under optimized conditions, the Co-MOF nanosheet-modified hematite gave a photocurrent density of 2.0 mA cm−2 (200% improvement) at 1.23 VRHE with a cathodic shift of 180 mV in the photocurrent onset potential, in comparison to bare α-Fe2O3 (0.71 mA cm−[email protected] VRHE). To elucidate the role of Co-MOF, X-ray photoelectron spectroscopy, electrochemical impedance spectroscopy and Mott-Schottky measurements were carried out. It was found that the atomically distributed Co2+ in Co-MOF possessed excellent hole storage capability and charge transfer efficiency, as evidenced by the high surface capacitance and extremely low surface charge transfer resistance

Anomalous stopping of laser-accelerated intense proton beam in dense ionized matter

Ultrahigh-intensity lasers (10$^{18}$-10$^{22}$W/cm$^{2}$) have opened up new perspectives in many fields of research and application [1-5]. By irradiating a thin foil, an ultrahigh accelerating field (10$^{12}$ V/m) can be formed and multi-MeV ions with unprecedentedly high intensity (10$^{10}$A/cm$^2$) in short time scale ($\sim$ps) are produced [6-14]. Such beams provide new options in radiography [15], high-yield neutron sources [16], high-energy-density-matter generation [17], and ion fast ignition [18,19]. An accurate understanding of the nonlinear behavior of beam transport in matter is crucial for all these applications. We report here the first experimental evidence of anomalous stopping of a laser-generated high-current proton beam in well-characterized dense ionized matter. The observed stopping power is one order of magnitude higher than single-particle slowing-down theory predictions. We attribute this phenomenon to collective effects where the intense beam drives an decelerating electric field approaching 1GV/m in the dense ionized matter. This finding will have considerable impact on the future path to inertial fusion energy.Comment: 8 pages, 4 figure

Target density effects on charge tansfer of laser-accelerated carbon ions in dense plasma

We report on charge state measurements of laser-accelerated carbon ions in the energy range of several MeV penetrating a dense partially ionized plasma. The plasma was generated by irradiation of a foam target with laser-induced hohlraum radiation in the soft X-ray regime. We used the tri-cellulose acetate (C$_{9}$H$_{16}$O$_{8}$) foam of 2 mg/cm$^{-3}$ density, and $1$-mm interaction length as target material. This kind of plasma is advantageous for high-precision measurements, due to good uniformity and long lifetime compared to the ion pulse length and the interaction duration. The plasma parameters were diagnosed to be T$_{e}$=17 eV and n$_{e}$=4 $\times$ 10$^{20}$ cm$^{-3}$. The average charge states passing through the plasma were observed to be higher than those predicted by the commonly-used semiempirical formula. Through solving the rate equations, we attribute the enhancement to the target density effects which will increase the ionization rates on one hand and reduce the electron capture rates on the other hand. In previsous measurement with partially ionized plasma from gas discharge and z-pinch to laser direct irradiation, no target density effects were ever demonstrated. For the first time, we were able to experimentally prove that target density effects start to play a significant role in plasma near the critical density of Nd-Glass laser radiation. The finding is important for heavy ion beam driven high energy density physics and fast ignitions.Comment: 7 pages, 4 figures, 35 conference

Quantitative Inversion of Lunar Surface Chemistry Based on Hyperspectral Feature Bands and Extremely Randomized Trees Algorithm

In situ resource utilization (ISRU) is required for the operation of both medium and long-term exploration missions to provide metallic materials for the construction of lunar base infrastructure and H2O and O2 for life support. The study of the distribution of the lunar surface elements (Fe, Ti, Al, and Si) is the basis for the in situ utilization of mineral resources. With the arrival of the era of big data, the application of big data concepts and technical methods to lunar surface chemistry inversion has become an inevitable trend. This paper is guided by big data theory, and the Apollo 17 region and the area near the Copernicus crater are selected for analysis. The dimensionality of the first-order differential spectral features of lunar soil samples is reduced based on Pearson correlation analysis and the successive projections algorithm (SPA), and the extremely randomized trees (Extra-Trees) algorithm is applied to Chang’E-1 Interference Imaging Spectrometer (IIM) data to establish a prediction model for the lunar surface chemistry and generate FeO, TiO2, Al2O3, and SiO2 distribution maps. The results show that the optimum number of variables for FeO, TiO2, Al2O3, and SiO2 is 17, 5, 8, and 30, respectively. The accuracy of the Extra-Trees model using the best variables was improved over that of the original band model, with determination coefficients (R2) of 0.962, 0.944, 0.964, and 0.860 for FeO, TiO2, Al2O3, and SiO2, and root mean square errors (RMSEs) of 1.028, 0.672, 0.942, and 0.897, respectively. The modeling feature variables and model preference methods in this study can improve the inversion accuracy of chemical abundance to some extent, demonstrating the potential of IIM data in predicting chemical abundance and providing a good data basis for lunar geological evolution studies and ISRU

Ultrathin hematite films deposited layer-by-layer on a TiO2 underlayer for efficient water splitting under visible light

Ultrathin hematite (α-Fe2O3) film deposited on a TiO2 underlayer as a photoanode for photoelectrochemical water splitting was described. The TiO2 underlayer was coated on conductive fluorine-doped tin oxide (FTO) glass by spin coating. The hematite films were formed layer-by-layer by repeating the separated two-phase hydrolysis-solvothermal reaction of iron(III) acetylacetonate and aqueous ammonia. A photocurrent density of 0.683 mA cm−2 at +1.5 V vs. RHE (reversible hydrogen electrode) was obtained under visible light (>420 nm, 100 mW cm−2) illumination. The TiO2 underlayer plays an important role in the formation of hematite film, acting as an intermediary to alleviate the dead layer effect and as a support of large surface areas to coat greater amounts of Fe2O3. The as-prepared photoanodes are notably stable and highly efficient for photoelectrochemical water splitting under visible light. This study provides a facile synthesis process for the controlled production of highly active ultrathin hematite film and a simple route for photocurrent enhancement using several photoanodes in tandem

Quantitative Inversion of Lunar Surface Chemistry Based on Hyperspectral Feature Bands and Extremely Randomized Trees Algorithm

In situ resource utilization (ISRU) is required for the operation of both medium and long-term exploration missions to provide metallic materials for the construction of lunar base infrastructure and H2O and O2 for life support. The study of the distribution of the lunar surface elements (Fe, Ti, Al, and Si) is the basis for the in situ utilization of mineral resources. With the arrival of the era of big data, the application of big data concepts and technical methods to lunar surface chemistry inversion has become an inevitable trend. This paper is guided by big data theory, and the Apollo 17 region and the area near the Copernicus crater are selected for analysis. The dimensionality of the first-order differential spectral features of lunar soil samples is reduced based on Pearson correlation analysis and the successive projections algorithm (SPA), and the extremely randomized trees (Extra-Trees) algorithm is applied to Chang’E-1 Interference Imaging Spectrometer (IIM) data to establish a prediction model for the lunar surface chemistry and generate FeO, TiO2, Al2O3, and SiO2 distribution maps. The results show that the optimum number of variables for FeO, TiO2, Al2O3, and SiO2 is 17, 5, 8, and 30, respectively. The accuracy of the Extra-Trees model using the best variables was improved over that of the original band model, with determination coefficients (R2) of 0.962, 0.944, 0.964, and 0.860 for FeO, TiO2, Al2O3, and SiO2, and root mean square errors (RMSEs) of 1.028, 0.672, 0.942, and 0.897, respectively. The modeling feature variables and model preference methods in this study can improve the inversion accuracy of chemical abundance to some extent, demonstrating the potential of IIM data in predicting chemical abundance and providing a good data basis for lunar geological evolution studies and ISRU