Improved Charge Separation and Photovoltaic Performance of BiI3 Absorber Layers by Use of an In Situ Formed BiSI Interlayer

Stable and nontoxic bismuth iodide (BiI3) is emerging as a promising absorber material for solar cell applications as it possesses favorable optical properties such as a narrow bandgap (1.7 eV) and a high absorption coefficient (105 cm–1) in the visible region. Despite these promising features, solar cells employing this material have only achieved power conversion efficiencies in the region of 1% as of yet, which is distant from the theoretical efficiency limit of 28%. It is reasonable to suppose that the relatively low performance of BiI3-based solar cells may originate from very short carrier lifetimes (180–240 ps) in BiI3, which makes efficient separation of mobile charges a crucial factor for the improvement of the photovoltaic performance of this material. Herein, transient optical spectroscopy is employed to show that the use of a bismuth sulfide iodide interlayer between the electron transport layer (ETL) and the bismuth iodide absorber promotes efficient charge separation. On the basis of this knowledge, we report BiI3 solar cells with a power conversion efficiency of 1.21% using a solar cell architecture comprised of ITO/SnO2/BiSI/BiI3/organic HTM/Au

Negative CT Contrast Agents for the Diagnosis of Malignant Osteosarcoma

© 2019 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim The current positive computed tomography (CT) contrast agents (PCTCAs) including clinical iodides, present high CT density value (CT-DV). However, they are incapable for the accurate diagnosis of some diseases with high CT-DV, such as osteosarcoma. Because bones and PCTCAs around osteosarcoma generate similar X-ray attenuations. Here, an innovative strategy of negative CT contrast agents (NCTCAs) to reduce the CT-DV of osteosarcoma is proposed, contributing to accurate detection of osteosarcoma. Hollow mesoporous silica nanoparticles, loading ammonia borane molecules and further modified by polyethylene glycol, are synthesized as NCTCAs for the diagnosis of osteosarcoma. The nanocomposites can produce H2 in situ at osteosarcoma areas by responding to the acidic microenvironment of osteosarcoma, resulting in nearly 20 times reduction of CT density in osteosarcoma. This helps form large CT density contrast between bones and osteosarcoma, and successfully achieves accurate diagnosis of osteosarcoma. Meanwhile, The NCTCAs strategy greatly expands the scope of CT application, and provides profound implications for the precise clinical diagnosis, treatment, and prognosis of diseases

Accurate and Real-Time Temperature Monitoring during MR Imaging Guided PTT.

Photothermal therapy (PTT) is an efficient approach for cancer treatment. However, accurately monitoring the spatial distribution of photothermal transducing agents (PTAs) and mapping the real-time temperature change in tumor and peritumoral normal tissue remain a huge challenge. Here, we propose an innovative strategy to integrate T1-MRI for precisely tracking PTAs with magnetic resonance temperature imaging (MRTI) for real-time monitoring temperature change in vivo during PTT. NaBiF4: Gd@PDA@PEG nanomaterials were synthesized with favorable T1-weighted performance to target tumor and localize PTAs. The extremely weak susceptibility (1.04 × 10-6 emu g-1 Oe1-) of NaBiF4: Gd@PDA@PEG interferes with the local phase marginally, which maintains the capability of MRTI to dynamically record real-time temperature change in tumor and peritumoral normal tissue. The time resolution is 19 s per frame, and the detection precision of temperature change is approximately 0.1 K. The approach achieving PTT guided by multimode MRI holds significant potential for the clinical application

Whistle detection and classification for whales based on convolutional neural networks

Passive acoustic observation of whales is an increasingly important tool for whale research. Accurately detecting whale sounds and correctly classifying them into corresponding whale species are essential tasks, especially in the case when two species of whales vocalize in the same observed area. Whistles are vital vocalizations of toothed whales, such as killer whales and long-finned pilot whales. In this paper, based on deep convolutional neural networks (CNNs), a novel method is proposed to detect and classify whistles of both killer whales and long-finned pilot whales. Compared with traditional methods, the proposed one can automatically learn the sound characteristics from the training data, without specifying the sound features for classification and detection, and thus shows better adaptability to complex sound signals. First, the denoised sound to be analyzed is sent to the trained detection model to estimate the number and positions of the target whistles. The detected whistles are then sent to the trained classification model, which determines the corresponding whale species. A GUI interface is developed to assist with the detection and classification process. Experimental results show that the proposed method can achieve 97% correct detection rate and 95% correct classification rate on the testing set. In the future, the presented method can be further applied to passive acoustic observation applications for some other whale or dolphin species

Very high upper critical fields in MgB2 produced by selective tuning of impurity scattering

We report a significant enhancement of the upper critical field $H_{c2}$ of different $MgB_2$ samples alloyed with nonmagnetic impurities. By studying films and bulk polycrystals with different resistivities $\rho$, we show a clear trend of $H_{c2}$ increase as $\rho$ increases. One particular high resistivity film had zero-temperature $H_{c2}(0)$ well above the $H_{c2}$ values of competing non-cuprate superconductors such as $Nb_3Sn$ and Nb-Ti. Our high-field transport measurements give record values $H_{c2}^\perp (0) \approx 34T$ and $H_{c2}\|(0) \approx 49 T$ for high resistivity films and $H_{c2}(0)\approx 29 T$ for untextured bulk polycrystals. The highest $H_{c2}$ film also exhibits a significant upward curvature of $H_{c2}(T)$, and temperature dependence of the anisotropy parameter $\gamma(T) = H_{c2}\|/ H_{c2}^\perp$ opposite to that of single crystals: $\gamma(T)$ decreases as the temperature decreases, from $\gamma(T_c) \approx 2$ to $\gamma(0) \approx 1.5$. This remarkable $H_{c2}$ enhancement and its anomalous temperature dependence are a consequence of the two-gap superconductivity in $MgB_2$, which offers special opportunities for further $H_{c2}$ increase by tuning of the impurity scattering by selective alloying on Mg and B sites. Our experimental results can be explained by a theory of two-gap superconductivity in the dirty limit. The very high values of $H_{c2}(T)$ observed suggest that $MgB_2$ can be made into a versatile, competitive high-field superconductor.Comment: An updated version of the paper (12/12/2002)that was placed on cond-mat on May 7 200

Well-posedness for degenerate third order equations with delay and applications to inverse problems

[EN] In this paper, we study well-posedness for the following third-order in time equation with delay <disp-formula idoperators defined on a Banach space X with domains D(A) and D(B) such that t)is the state function taking values in X and u(t): (-, 0] X defined as u(t)() = u(t+) for < 0 belongs to an appropriate phase space where F and G are bounded linear operators. Using operator-valued Fourier multiplier techniques we provide optimal conditions for well-posedness of equation (0.1) in periodic Lebesgue-Bochner spaces Lp(T,X), periodic Besov spaces Bp,qs(T,X) and periodic Triebel-Lizorkin spaces Fp,qs(T,X). A novel application to an inverse problem is given.The first, second and third authors have been supported by MEC, grant MTM2016-75963-P. The second author has been supported by AICO/2016/30. The fourth author has been supported by MEC, grant MTM2015-65825-P.Conejero, JA.; Lizama, C.; Murillo-Arcila, M.; Seoane Sepúlveda, JB. (2019). 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A study on text-score disagreement in online reviews

In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the same score (and vice-versa); and 2) detecting and analyzing the mismatches between the review content and the actual score may benefit both service providers and consumers, by highlighting specific factors of satisfaction (and dissatisfaction) in texts. To prove the intuitions, we adopt sentiment analysis techniques and we concentrate on hotel reviews, to find polarity mismatches therein. In particular, we first train a text classifier with a set of annotated hotel reviews, taken from the Booking website. Then, we analyze a large dataset, with around 160k hotel reviews collected from Tripadvisor, with the aim of detecting a polarity mismatch, indicating if the textual content of the review is in line, or not, with the associated score. Using well established artificial intelligence techniques and analyzing in depth the reviews featuring a mismatch between the text polarity and the score, we find that -on a scale of five stars- those reviews ranked with middle scores include a mixture of positive and negative aspects. The approach proposed here, beside acting as a polarity detector, provides an effective selection of reviews -on an initial very large dataset- that may allow both consumers and providers to focus directly on the review subset featuring a text/score disagreement, which conveniently convey to the user a summary of positive and negative features of the review target.Comment: This is the accepted version of the paper. The final version will be published in the Journal of Cognitive Computation, available at Springer via http://dx.doi.org/10.1007/s12559-017-9496-

Many Body Theory of Charge Transfer in Hyperthermal Atomic Scattering

We use the Newns-Anderson Hamiltonian to describe many-body electronic processes that occur when hyperthermal alkali atoms scatter off metallic surfaces. Following Brako and Newns, we expand the electronic many-body wavefunction in the number of particle-hole pairs (we keep terms up to and including a single particle-hole pair). We extend their earlier work by including level crossings, excited neutrals and negative ions. The full set of equations of motion are integrated numerically, without further approximations, to obtain the many-body amplitudes as a function of time. The velocity and work-function dependence of final state quantities such as the distribution of ion charges and excited atomic occupancies are compared with experiment. In particular, experiments that scatter alkali ions off clean Cu(001) surfaces in the energy range 5 to 1600 eV constrain the theory quantitatively. The neutralization probability of Na$^+$ ions shows a minimum at intermediate velocity in agreement with the theory. This behavior contrasts with that of K$^+$, which shows ... (7 figures, not included. Figure requests: [email protected])Comment: 43 pages, plain TeX, BUP-JBM-