Efficient and Stable Mesoscopic Perovskite Solar Cells Using PDTITT as a New Hole Transporting Layer

Stability is the main challenge in the field of organic–inorganic perovskite solar cells (PSCs). Finding low‐cost and stable hole transporting layer (HTL) is an effective strategy to address this issue. Here, a new donor polymer, poly(5,5‐didecyl‐5H‐1,8‐dithia‐as‐indacenone‐alt‐thieno[3,2‐b]thiophene) (PDTITT), is synthesized and employed as an HTL in PSCs, which has a suitable band alignment with respect to the double‐A cation perovskite film. Using PDTITT, the hole extraction in PSCs is greatly improved as compared to commonly used HTLs such as 2,2′,7,7′‐tetrakis[N,N‐di(4‐methoxyphenyl)amino]‐9,9′‐spirobifluorene (spiro‐OMeTAD), addressing the hysteresis issue. After careful optimization, an efficient PSC is achieved based on mesoscopic TiO₂ electron transporting layer with a maximum power conversion efficiency (PCE) of 18.42% based on PDTITT HTL, which is comparable with spiro‐OMeTAD‐based PSC (19.21%). Since spiro‐based PSCs suffer from stability issue, the operational stability in the PSC with PDTITT HTL is studied. It is found that the device with PDTITT retains 88% of its initial PCE value after 200 h under illumination, which is better than the spiro‐based PSC (54%).     

SLAM for autonomous planetary rovers with global localization

This paper describes a novel approach to simultaneous localization and mapping (SLAM) techniques applied to the autonomous planetary rover exploration scenario to reduce both the relative and absolute localization errors, using two well‐proven techniques: particle filters and scan matching. Continuous relative localization is improved by matching high‐resolution sensor scans to the online created local map. Additionally, to avoid issues with drifting localization, absolute localization is globally corrected at discrete times, according to predefined event criteria, by matching the current local map to the orbiter's global map. The resolutions of local and global maps can be appropriately chosen for computation and accuracy purposes. Further, the online generated local map, of the form of a structured elevation grid map, can also be used to evaluate the traversability of the surrounding environment and allow for continuous navigation. The objective of this study is to support long‐range low‐supervision planetary exploration. The implemented SLAM technique has been validated with a data set acquired during a field test campaign performed at the Teide Volcano on the island of Tenerife, representative of a Mars/Moon exploration scenario.     

HEVC optimization based on human perception for real-time environments

High-Efficiency Video Coding (HEVC) is the new emerging video coding standard of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). The HEVC standard provides a significant improvement in compression efficiency in comparison with existing standards such as H264/AVC by means of greater complexity. In this paper we will examine several HEVC optimizations based on image analysis to reduce its huge CPU, resource and memory expensive encoding process. The proposed algorithms optimize the HEVC quad-tree partitioning procedure, intra/inter prediction and mode decision by means of H264-based methods and spatial and temporal homogeneity analysis which is directly applied to the original video. The validation process of these approaches was conducted by taking into account the human visual system (HVS). The adopted solution makes it possible to perform HEVC real time encoding for HD sequences on a low cost processor with negligible quality loss. Moreover, the frames pre-processing leverages the logic units and embedded hardware available on an Intel GPU, so the execution time of these stages are negligible for the encoding processor.

     

Improving fMRI in signal drop-out regions at 7 T by using tailored radio-frequency pulses: application to the ventral occipito-temporal cortex

Objective

Signal drop-off occurs in echo-planar imaging in inferior brain areas due to field gradients from susceptibility differences between air and tissue. Tailored-RF pulses based on a hyperbolic secant (HS) have been shown to partially recover signal at 3 T, but have not been tested at higher fields.

Materials and methods

The aim of this study was to compare the performance of an optimized tailored-RF gradient-echo echo-planar imaging (TRF GRE-EPI) sequence with standard GRE-EPI at 7 T, in a passive viewing of faces or objects fMRI paradigm in healthy subjects.

Results

Increased temporal-SNR (tSNR) was observed in the middle and inferior temporal lobes and orbitofrontal cortex of all subjects scanned, but elsewhere tSNR decreased relative to the standard acquisition. In the TRF GRE-EPI, increased functional signal was observed in the fusiform, lateral occipital cortex, and occipital pole, regions known to be part of the visual pathway involved in face-object perception.

Conclusion

This work highlights the potential of TRF approaches at 7 T. Paired with a reversed-gradient distortion correction to compensate for in-plane susceptibility gradients, it provides an improved acquisition strategy for future neurocognitive studies at ultra-high field imaging in areas suffering from static magnetic field inhomogeneities.

     

Cover Image,Volume 66, Issue 7

The cover image, by Maria Pia Di Bello et al., is based on the Research Article Towards a new strategy of a chitosan‐based molecularly imprinted membrane for removal of 4‐nitrophenol in real water samples, DOI: 10.1002/pi.5360 .

     

Optimization study of soybean intermittent drying in fixed-bed drying technology

Intermittent drying of materials is an alternative operation that aims at reducing energy consumption, improve the preservation of dried products or decrease effective drying time. Intermittent drying supplies the system with time-varying input air properties that are opposite to traditional operations, where air properties are constant at the dryer inlet. The major objective of this study is to establish the most satisfactory patterns of air temperature and velocity modulation at the dryer entrance to reduce energy consumption. This optimization study was based on a heterogeneous model for the drying of grains in fixed bed validated with experimental data. Intermittent and conventional operation experiments were conducted using equal energy consumption, and the influence of air temperature and velocity modulation on the drying rates related to the percentage of evaporated water were assessed. Results indicated that higher drying rates can be achieved under intermittent operation, and the validated model based on these results could reasonably predict temperature and moisture content profiles. Simulations pointed out that the best modulation patterns of air properties is a function of a variety of system conditions such as initial temperature and moisture content of both soybean and drying air. However, a tendency to reduce energy consumption was observed when the system operation is initially at high temperature and constantly at low velocity.     

Majorana bound states in a quantum dot device coupled with a superconductor zigzag chain

Research in condensed matter physics on topological insulators and superconductors has contributed greatly to the characterization of the surface properties and zero modes of nanowires. In this work we investigated theoretically, using the recursive Green’s function approach, electron transport through a T-shaped single-level spinless quantum dot, connected to a zigzag chain and coupled to a p-wave superconductor. This model is an extension of the Kitaev chain for a triangular network of finite size with three, four, and five sites. We found that the Majorana zero modes can be tuned through the coupling parameters of the device and that the linear conductance shows Majorana bound states (MBS) in the topological phase, being maximally robust in the general topological phase. This more realistic model permits the detection of MBS via control of the parameters governing the electronic tunneling and could be helpful for relevant experiments.     

Toward a robust optimal point selection: a multiple-criteria decision-making process applied to multi-objective optimization using response surface methodology

During the multi-objective optimization process, numerous efficient solutions may be generated to form the Pareto frontier. Due to the complexity of formulating and solving mathematical problems, choosing the best point to be implemented becomes a non-trivial task. Thus, this paper introduces a weighting strategy named robust optimal point selection, based on ratio diversification/error, to choose the most preferred Pareto optimal point in multi-objective optimization problems using response surface methodology. Furthermore, this paper proposes to explore a theoretical gap—the prediction variance behavior related to the weighting. The ratios Shannon’s entropy/error and diversity/error and the unscaled prediction variance are experimentally modeled using mixture design and the optimal weights for the multi-objective optimization process are defined by the maximization of the proposed measures. The study could demonstrate that the weights used in the multi-objective optimization process influence the prediction variance. Furthermore, the use of diversification measures, such as entropy and diversity, associated with measures of error, such as mean absolute percent error, was determined to be useful in mapping regions of minimum variance within the Pareto optimal responses obtained in the optimization process.

     

Towards bridging the neuro-symbolic gap: deep deductive reasoners

Applied Intelligence - Symbolic knowledge representation and reasoning and deep learning are fundamentally different approaches to artificial intelligence with complementary capabilities. The...