Toward Stable Cycling of a Cost-Effective Cation-Disordered Rocksalt Cathode via Fluorination

The recently developed Li-excess cation-disordered rock salts (DRXs) exhibit an excellent chemical diversity for the development of alternative Co/Ni-free high-energy cathodes. Herein, the synthesis of a highly fluorinated DRX cathode, Li_1.2Mn_0.6Ti_0.2O_1.8F_0.2, based on cost-effective and earth-abundant transition metals, via a solid-state reaction, is reported. The fluorinated DRX cathode using ammonium fluoride precursor exhibits more uniform particle size and delivers a specific discharge capacity of 233 mAh g⁻¹ and specific energy of 754 Wh kg⁻¹, with 206 mAh g⁻¹ retained after 200 cycles. The combined synchrotron X-ray absorption spectroscopy and resonant inelastic X-ray scattering spectroscopy analysis reveals that the remarkable cycling performance is attributed to the high fluorination and thus enhanced Mn content, enabling the utilization of more Mn redox than the oxide analog. This study demonstrates a great promise to develop next-generation cost-effective DRX cathodes with enhanced capacity retention for high-energy Li-ion batteries.     

Hardware Implementation of a Fixed-Point Decoder for Low-Density Lattice Codes

Journal of Signal Processing Systems - This paper describes a field-programmable gate array (FPGA) implementation of a fixed-point low-density lattice code (LDLC) decoder where the Gaussian mixture...     

Parallel best-first search algorithms for planning problems on multi-core processors

The Journal of Supercomputing - The multiplication of computing cores in modern processor units permits revisiting the design of classical algorithms to improve computational performance in complex...     

Instructing students on effective sequences of examples and problems: Does self-regulated learning improve from knowing what works and why?

Nowadays, students often practice problem-solving skills in online learning environments with the help of examples and problems. This requires them to self-regulate their learning. It is questionable how novices self-regulate their learning from examples and problems and whether they need support. The present study investigated the open questions (1) to what extent students' (novices) task selections align with instructional design principles and (2) whether informing them about these principles would improve their task selections, learning outcomes, and motivation. Higher education students (N = 150) learned a problem-solving procedure by fixed sequences of examples and problems (FS-condition), or by self-regulated learning (SRL). The SRL participants selected tasks from a database, varying in format, complexity, and cover story, either with (ISRL-condition) or without (SRL-condition) watching a video detailing the instructional design principles. Students' task-selection patterns in both SRL conditions largely corresponded to the principles, although tasks were built up in complexity more often in the ISRL-condition than in the SRL-condition. Moreover, there was still room for improvement in students' task selections after solving practice problems. The video instruction helped students to better apply certain principles, but did not enhance learning and motivation. Finally, there were no test performance or motivational differences among conditions. Although these findings might suggest it is relatively ‘safe’ to allow students to independently start learning new problems-solving tasks using examples and problems, caution is warranted: It is unclear whether these findings generalize to other student populations, as the students participating in this study have had some experience with similar tasks or learning with examples. Moreover, as there was still room for improvement in students' task selections, follow-up research should investigate how we can further improve self-regulated learning from examples and practice problems.     

Measuring Mental Workload Using ERPs Based on FIR,ICA, and MARA

Mental workload is considered to be strongly linked to human performance, and the ability to measure it accurately is key for balancing human health and work. In this study, brain signals were elicited by mental arithmetic tasks of varying difficulty to stimulate different levels of mental workload. In addition, a finite impulse response (FIR) filter, independent component analysis (ICA), and multiple artifact rejection algorithms (MARAs) were used to filter event-related potentials (ERPs). Then, the data consisting of ERPs, subjective ratings of mental workload, and task performance, were analyzed through the use of variance and Spearman’s correlation during a simulated computer task. We found that participants responded faster and performed better in the easy task condition, followed by the medium and high-difficulty conditions, which verifies the validity of the ERP filtering. Moreover, larger P2 and P3 waveforms were evoked as the task difficulty increased, and a higher task difficulty elicited a more enhanced N300. Correlation analysis revealed a negative relationship between the amplitude of P3 and the subjective ratings, and a positive relationship between the P3 amplitude and accuracy. The results presented in this paper demonstrate that a combination of FIR, ICA, and MARA methods can filter ERPs in the non-invasive real-time measurement of workload. Additionally, frontocentral P2, N3, and parietal P3 components showed differences between genders. The proposed measurement of mental workload can be useful for real-time identification of mental states and can be applied to human–computer interaction in the future.     

Anticipating Cutoff Diameters in Deterministic Lateral Displacement (DLD) Microfluidic Devices for an Optimized Particle Separation

Deterministic lateral displacement (DLD) devices enable to separate nanometer to micrometer‐sized particles around a cutoff diameter, during their transport through a microfluidic channel with slanted rows of pillars. In order to design appropriate DLD geometries for specific separation sizes, robust models are required to anticipate the value of the cutoff diameter. So far, the proposed models result in a single cutoff diameter for a given DLD geometry. This paper shows that the cutoff diameter actually varies along the DLD channel, especially in narrow pillar arrays. Experimental and numerical results reveal that the variation of the cutoff diameter is induced by boundary effects at the channel side walls, called the wall effect. The wall effect generates unexpected particle trajectories that may compromise the separation efficiency. In order to anticipate the wall effect when designing DLD devices, a predictive model is proposed in this work and has been validated experimentally. In addition to the usual geometrical parameters, a new parameter, the number of pillars in the channel cross dimension, is considered in this model to investigate its influence on the particle trajectories.