▶ The phase transformation and performance of LiFePO4 materials are reviewed. ▶ Carbon coating is more critical than doping and particle size control. ▶ Iron deposit on graphite anode leads to ...capacity degradation. ▶ Low temperature performance can be improved by electrolyte modification.
LiFePO4 has been considered a promising battery material in electric vehicles. However, there are still a number of technical challenges to overcome before its wide-spread applications. In this article, the structure and electrochemical performance of LiFePO4 are reviewed in light of the major technical requirements for EV batteries. The rate capability, capacity density, cyclic life and low-temperature performance of various LiFePO4 materials are described. The major factors affecting these properties are discussed, which include particle size, doping, carbon coating, conductive carbon loading and synthesis techniques. Important future research for science and engineering is suggested.
Reconfigurable intelligent surface (RIS) is envisioned to be an essential component of the paradigm for beyond 5G networks as it can potentially provide similar or higher array gains with much lower ...hardware cost and energy consumption compared with the massive multiple-input multiple-output (MIMO) technology. In this paper, we focus on one of the fundamental challenges, namely the channel acquisition, in a RIS-assisted multiuser MIMO system. The state-of-the-art channel acquisition approach in such a system with fully passive RIS elements estimates the cascaded transmitter-to-RIS and RIS-to-receiver channels by adopting excessively long training sequences. To estimate the cascaded channels with an affordable training overhead, we formulate the channel estimation problem in the RIS-assisted multiuser MIMO system as a matrix-calibration based matrix factorization task. By exploiting the information on the slow-varying channel components and the hidden channel sparsity, we propose a novel message-passing based algorithm to factorize the cascaded channels. Furthermore, we present an analytical framework to characterize the theoretical performance bound of the proposed estimator in the large-system limit. Finally, we conduct simulations to verify the high accuracy and efficiency of the proposed algorithm.
The anomalous Hall effect is a fundamental transport process in solids arising from the spin-orbit coupling. In a quantum anomalous Hall insulator, spontaneous magnetic moments and spin-orbit ...coupling combine to give rise to a topologically nontrivial electronic structure, leading to the quantized Hall effect without an external magnetic field. Based on first-principles calculations, we predict that the tetradymite semiconductors Bi₂Te₃, Bi₂Se₃, and Sb₂Te₃ form magnetically ordered insulators when doped with transition metal elements (Cr or Fe), in contrast to conventional dilute magnetic semiconductors where free carriers are necessary to mediate the magnetic coupling. In two-dimensional thin films, this magnetic order gives rise to a topological electronic structure characterized by a finite Chern number, with the Hall conductance quantized in units of e²/h (where e is the charge of an electron and h is Planck's constant).
...in addition to innovative courses for a better learning experience, promotional videos can be useful to motivate children to have a healthy lifestyle at home by increasing physical activities, ...having a balanced diet, regular sleep pattern, and good personal hygiene.8 To make these educational materials truly effective, they must be age-appropriate and attractive. Schools can actively promote a health-conscious schedule, good personal hygiene, encourage physical activities, appropriate diet, and good sleep habits, and integrate such health promotion materials into the school curriculum.3 A Chinese child studies from home during the COVID-19 outbreak Fan Jiang In the event of home confinement, parents are often the closest and best resource for children to seek help from. Good parenting skills become particularly crucial when children are confined at home. Besides monitoring child performance and behaviour, parents also need to respect their identity and needs, and they need to help children develop self-discipline skills.
Biofuel energy as an alternative and additive form of energy to fossil fuel has gained much attention in recent times. In order to sustain such a vision, a robust supply chain is of extreme ...importance in helping to deliver competitive biofuel to the end user markets. In this paper, firstly, an introduction of the evolution of biofuels and the general structure of the biofuel supply chain are presented. Secondly, the three types of decision making levels and uncertainties that are inherent within the biofuel supply chain are discussed. Thirdly, important methodologies for modeling uncertainties in the decision making process are provided. Fourthly, sustainability concepts and models that give perspectives to the social, economical and environmental concepts are reviewed. Finally, conclusions and future research based on incorporating uncertainties and sustainability concepts within the biofuel supply chain are drawn and suggested, respectively.
This paper presents a new technique for artificial neural network (ANN) inverse modeling and applications to microwave filters. In inverse modeling of a microwave component, the inputs to the model ...are electrical parameters such as <inline-formula> <tex-math notation="LaTeX">S </tex-math></inline-formula>-parameters, and the outputs of the model are geometrical or physical parameters. Since the analytical formula of the inverse input-output relationship does not exist, the ANN becomes a logical choice, because it can be trained to learn from the data in inverse modeling. The main challenge of inverse modeling is the nonuniqueness problem. This problem in the ANN inverse modeling is that different training samples with the same or very similar input values have quite different (contradictory) output values (multivalued solutions). In this paper, we propose a multivalued neural network inverse modeling technique to associate a single set of electrical parameters with multiple sets of geometrical or physical parameters. One set of geometrical or physical parameters is called one value of our proposed inverse model. Our proposed multivalued neural network is structured to accommodate multiple values for the model output. We also propose a new training error function to focus on matching each training sample using only one value of our proposed inverse model, while other values are free and can be trained to match other contradictory samples. In this way, our proposed multivalued neural network can learn all the training data by automatically redirecting contradictory information into different values of the proposed inverse model. Therefore, our proposed technique can solve the nonuniqueness problem in a simpler and more automated way compared with the existing ANN inverse modeling techniques. This technique is illustrated by inverse modeling and parameter extraction of four microwave filter examples.
Developing high-performance film dielectrics for capacitive energy storage has been a great challenge for modern electrical devices. Despite good results obtained in lead titanate-based dielectrics, ...lead-free alternatives are strongly desirable due to environmental concerns. Here we demonstrate that giant energy densities of ~70 J cm
, together with high efficiency as well as excellent cycling and thermal stability, can be achieved in lead-free bismuth ferrite-strontium titanate solid-solution films through domain engineering. It is revealed that the incorporation of strontium titanate transforms the ferroelectric micro-domains of bismuth ferrite into highly-dynamic polar nano-regions, resulting in a ferroelectric to relaxor-ferroelectric transition with concurrently improved energy density and efficiency. Additionally, the introduction of strontium titanate greatly improves the electrical insulation and breakdown strength of the films by suppressing the formation of oxygen vacancies. This work opens up a feasible and propagable route, i.e., domain engineering, to systematically develop new lead-free dielectrics for energy storage.
Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. In this work, we introduce a relatively new swarm intelligence ...algorithm,
i.e.
the artificial bee colony (ABC) algorithm proposed in 2005, to this field. It is inspired by the foraging behavior of a bee colony, and only three parameters are needed to control it. We applied it to several potential functions of quite different nature,
i.e.
, the Coulomb-Born-Mayer, Lennard-Jones, Morse,
Z
and Gupta potentials. The benchmarks reveal that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum, while for short-ranged ones it is sometimes trapped into a local minimum funnel on a potential energy surface of large clusters. We have released an efficient, user-friendly, and free program "ABCluster" to realize the ABC algorithm. It is a black-box program for non-experts as well as experts and might become a useful tool for chemists to study clusters.
Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. We apply a swarm-intelligence based heuristic algorithm,
i.e.
the artificial bee colony algorithm to solve this problem for various kinds of clusters.
•Lanthanide molecular probes are promising candidates for NIR bioimaging and biosensing.•We summarized the design, synthesis and applications of lanthanide complexes for bioimaging.•Lanthanide ...complexes will be the next generation biomedical theranostic agents.
Recent advances in NIR detector bloom the design of NIR fluorophores for bioimaging guided diagnosis and therapeutics, with reduced light-tissue interaction, enhanced signal-to-noise ratio and increased penetration depth. NIR lanthanide molecular probes represent an important and emerging group of NIR imaging and sensing materials with attractive structural and photophysical characteristics including small sizes, metal-centered emission, long decay lifetime, large Stokes shift and high resistance to photobleaching. In this review, the sensitization of lanthanides and design principle of lanthanide molecular probes were described. We summarized the recent progresses in last decade on NIR luminescent lanthanide molecular probes by precisely tuning the antenna ligands. The development tendency of applying lanthanide molecular probes for in vivo bioimaging and biosensing would also be discussed, showing the unique and attractive properties of lanthanide coordination compounds compared to organic molecules and inorganic quantum nanoparticles.
Novel 3D Ni1−xCoxSe2 mesoporous nanosheet networks with tunable stoichiometry are successfully synthesized on Ni foam (Ni1−xCoxSe2 MNSN/NF with x ranging from 0 to 0.35). The collective effects of ...special morphological design and electronic structure engineering enable the integrated electrocatalyst to have very high activity for hydrogen evolution reaction (HER) and excellent stability in a wide pH range. Ni0.89Co0.11Se2 MNSN/NF is revealed to exhibit an overpotential (η10) of 85 mV at −10 mA cm−2 in alkaline medium (pH 14) and η10 of 52 mV in acidic solution (pH 0), which are the best among all selenide‐based electrocatalysts reported thus far. In particular, it is shown for the first time that the catalyst can work efficiently in neutral solution (pH 7) with a record η10 of 82 mV for all noble metal‐free electrocatalysts ever reported. Based on theoretical calculations, it is further verified that the advanced all‐pH HER activity of Ni0.89Co0.11Se2 is originated from the enhanced adsorption of both H+ and H2O induced by the substitutional doping of cobalt at an optimal level. It is believed that the present work provides a valuable route for the design and synthesis of inexpensive and efficient all‐pH HER electrocatalysts.
An integrated electrocatalyst comprising 3D mesoporous Ni0.89Co0.11Se2 nanosheet networks on Ni foam is synthesized, and it demonstrates very high activities and excellent stabilities for hydrogen evolution reaction (HER) in all‐pH conditions. Theoretical calculations verify that electronic structure engineering by optimal Co doping enhances the adsorption of H+ and H2O, leading to the advanced all‐pH HER activity of the catalyst.
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