Lithium–sulfur batteries are a promising energy-storage technology due to their relatively low cost and high theoretical energy density. However, one of their major technical problems is the shuttling of soluble polysulfides between electrodes, resulting in rapid capacity fading. Here, we present a metal–organic framework (MOF)-based battery separator to mitigate the shuttling problem. We show that the MOF-based separator acts as an ionic sieve in lithium–sulfur batteries, which selectively sieves Li+ ions while e ciently suppressing undesired polysulfides migrating to the anode side. When a sulfur-containing mesoporous carbon material (approximately 70 wt% sulfur content) is used as a cathode composite without elaborate synthesis or surface modification, a lithium–sulfur battery with a MOF-based separator exhibits a low capacity decay rate (0.019% per cycle over 1,500 cycles). Moreover, there is almost no capacity fading after the initial 100 cycles. Our approach demonstrates the potential for MOF-based materials as separators for energy-storage applications.
Lithium–sulfur (Li–S) batteries with high energy density and long cycle life are considered to be one of the most promising next-generation energy-storage systems beyond routine lithium-ion batteries. Various approaches have been proposed to break down technical barriers in Li–S battery systems. The use
of nanostructured metal oxides and sulfides for high sulfur utilization and long life span of Li–S batteries is reviewed here. The relationships between the intrinsic properties of metal oxide/sulfide hosts and electrochemical performances of Li–S batteries are discussed. Nanostructured metal oxides/ sulfides hosts used in solid sulfur cathodes, separators/interlayers, lithium- metal-anode protection, and lithium polysulfides batteries are discussed respectively. Prospects for the future developments of Li–S batteries with nanostructured metal oxides/sulfides are also discussed.
Reconstruction- and example-based super-resolution
(SR) methods are promising for restoring a high-resolution
(HR) image from low-resolution (LR) image(s). Under large
magnification, reconstruction-based methods usually fail
to hallucinate visual details while example-based methods
sometimes introduce unexpected details. Given a generic
LR image, to reconstruct a photo-realistic SR image and
to suppress artifacts in the reconstructed SR image, we
introduce a multi-scale dictionary to a novel SR method
that simultaneously integrates local and non-local priors.
The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local
area. The non-local prior enriches visual details by taking
a weighted average of a large neighborhood as an estimate
of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate
that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
New applications such as video conferencing, video on demand, multi-
media transcoders, Voice-over-IP (VoIP), intrusion detection, distributed
collaboration, and intranet security require advanced functionality from
networks beyond simple forwarding congestion control techniques.
Emerging technologies such as WiFi and WiMAX are profoundly changing the
landscape of wireless broadband. As we evolve into future generation wireless
networks, a primary challenge is the support of high data rate, integrated multi-
media type traffic over a unified platform. Due to its inherent advantages in
high-speed communication, orthogonal frequency division multiplexing (OFDM)
has become the modem of choice for a number of high profile wireless systems
(e.g., DVB-T, WiFi, WiMAX, Ultra-wideband).
Employing multiple transmit and receive antennas, namely using multi-input multi-output
(MIMO) systems, has proven to be a major breakthrough in providing reliable wireless
communication links. Since their invention in the mid-1990s, transmit diversity, achieved
through space-time coding, and spatial multiplexing schemes have been the focus of much
research in the area of wireless communications.
Today’s wireless services have come a long way since the roll out of the
conventional voice-centric cellular systems. The demand for wireless access
in voice and high rate data multi-media applications has been increasing.
New generation wireless communication systems are aimed at accommodating
this demand through better resource management and improved transmission
technologies.
Mobile communication has gained significant importance in today’s society. As
of 2010, the number of mobile phone subscribers has surpassed 5 billion [ABI10],
and the global annual mobile revenue is soon expected to top $1 trillion [Inf10].
While these numbers appear promising for mobile operators at first sight, the
major game-changer that has come up recently is the fact that the market is
more and more driven by the demand for mobile data traffic [Cis10].
