Lithium extraction from high Mg/Li ratio brine is a key technical problem in the world. Based on the principle of rocking‐chair lithium‐ion batteries, cathode material LiFePO
4
is applied to extract lithium from brine, and a novel lithium‐ion battery system of LiFePO
4
| NaCl solution | anion‐exchange membrane | brine | FePO
4
is constructed. In this method, Li
+
is selectively absorbed from the brine by FePO
4
(Li
+
+ e + FePO
4
= LiFePO
4
); meanwhile, Li
+
is desorbed from LiFePO
4
(LiFePO
4
− e = Li
+
+ FePO
4
) and enriched efficiently. To treat a raw brine solution, the Mg/Li ratio decreases from the initial 134.4 in the brine to 1.2 in the obtained anolyte and 83% lithium is extracted. For the treatment of an old brine solution, the Mg/Li ratio decreases from the initial 48.4 in the brine to 0.5 and the concentration of lithium in the anolyte is accumulated about six times (from the initial 0.51 g L
−1
in the brine to 3.2 g L
−1
in the anolyte), with the absorption capacity of about 25 mg (Li) g (LiFePO
4
)
−1
. Additionally, it displays a great perspective on the application in light of its high selectively, good cycling performance, effective lithium enrichment, environmental friendliness, low cost, and avoidance of poisonous organic reagents and harmful acid or oxidant.
Sequence-to-sequence models with soft attention had significant success in machine translation, speech recognition, and question answering. Though capable and easy to use, they require that the entirety of the input sequence is available at the beginning of inference, an assumption that is not valid for instantaneous translation and speech recognition. To address this problem, we present a new method for solving sequence-to-sequence problems using hard online alignments instead of soft offline alignments. The online alignments model is able to start producing outputs without the need to first process the entire input sequence. A highly accurate online sequence-to-sequence model is useful because it can be used to build an accurate voice-based instantaneous translator. Our model uses hard binary stochastic decisions to select the timesteps at which outputs will be produced. The model is trained to produce these stochastic decisions using a standard policy gradient method. In our experiments, we show that this model achieves encouraging performance on TIMIT and Wall Street Journal (WSJ) speech recognition datasets.
Parametric nonlinear optical processes are at the heart of nonlinear optics underpinning the central role in the generation of entangled photons as well as the realization of coherent optical sources.Exciton-polaritons are capable to sustain parametric scattering at extremely low threshold, offering a readily accessible platform to study bosonic fluids. Recently, two-dimensional transition-metal dichalcogenides (TMDs) have attracted great attention in strong light-matter interactions due to robust excitonic transitions and unique spin-valley degrees of freedom. However, further progress is hindered by the lack of realizations of strong nonlinear effects in TMDs polaritons. Here, we demonstrate the first realization of nonlinear optical parametric polaritons in a WS2 monolayer microcavity pumped at the inflection point and triggered in the ground state. We observed the formation of a phase-matched idler state and nonlinear amplification that preserves the valley population and survives up to room temperature. Our results open a new door towards the realization of future for all-optical valley polariton nonlinear devices.
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