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•Metal–organic frameworks (MOFs) for the synthesis of cyclic carbonates are reviewed.•Functional porous organic polymers (POPs) for the synthesis of cyclic carbonates are ...reviewed.•The syntheses, structural features and catalytic performances of the porous catalytic materials are included comprehensively.•The MOFs and POPs catalysts are rationally classified and summarized based on their various active sites.
The capture and chemical fixation of carbon dioxide (CO2) into cyclic carbonates is considered to be a promising way to alleviate CO2 concerns and produce fine chemicals. This process can be effectively promoted by various kinds of newly developed porous heterogeneous catalysts with Lewis acidic and nucleophilic sites. These porous catalytic materials include metal–organic frameworks (MOFs), covalent-organic frameworks (COFs), nanoporous ionic organic networks (NIONs) and amorphous porous organic polymers. In this review, we have briefly classified these materials based on their different structural features and compositions. The syntheses and catalytic performances of these porous heterogeneous catalysts are described from the perspective of catalyst design. This review will guide material scientists attempting to design more efficient porous catalysts for CO2 capture and conversions.
The unique applications of porous metal–organic framework (MOF) liquids with permanent porosity and fluidity have attracted significant attention. However, fabrication of porous MOF liquids remains ...challenging because of the easy intermolecular self‐filling of the cavity or the rapid settlement of porous hosts in hindered solvents that cannot enter their pores. Herein, we report a facile strategy for the fabrication of a MOF liquid (Im‐UiO‐PL) by surface ionization of an imidazolium‐functionalized framework with a sterically hindered poly(ethylene glycol) sulfonate (PEGS) canopy. The Im‐UiO‐PL obtained in this way has a CO2 adsorption approximately 14 times larger than that of pure PEGS. Distinct from a porous MOF solid counterpart, the stored CO2 in Im‐UiO‐PL can be slowly released and efficiently utilized to synthesize cyclic carbonates in the atmosphere. This is the first example of the use of a porous MOF liquid as a CO2 storage material for catalysis. It offers a new method for the fabrication of unique porous liquid MOFs with functional behaviors in various fields of gas adsorption and catalysis.
An ionization strategy has been developed to fabricate a porous MOF liquid, which shows large adsorption of CO2. The adsorbed CO2 can subsequently be slowly released and efficiently utilized to synthesize, for example, cyclic carbonates.
We study the performance of classical and quantum machine learning (ML) models in predicting outcomes of physical experiments. The experiments depend on an input parameter x and involve execution of ...a (possibly unknown) quantum process E. Our figure of merit is the number of runs of E required to achieve a desired prediction performance. We consider classical ML models that perform a measurement and record the classical outcome after each run of E, and quantum ML models that can access E coherently to acquire quantum data; the classical or quantum data are then used to predict the outcomes of future experiments. We prove that for any input distribution D(x), a classical ML model can provide accurate predictions on average by accessing E a number of times comparable to the optimal quantum ML model. In contrast, for achieving an accurate prediction on all inputs, we prove that the exponential quantum advantage is possible. For example, to predict the expectations of all Pauli observables in an n-qubit system ρ, classical ML models require 2Ω(n) copies of ρ, but we present a quantum ML model using only O(n) copies. Our results clarify where the quantum advantage is possible and highlight the potential for classical ML models to address challenging quantum problems in physics and chemistry.
A solar-blind photodetector (PD) based on the cosputtered aluminum-gallium oxide (AGO) material after thermal annealing at 900 °C has been demonstrated using a metal-semiconductor-metal structure. By ...incorporating optimum trace aluminum (Al), the AGO PD shows the peak responsivity (at 230 nm) of 1.38 A/W under a bias voltage of 5 V, which is 53.61 times greater than that of the PD from the gallium oxide (GO) film without incorporating any Al content. The photocurrent, dark current, and detectivity (at 5 V and 230 nm) of AGO PD are also improved to be 46.4, 0.83, and 96.5 times, respectively, greater than those of GO one. Unlike conventional GO samples revealing obvious drop in spectral response from 250 to 200 nm, the AGO PD with an Al/(Al + Ga) ratio of 1.8% exhibits a nearly flat responsivity curve in the deep ultraviolet region. This improvement is significant compared with previous reports for the GO and AGO PDs by other growth methods.
Exploiting Zn metal‐free anode materials would be an effective strategy to resolve the problems of Zn metal dendrites that severely hinder the development of Zn ion batteries (ZIBs). However, the ...study of Zn metal‐free anode materials is still in their infancy, and more importantly, the low energy density severely limits their practical implementations. Herein, a novel (NH4)2V10O25 · 8H2O@Ti3C2Tx (NHVO@Ti3C2Tx) film anode is proposed and investigated for constructing “rocking‐chair” ZIBs. The NHVO@Ti3C2Tx electrode shows a capacity of 514.7 mAh g−1 and presents low potential which is 0.59 V (vs Zn2+/Zn) at 0.1 A g−1. The introduction of Ti3C2Tx not only affords an interconnected conductive network, but also stabilizes the NHVO nanobelts structure for a long cycle life (84.2% retention at 5.0 A g−1 over 6000 cycles). As a proof‐of‐concept, a zinc metal‐free full battery is successfully demonstrated, which delivers the highest capacity of 131.7 mAh g−1 (mass containing anodic and cathodic) and energy density of 97.1 Wh kg−1 compared to all reported aqueous “rocking‐chair” ZIBs. Furthermore, a long cycling span of 6000 cycles is obtained with capacity retention reaching up to 92.1%, which is impressive. This work is expected to provide new moment toward V‐based materials for “rocking‐chair” ZIBs.
A novel (NH4)2V10O25 · 8H2O@Ti3C2Tx (NHVO@Ti3C2Tx) film anode is proposed and investigated for constructing “rocking‐chair” zinc ion batteries (ZIBs). Due to good crystal and electrode structure engineering, the hybrid electrode exhibits superior electrochemical performance with a low potential (vs Zn2+/Zn). By pairing the NHVO@ Ti3C2Tx film anode and ZnMn2O4 cathode, the Zn‐ion full battery can deliver remarkable specific capacity and energy density.
Power of data in quantum machine learning Huang, Hsin-Yuan; Broughton, Michael; Mohseni, Masoud ...
Nature communications,
05/2021, Volume:
12, Issue:
1
Journal Article
Peer reviewed
Open access
The use of quantum computing for machine learning is among the most exciting prospective applications of quantum technologies. However, machine learning tasks where data is provided can be ...considerably different than commonly studied computational tasks. In this work, we show that some problems that are classically hard to compute can be easily predicted by classical machines learning from data. Using rigorous prediction error bounds as a foundation, we develop a methodology for assessing potential quantum advantage in learning tasks. The bounds are tight asymptotically and empirically predictive for a wide range of learning models. These constructions explain numerical results showing that with the help of data, classical machine learning models can be competitive with quantum models even if they are tailored to quantum problems. We then propose a projected quantum model that provides a simple and rigorous quantum speed-up for a learning problem in the fault-tolerant regime. For near-term implementations, we demonstrate a significant prediction advantage over some classical models on engineered data sets designed to demonstrate a maximal quantum advantage in one of the largest numerical tests for gate-based quantum machine learning to date, up to 30 qubits.
Herein, an effective tandem catalysis strategy is developed to improve the selectivity of the CO2RR towards C2H4 by multiple distinct catalytic sites in local vicinity. An earth‐abundant ...elements‐based tandem electrocatalyst PTF(Ni)/Cu is constructed by uniformly dispersing Cu nanoparticles (NPs) on the porphyrinic triazine framework anchored with atomically isolated nickel–nitrogen sites (PTF(Ni)) for the enhanced CO2RR to produce C2H4. The Faradaic efficiency of C2H4 reaches 57.3 % at −1.1 V versus the reversible hydrogen electrode (RHE), which is about 6 times higher than the non‐tandem catalyst PTF/Cu, which produces CH4 as the major carbon product. The operando infrared spectroscopy and theoretic density functional theory (DFT) calculations reveal that the local high concentration of CO generated by PTF(Ni) sites can facilitate the C−C coupling to form C2H4 on the nearby Cu NP sites. The work offers an effective avenue to design electrocatalysts for the highly selective CO2RR to produce multicarbon products via a tandem route.
An effective tandem catalysis strategy is developed to enhance the selectivity of the CO2 electroreduction reaction towards C2H4 with a 6‐fold increase in comparison with that of the non‐tandem catalysts. The local high concentration of CO generated by atomically isolated nickel–nitrogen sites PTF(Ni) sites can facilitate the C−C coupling to form C2H4 on the nearby Cu NP sites, thus switching from CH4 to C2H4 production with a Faradaic efficiency of 57.3 %.
We consider the problem of jointly estimating expectation values of many Pauli observables, a crucial subroutine in variational quantum algorithms. Starting with randomized measurements, we propose ...an efficient derandomization procedure that iteratively replaces random single-qubit measurements by fixed Pauli measurements; the resulting deterministic measurement procedure is guaranteed to perform at least as well as the randomized one. In particular, for estimating any L low-weight Pauli observables, a deterministic measurement on only of order log (L) copies of a quantum state suffices. In some cases, for example, when some of the Pauli observables have high weight, the derandomized procedure is substantially better than the randomized one. Specifically, numerical experiments highlight the advantages of our derandomized protocol over various previous methods for estimating the ground-state energies of small molecules.
We propose a method for detecting bipartite entanglement in a many-body mixed state based on estimating moments of the partially transposed density matrix. The estimates are obtained by performing ...local random measurements on the state, followed by postprocessing using the classical shadows framework. Our method can be applied to any quantum system with single-qubit control. We provide a detailed analysis of the required number of experimental runs, and demonstrate the protocol using existing experimental data Brydges et al., Science 364, 260 (2019)SCIEAS0036-807510.1126/science.aau4963.
Microglia are the resident macrophages of the central nervous system. Microglia possess varied morphologies and functions. Under normal physiological conditions, microglia mainly exist in a resting ...state and constantly monitor their microenvironment and survey neuronal and synaptic activity. Through the C1q, C3 and CR3 "Eat Me" and CD47 and SIRPα "Don't Eat Me" complement pathways, as well as other pathways such as CX3CR1 signaling, resting microglia regulate synaptic pruning, a process crucial for the promotion of synapse formation and the regulation of neuronal activity and synaptic plasticity. By mediating synaptic pruning, resting microglia play an important role in the regulation of experience-dependent plasticity in the barrel cortex and visual cortex after whisker removal or monocular deprivation, and also in the regulation of learning and memory, including the modulation of memory strength, forgetfulness, and memory quality. As a response to brain injury, infection or neuroinflammation, microglia become activated and increase in number. Activated microglia change to an amoeboid shape, migrate to sites of inflammation and secrete proteins such as cytokines, chemokines and reactive oxygen species. These molecules released by microglia can lead to synaptic plasticity and learning and memory deficits associated with aging, Alzheimer's disease, traumatic brain injury, HIV-associated neurocognitive disorder, and other neurological or mental disorders such as autism, depression and post-traumatic stress disorder. With a focus mainly on recently published literature, here we reviewed the studies investigating the role of resting microglia in synaptic plasticity and learning and memory, as well as how activated microglia modulate disease-related plasticity and learning and memory deficits. By summarizing the function of microglia in these processes, we aim to provide an overview of microglia regulation of synaptic plasticity and learning and memory, and to discuss the possibility of microglia manipulation as a therapeutic to ameliorate cognitive deficits associated with aging, Alzheimer's disease, traumatic brain injury, HIV-associated neurocognitive disorder, and mental disorders.
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