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欧盟资助3个成员国的能源系统现代化项目 快报文章
气候变化快报,2021年第17期
作者:  刘燕飞
Microsoft Word(15Kb)  |  收藏  |  浏览/下载:740/0  |  提交时间:2021/09/06
Modernisation Fund  European  energy systems  
英国提出能源系统智能与灵活性计划和数字化战略 快报文章
气候变化快报,2021年第16期
作者:  刘燕飞
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Net Zero Energy System  Digitalising  Smart Systems  Flexibility  
Accelerated discovery of CO2 electrocatalysts using active machine learning 期刊论文
NATURE, 2020, 581 (7807) : 178-+
作者:  Lan, Jun;  Ge, Jiwan;  Yu, Jinfang;  Shan, Sisi;  Zhou, Huan;  Fan, Shilong;  Zhang, Qi;  Shi, Xuanling;  Wang, Qisheng;  Zhang, Linqi;  Wang, Xinquan
收藏  |  浏览/下载:88/0  |  提交时间:2020/07/03

The rapid increase in global energy demand and the need to replace carbon dioxide (CO2)-emitting fossil fuels with renewable sources have driven interest in chemical storage of intermittent solar and wind energy(1,2). Particularly attractive is the electrochemical reduction of CO2 to chemical feedstocks, which uses both CO2 and renewable energy(3-8). Copper has been the predominant electrocatalyst for this reaction when aiming for more valuable multi-carbon products(9-16), and process improvements have been particularly notable when targeting ethylene. However, the energy efficiency and productivity (current density) achieved so far still fall below the values required to produce ethylene at cost-competitive prices. Here we describe Cu-Al electrocatalysts, identified using density functional theory calculations in combination with active machine learning, that efficiently reduce CO2 to ethylene with the highest Faradaic efficiency reported so far. This Faradaic efficiency of over 80 per cent (compared to about 66 per cent for pure Cu) is achieved at a current density of 400 milliamperes per square centimetre (at 1.5 volts versus a reversible hydrogen electrode) and a cathodic-side (half-cell) ethylene power conversion efficiency of 55 +/- 2 per cent at 150 milliamperes per square centimetre. We perform computational studies that suggest that the Cu-Al alloys provide multiple sites and surface orientations with near-optimal CO binding for both efficient and selective CO2 reduction(17). Furthermore, in situ X-ray absorption measurements reveal that Cu and Al enable a favourable Cu coordination environment that enhances C-C dimerization. These findings illustrate the value of computation and machine learning in guiding the experimental exploration of multi-metallic systems that go beyond the limitations of conventional single-metal electrocatalysts.


  
Quantum entanglement between an atom and a molecule 期刊论文
NATURE, 2020, 581 (7808) : 273-+
作者:  Trisos, Christopher H.;  Merow, Cory;  Pigot, Alex L.
收藏  |  浏览/下载:29/0  |  提交时间:2020/07/03

Conventional information processors convert information between different physical carriers for processing, storage and transmission. It seems plausible that quantum information will also be held by different physical carriers in applications such as tests of fundamental physics, quantum enhanced sensors and quantum information processing. Quantum controlled molecules, in particular, could transduce quantum information across a wide range of quantum bit (qubit) frequencies-from a few kilohertz for transitions within the same rotational manifold(1), a few gigahertz for hyperfine transitions, a few terahertz for rotational transitions, to hundreds of terahertz for fundamental and overtone vibrational and electronic transitions-possibly all within the same molecule. Here we demonstrate entanglement between the rotational states of a (CaH+)-Ca-40 molecular ion and the internal states of a Ca-40(+) atomic ion(2). We extend methods used in quantum logic spectroscopy(1,3) for pure-state initialization, laser manipulation and state readout of the molecular ion. The quantum coherence of the Coulomb coupled motion between the atomic and molecular ions enables subsequent entangling manipulations. The qubit addressed in the molecule has a frequency of either 13.4 kilohertz(1) or 855 gigahertz(3), highlighting the versatility of molecular qubits. Our work demonstrates how molecules can transduce quantum information between qubits with different frequencies to enable hybrid quantum systems. We anticipate that our method of quantum control and measurement of molecules will find applications in quantum information science, quantum sensors, fundamental and applied physics, and controlled quantum chemistry.


Quantum entanglement is realized between rotational levels of a molecular ion with energy differences spanning several orders of magnitude and long-lived internal states of a single atomic ion.


  
Short-range order and its impact on the CrCoNi medium-entropy alloy 期刊论文
NATURE, 2020, 581 (7808) : 283-+
作者:  Tan, Hwei-Ee;  Sisti, Alexander C.;  Jin, Hao;  Vignovich, Martin;  Villavicencio, Miguel;  Tsang, Katherine S.;  Goffer, Yossef;  Zuker, Charles S.
收藏  |  浏览/下载:8/0  |  提交时间:2020/07/03

Traditional metallic alloys are mixtures of elements in which the atoms of minority species tend to be distributed randomly if they are below their solubility limit, or to form secondary phases if they are above it. The concept of multiple-principal-element alloys has recently expanded this view, as these materials are single-phase solid solutions of generally equiatomic mixtures of metallic elements. This group of materials has received much interest owing to their enhanced mechanical properties(1-5). They are usually called medium-entropy alloys in ternary systems and high-entropy alloys in quaternary or quinary systems, alluding to their high degree of configurational entropy. However, the question has remained as to how random these solid solutions actually are, with the influence of short-range order being suggested in computational simulations but not seen experimentally(6,7). Here we report the observation, using energy-filtered transmission electron microscopy, of structural features attributable to short-range order in the CrCoNi medium-entropy alloy. Increasing amounts of such order give rise to both higher stacking-fault energy and hardness. These findings suggest that the degree of local ordering at the nanometre scale can be tailored through thermomechanical processing, providing a new avenue for tuning the mechanical properties of medium- and high-entropy alloys.


Metal alloys consisting of three or more major elemental components show enhanced mechanical properties, which are now shown to be correlated with short-range order observed with electron microscopy.


  
Loopy Levy flights enhance tracer diffusion in active suspensions 期刊论文
NATURE, 2020, 579 (7799) : 364-+
作者:  Hu, Bo;  Jin, Chengcheng;  Zeng, Xing;  Resch, Jon M.;  Jedrychowski, Mark P.;  Yang, Zongfang;  Desai, Bhavna N.;  Banks, Alexander S.;  Lowell, Bradford B.;  Mathis, Diane;  Spiegelman, Bruce M.
收藏  |  浏览/下载:16/0  |  提交时间:2020/07/03

A theoretical framework describing the hydrodynamic interactions between a passive particle and an active medium in out-of-equilibrium systems predicts long-range Levy flights for the diffusing particle driven by the density of the active component.


Brownian motion is widely used as a model of diffusion in equilibrium media throughout the physical, chemical and biological sciences. However, many real-world systems are intrinsically out of equilibrium owing to energy-dissipating active processes underlying their mechanical and dynamical features(1). The diffusion process followed by a passive tracer in prototypical active media, such as suspensions of active colloids or swimming microorganisms(2), differs considerably from Brownian motion, as revealed by a greatly enhanced diffusion coefficient(3-10) and non-Gaussian statistics of the tracer displacements(6,9,10). Although these characteristic features have been extensively observed experimentally, there is so far no comprehensive theory explaining how they emerge from the microscopic dynamics of the system. Here we develop a theoretical framework to model the hydrodynamic interactions between the tracer and the active swimmers, which shows that the tracer follows a non-Markovian coloured Poisson process that accounts for all empirical observations. The theory predicts a long-lived Levy flight regime(11) of the loopy tracer motion with a non-monotonic crossover between two different power-law exponents. The duration of this regime can be tuned by the swimmer density, suggesting that the optimal foraging strategy of swimming microorganisms might depend crucially on their density in order to exploit the Levy flights of nutrients(12). Our framework can be applied to address important theoretical questions, such as the thermodynamics of active systems(13), and practical ones, such as the interaction of swimming microorganisms with nutrients and other small particles(14) (for example, degraded plastic) and the design of artificial nanoscale machines(15).


  
Probing the core of the strong nuclear interaction 期刊论文
NATURE, 2020, 578 (7796) : 540-+
作者:  Bialas, Allison R.;  Presumey, Jessy;  Das, Abhishek;  van der Poel, Cees E.;  Lapchak, Peter H.;  Mesin, Luka;  Victora, Gabriel;  Tsokos, George C.;  Mawrin, Christian;  Herbst, Ronald;  Carroll, Michael C.
收藏  |  浏览/下载:16/0  |  提交时间:2020/07/03

High-energy electron scattering that can isolate pairs of nucleons in high-momentum configurations reveals a transition to spin-independent scalar forces at small separation distances, supporting the use of point-like nucleon models to describe dense nuclear systems.


The strong nuclear interaction between nucleons (protons and neutrons) is the effective force that holds the atomic nucleus together. This force stems from fundamental interactions between quarks and gluons (the constituents of nucleons) that are described by the equations of quantum chromodynamics. However, as these equations cannot be solved directly, nuclear interactions are described using simplified models, which are well constrained at typical inter-nucleon distances(1-5) but not at shorter distances. This limits our ability to describe high-density nuclear matter such as that in the cores of neutron stars(6). Here we use high-energy electron scattering measurements that isolate nucleon pairs in short-distance, high-momentum configurations(7-9), accessing a kinematical regime that has not been previously explored by experiments, corresponding to relative momenta between the pair above 400 megaelectronvolts per c (c, speed of light in vacuum). As the relative momentum between two nucleons increases and their separation thereby decreases, we observe a transition from a spin-dependent tensor force to a predominantly spin-independent scalar force. These results demonstrate the usefulness of using such measurements to study the nuclear interaction at short distances and also support the use of point-like nucleon models with two- and three-body effective interactions to describe nuclear systems up to densities several times higher than the central density of the nucleus.


  
In situ NMR metrology reveals reaction mechanisms in redox flow batteries 期刊论文
NATURE, 2020, 579 (7798) : 224-+
作者:  Ma, Jianfei;  You, Xin;  Sun, Shan;  Wang, Xiaoxiao;  Qin, Song;  Sui, Sen-Fang
收藏  |  浏览/下载:11/0  |  提交时间:2020/07/03

Large-scale energy storage is becoming increasingly critical to balancing renewable energy production and consumption(1). Organic redox flow batteries, made from inexpensive and sustainable redox-active materials, are promising storage technologies that are cheaper and less environmentally hazardous than vanadium-based batteries, but they have shorter lifetimes and lower energy density(2,3). Thus, fundamental insight at the molecular level is required to improve performance(4,5). Here we report two in situ nuclear magnetic resonance (NMR) methods of studying redox flow batteries, which are applied to two redox-active electrolytes: 2,6-dihydroxyanthraquinone (DHAQ) and 4,4 '  -((9,10-anthraquinone-2,6-diyl)dioxy) dibutyrate (DBEAQ). In the first method, we monitor the changes in the H-1 NMR shift of the liquid electrolyte as it flows out of the electrochemical cell. In the second method, we observe the changes that occur simultaneously in the positive and negative electrodes in the full electrochemical cell. Using the bulk magnetization changes (observed via the H-1 NMR shift of the water resonance) and the line broadening of the H-1 shifts of the quinone resonances as a function of the state of charge, we measure the potential differences of the two single-electron couples, identify and quantify the rate of electron transfer between the reduced and oxidized species, and determine the extent of electron delocalization of the unpaired spins over the radical anions. These NMR techniques enable electrolyte decomposition and battery self-discharge to be explored in real time, and show that DHAQ is decomposed electrochemically via a reaction that can be minimized by limiting the voltage used on charging. We foresee applications of these NMR methods in understanding a wide range of redox processes in flow and other electrochemical systems.


  
Power generation from ambient humidity using protein nanowires 期刊论文
NATURE, 2020, 578 (7796) : 550-+
作者:  Luong, Duy X.;  Bets, Ksenia V.;  Algozeeb, Wala Ali;  Stanford, Michael G.;  Kittrell, Carter;  Chen, Weiyin;  Salvatierra, Rodrigo V.;  Ren, Muqing;  McHugh, Emily A.;  Advincula, Paul A.;  Wang, Zhe;  Bhatt, Mahesh;  Guo, Hua;  Mancevski, Vladimir;  Shahsavari, Rouzbeh;  Yakobson, Boris I.;  Tour, James M.
收藏  |  浏览/下载:85/0  |  提交时间:2020/07/03

Harvesting energy from the environment offers the promise of clean power for self-sustained systems(1,2). Known technologies-such as solar cells, thermoelectric devices and mechanical generators-have specific environmental requirements that restrict where they can be deployed and limit their potential for continuous energy production(3-5). The ubiquity of atmospheric moisture offers an alternative. However, existing moisture-based energy-harvesting technologies can produce only intermittent, brief (shorter than 50 seconds) bursts of power in the ambient environment, owing to the lack of a sustained conversion mechanism(6-12). Here we show that thin-film devices made from nanometre-scale protein wires harvested from the microbe Geobacter sulfurreducens can generate continuous electric power in the ambient environment. The devices produce a sustained voltage of around 0.5 volts across a 7-micrometre-thick film, with a current density of around 17 microamperes per square centimetre. We find the driving force behind this energy generation to be a self-maintained moisture gradient that forms within the film when the film is exposed to the humidity that is naturally present in air. Connecting several devices linearly scales up the voltage and current to power electronics. Our results demonstrate the feasibility of a continuous energy-harvesting strategy that is less restricted by location or environmental conditions than other sustainable approaches.


A new type of energy-harvesting device, based on protein nanowires from the microbe Geobacter sulforreducens, can generate a sustained power output by producing a moisture gradient across the nanowire film using natural humidity.


  
Classification with a disordered dopantatom network in silicon 期刊论文
NATURE, 2020, 577 (7790) : 341-+
作者:  Vagnozzi, Ronald J.;  Maillet, Marjorie;  Sargent, Michelle A.;  Khalil, Hadi;  Johansen, Anne Katrine Z.;  Schwanekamp, Jennifer A.;  York, Allen J.;  Huang, Vincent;  Nahrendorf, Matthias;  Sadayappan, Sakthivel;  Molkentin, Jeffery D.
收藏  |  浏览/下载:23/0  |  提交时间:2020/07/03

Classification is an important task at which both biological and artificial neural networks excel(1,2). In machine learning, nonlinear projection into a high-dimensional feature space can make data linearly separable(3,4), simplifying the classification of complex features. Such nonlinear projections are computationally expensive in conventional computers. A promising approach is to exploit physical materials systems that perform this nonlinear projection intrinsically, because of their high computational density(5), inherent parallelism and energy efficiency(6,7). However, existing approaches either rely on the systems'  time dynamics, which requires sequential data processing and therefore hinders parallel computation(5,6,8), or employ large materials systems that are difficult to scale up(7). Here we use a parallel, nanoscale approach inspired by filters in the brain(1) and artificial neural networks(2) to perform nonlinear classification and feature extraction. We exploit the nonlinearity of hopping conduction(9-11) through an electrically tunable network of boron dopant atoms in silicon, reconfiguring the network through artificial evolution to realize different computational functions. We first solve the canonical two-input binary classification problem, realizing all Boolean logic gates(12) up to room temperature, demonstrating nonlinear classification with the nanomaterial system. We then evolve our dopant network to realize feature filters(2) that can perform four-input binary classification on the Modified National Institute of Standards and Technology handwritten digit database. Implementation of our material-based filters substantially improves the classification accuracy over that of a linear classifier directly applied to the original data(13). Our results establish a paradigm of silicon-based electronics for smallfootprint and energy-efficient computation(14).