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Potential for large-scale CO2 removal via enhanced rock weathering with croplands 期刊论文
NATURE, 2020, 583 (7815) : 242-+
作者:  David J. Beerling;  Euripides P. Kantzas;  Mark R. Lomas;  Peter Wade;  Rafael M. Eufrasio;  Phil Renforth;  Binoy Sarkar;  M. Grace Andrews;  Rachael H. James;  Christopher R. Pearce;  Jean-Francois Mercure;  Hector Pollitt;  Philip B. Holden;  Neil R. Edwards;  Madhu Khanna;  Lenny Koh;  Shaun Quegan;  Nick F. Pidgeon;  Ivan A. Janssens;  James Hansen;  Steven A. Banwart
收藏  |  浏览/下载:18/0  |  提交时间:2020/07/14

Enhanced silicate rock weathering (ERW), deployable with croplands, has potential use for atmospheric carbon dioxide (CO2) removal (CDR), which is now necessary to mitigate anthropogenic climate change(1). ERW also has possible co-benefits for improved food and soil security, and reduced ocean acidification(2-4). Here we use an integrated performance modelling approach to make an initial techno-economic assessment for 2050, quantifying how CDR potential and costs vary among nations in relation to business-as-usual energy policies and policies consistent with limiting future warming to 2 degrees Celsius(5). China, India, the USA and Brazil have great potential to help achieve average global CDR goals of 0.5 to 2gigatonnes of carbon dioxide (CO2) per year with extraction costs of approximately US$80-180 per tonne of CO2. These goals and costs are robust, regardless of future energy policies. Deployment within existing croplands offers opportunities to align agriculture and climate policy. However, success will depend upon overcoming political and social inertia to develop regulatory and incentive frameworks. We discuss the challenges and opportunities of ERW deployment, including the potential for excess industrial silicate materials (basalt mine overburden, concrete, and iron and steel slag) to obviate the need for new mining, as well as uncertainties in soil weathering rates and land-ocean transfer of weathered products.


  
Molecular tuning of CO2-to-ethylene conversion 期刊论文
NATURE, 2020, 577 (7791) : 509-+
作者:  Li, Fengwang;  39;Brien, Colin P.
收藏  |  浏览/下载:13/0  |  提交时间:2020/07/03

The electrocatalytic reduction of carbon dioxide, powered by renewable electricity, to produce valuable fuels and feedstocks provides a sustainable and carbon-neutral approach to the storage of energy produced by intermittent renewable sources(1). However, the highly selective generation of economically desirable products such as ethylene from the carbon dioxide reduction reaction (CO2RR) remains a challenge(2). Tuning the stabilities of intermediates to favour a desired reaction pathway can improve selectivity(3-5), and this has recently been explored for the reaction on copper by controlling morphology(6), grain boundaries(7), facets(8), oxidation state(9) and dopants(10). Unfortunately, the Faradaic efficiency for ethylene is still low in neutral media (60 per cent at a partial current density of 7 milliamperes per square centimetre in the best catalyst reported so far(9)), resulting in a low energy efficiency. Here we present a molecular tuning strategy-the functionalization of the surface of electrocatalysts with organic molecules-that stabilizes intermediates for more selective CO2RR to ethylene. Using electrochemical, operando/in situ spectroscopic and computational studies, we investigate the influence of a library of molecules, derived by electro-dimerization of arylpyridiniums(11), adsorbed on copper. We find that the adhered molecules improve the stabilization of an '  atop-bound'  CO intermediate (that is, an intermediate bound to a single copper atom), thereby favouring further reduction to ethylene. As a result of this strategy, we report the CO2RR to ethylene with a Faradaic efficiency of 72 per cent at a partial current density of 230 milliamperes per square centimetre in a liquid-electrolyte flow cell in a neutral medium. We report stable ethylene electrosynthesis for 190 hours in a system based on a membrane-electrode assembly that provides a full-cell energy efficiency of 20 per cent. We anticipate that this may be generalized to enable molecular strategies to complement heterogeneous catalysts by stabilizing intermediates through local molecular tuning.


Electrocatalytic reduction of CO2 over copper can be made highly selective by '  tuning'  the copper surface with adsorbed organic molecules to stabilize intermediates for carbon-based fuels such as ethylene


  
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:89/0  |  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.


  
Taking stock of national climate policies to evaluate implementation of the Paris Agreement 期刊论文
NATURE COMMUNICATIONS, 2020, 11 (1)
作者:  Roelfsema, Mark;  van Soest, Heleen L.;  Harmsen, Mathijs;  van Vuuren, Detlef P.;  Bertram, Christoph;  den Elzen, Michel;  Hoehne, Niklas;  Iacobuta, Gabriela;  Krey, Volker;  Kriegler, Elmar;  Luderer, Gunnar;  Riahi, Keywan;  Ueckerdt, Falko;  Despres, Jacques;  Drouet, Laurent;  Emmerling, Johannes;  Frank, Stefan;  Fricko, Oliver;  Gidden, Matthew;  Humpenoeder, Florian;  Huppmann, Daniel;  Fujimori, Shinichiro;  Fragkiadakis, Kostas;  Gi, Keii;  Keramidas, Kimon;  Koberle, Alexandre C.;  Reis, Lara Aleluia;  Rochedo, Pedro;  Schaeffer, Roberto;  Oshiro, Ken;  Vrontisi, Zoi;  Chen, Wenying;  Iyer, Gokul C.;  Edmonds, Jae;  Kannavou, Maria;  Jiang, Kejun;  Mathur, Ritu;  Safonoy, George;  Vishwanathan, Saritha Sudharmma
收藏  |  浏览/下载:20/0  |  提交时间:2020/05/13
Assessing the impact of ETS trading profit on emission abatements based on firm-level transactions 期刊论文
NATURE COMMUNICATIONS, 2020, 11 (1)
作者:  Guo, Jianfeng;  Gu, Fu;  Liu, Yinpeng;  Liang, Xi;  Mo, Jianlei;  Fan, Ying
收藏  |  浏览/下载:8/0  |  提交时间:2020/05/13
Ultra-high open-circuit voltage of tin perovskite solar cells via an electron transporting layer design 期刊论文
NATURE COMMUNICATIONS, 2020, 11 (1)
作者:  Jiang, Xianyuan;  Wang, Fei;  Wei, Qi;  Li, Hansheng;  Shang, Yuequn;  Zhou, Wenjia;  Wang, Cheng;  Cheng, Peihong;  Chen, Qi;  Chen, Liwei;  Ning, Zhijun
收藏  |  浏览/下载:11/0  |  提交时间:2020/05/13
Nitrifier adaptation to low energy flux controls inventory of reduced nitrogen in the dark ocean 期刊论文
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (9) : 4823-4830
作者:  Zhang, Yao;  Qin, Wei;  Hou, Lei;  Zakem, Emily J.;  Wan, Xianhui;  Zhao, Zihao;  Liu, Li;  Hunt, Kristopher A.;  Jiao, Nianzhi;  Kao, Shuh-Ji;  Tang, Kai;  Xie, Xiabing;  Shen, Jiaming;  Li, Yufang;  Chen, Mingming;  Dai, Xiaofeng;  Liu, Chang;  Deng, Wenchao;  Dai, Minhan;  Ingalls, Anitra E.;  Stahl, David A.;  Herndl, Gerhard J.
收藏  |  浏览/下载:14/0  |  提交时间:2020/05/13
nitrification  dark ocean  nitrogen flux  carbon fixation  homeostasis  
Attosecond pulse shaping using a seeded free-electron laser 期刊论文
NATURE, 2020
作者:  Achar, Yathish Jagadheesh;  Adhil, Mohamood;  Choudhary, Ramveer;  Gilbert, Nick;  Foiani, Marco
收藏  |  浏览/下载:9/0  |  提交时间:2020/07/03

Generation of intense attosecond waveforms with independently controllable amplitude and phase is performed by using a seeded free-electron laser.


Attosecond pulses are central to the investigation of valence- and core-electron dynamics on their natural timescales(1-3). The reproducible generation and characterization of attosecond waveforms has been demonstrated so far only through the process of high-order harmonic generation(4-7). Several methods for shaping attosecond waveforms have been proposed, including the use of metallic filters(8,9), multilayer mirrors(10) and manipulation of the driving field(11). However, none of these approaches allows the flexible manipulation of the temporal characteristics of the attosecond waveforms, and they suffer from the low conversion efficiency of the high-order harmonic generation process. Free-electron lasers, by contrast, deliver femtosecond, extreme-ultraviolet and X-ray pulses with energies ranging from tens of microjoules to a few millijoules(12,13). Recent experiments have shown that they can generate subfemtosecond spikes, but with temporal characteristics that change shot-to-shot(14-16). Here we report reproducible generation of high-energy (microjoule level) attosecond waveforms using a seeded free-electron laser(17). We demonstrate amplitude and phase manipulation of the harmonic components of an attosecond pulse train in combination with an approach for its temporal reconstruction. The results presented here open the way to performing attosecond time-resolved experiments with free-electron lasers.


  
On-device lead sequestration for perovskite solar cells 期刊论文
NATURE, 2020, 578 (7796) : 555-+
作者:  Fruchart, Michel;  Zhou, Yujie;  Vitelli, Vincenzo
收藏  |  浏览/下载:31/0  |  提交时间:2020/07/03

Perovskite solar cells, as an emerging high-efficiency and low-cost photovoltaic technology(1-6), face obstacles on their way towards commercialization. Substantial improvements have been made to device stability(7-10), but potential issues with lead toxicity and leaching from devices remain relatively unexplored(11-16). The potential for lead leakage could be perceived as an environmental and public health risk when using perovskite solar cells in building-integrated photovoltaics(17-23). Here we present a chemical approach for on-device sequestration of more than 96 per cent of lead leakage caused by severe device damage. A coating of lead-absorbing material is applied to the front and back sides of the device stack. On the glass side of the front transparent conducting electrode, we use a transparent lead-absorbing molecular film containing phosphonic acid groups that bind strongly to lead. On the back (metal) electrode side, we place a polymer film blended with lead-chelating agents between the metal electrode and a standard photovoltaic packing film. The lead-absorbing films on both sides swell to absorb the lead, rather than dissolve, when subjected to water soaking, thus retaining structural integrity for easy collection of lead after damage.


Using lead-absorbing materials to coat the front and back of perovskite solar cells can prevent lead leaching from damaged devices, without affecting the device performance or long-term operation stability.


  
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:24/0  |  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).