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Despite the maximized metal dispersion offered by single-atom catalysts, further improvement of intrinsic activity can be hindered by the lack of neighboring metal atoms in these systems. Here we report the use of isolated Pt 1 atoms on ceria as “seeds” to develop a Pt-O-Pt ensemble, which is well-represented by a Pt 8 O 14 model cluster that retains 100% metal dispersion. The Pt atom in the ensemble is 100–1000 times more active than their single-atom Pt 1 /CeO 2 parent in catalyzing the low-temperature CO oxidation under oxygen-rich conditions. Rather than the Pt-O-Ce interfacial catalysis, the stable catalytic unit is the Pt-O-Pt site itself without participation of oxygen from the 10–30 nm-size ceria support. Similar Pt-O-Pt sites can be built on various ceria and even alumina, distinguishable by facile activation of oxygen through the paired Pt-O-Pt atoms. Extending this design to other reaction systems is a likely outcome of the findings reported here. Single-atom metal catalysts offer maximized material efficiency, but there is large room to improve the intrinsic activity per metal atom for many reactions. Here, the authors demonstrate that the solution for CO oxidation is to tackle the issue of lacking neighboring Pt atoms in the single-atom Pt1/CeO2 system.

It is highly profitable to transform glycerol – the main by-product from biodiesel production to high value-added chemicals. In this work, we develop a photoelectrochemical system based on nanoporous BiVO 4 for selective oxidation of glycerol to 1,3-dihydroxyacetone – one of the most valuable derivatives of glycerol. Under AM 1.5G front illumination (100 mW cm −2 ) in an acidic medium (pH = 2) without adscititious oxidant, the nanoporous BiVO 4 photoanode achieves a glycerol oxidation photocurrent density of 3.7 mA cm −2 at a potential of 1.2 V versus RHE with 51% 1,3-dihydroxyacetone selectivity, equivalent to a production rate of 200 mmol of 1,3-dihydroxyacetone per m 2 of illumination area in one hour. The selective conversion of inexpensive precursors to high-value chemicals presents valuable academic and industrial consequences. Here, the authors show bismuth vanadate photoanodes to utilize light and photoelectrochemically oxidize glycerol selectively to valuable industrial products.

هي أكبر فضاء معماري موجود، وهي بحجمها واتساع رقعتها، تدل على هيمنة الإمبراطورية على العالم، وأيا كانت قوة ونفوذ المرء فإنه بمجرد دخوله المدينة المحرمة، يجد نفسه أشبه بحبة رمل في صحراء واسعة، لا أهمية له، وعليه أن يخضع لهيمنة ذلك الفضاء، وأن يخضع سيره وجلوسه لقوانين ذلك الفضاء ؛ أما بالنسبة للإمبراطور فالوضع مختلف، فهو وحده سيد المكان، فهو لا يخضع في ظهوره وفي أي مناسبة لأي قيد أو شرط، في جلوسه على عرش التنين في قاعة الانسجام الأسمى، يصبح مركز الكون، ولا سيطرة للفضاء الواسع عليه. عندما يفقد الناس ذواتهم في القصور الضخمة ففي ذلك استعارة لسلطة الإمبراطور على رعاياه المبنية على أساس معماري حينما يمر الإمبراطور في القصر يفرض هيمنته على الجميع.

Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-training and fine-tuning process. In this work, we show that fault-tolerant quantum computing could possibly provide provably efficient resolutions for generic (stochastic) gradient descent algorithms, scaling as O ( T 2 × polylog ( n ) ) , where n is the size of the models and T is the number of iterations in the training, as long as the models are both sufficiently dissipative and sparse, with small learning rates. Based on earlier efficient quantum algorithms for dissipative differential equations, we find and prove that similar algorithms work for (stochastic) gradient descent, the primary algorithm for machine learning. In practice, we benchmark instances of large machine learning models from 7 million to 103 million parameters. We find that, in the context of sparse training, a quantum enhancement is possible at the early stage of learning after model pruning, motivating a sparse parameter download and re-upload scheme. Our work shows solidly that fault-tolerant quantum algorithms could potentially contribute to most state-of-the-art, large-scale machine-learning problems. It is still unclear whether and how quantum computing might prove useful in solving known large-scale classical machine learning problems. Here, the authors show that variants of known quantum algorithms for solving differential equations can provide an advantage in solving some instances of stochastic gradient descent dynamics.

A View from the Stars is a collection of short fiction and nonfiction pieces from Cixin Liu, the New York Times bestselling author of The Three-Body Problem. Included are essays and interviews that shed light on Liu's experiences as a reader, writer, and lover of science fiction throughout his life, as well as short fiction that gives glimpses into the evolution of his imaginative voice over the years\"--Back cover.

Wuhan was the first epicentre of COVID-19 in the world, accounting for 80% of cases in China during the first wave. We aimed to assess household transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and risk factors associated with infectivity and susceptibility to infection in Wuhan. This retrospective cohort study included the households of all laboratory-confirmed or clinically confirmed COVID-19 cases and laboratory-confirmed asymptomatic SARS-CoV-2 infections identified by the Wuhan Center for Disease Control and Prevention between Dec 2, 2019, and April 18, 2020. We defined households as groups of family members and close relatives who did not necessarily live at the same address and considered households that shared common contacts as epidemiologically linked. We used a statistical transmission model to estimate household secondary attack rates and to quantify risk factors associated with infectivity and susceptibility to infection, accounting for individual-level exposure history. We assessed how intervention policies affected the household reproductive number, defined as the mean number of household contacts a case can infect. 27 101 households with 29 578 primary cases and 57 581 household contacts were identified. The secondary attack rate estimated with the transmission model was 15·6% (95% CI 15·2–16·0), assuming a mean incubation period of 5 days and a maximum infectious period of 22 days. Individuals aged 60 years or older were at a higher risk of infection with SARS-CoV-2 than all other age groups. Infants aged 0–1 years were significantly more likely to be infected than children aged 2–5 years (odds ratio [OR] 2·20, 95% CI 1·40–3·44) and children aged 6–12 years (1·53, 1·01–2·34). Given the same exposure time, children and adolescents younger than 20 years of age were more likely to infect others than were adults aged 60 years or older (1·58, 1·28–1·95). Asymptomatic individuals were much less likely to infect others than were symptomatic cases (0·21, 0·14–0·31). Symptomatic cases were more likely to infect others before symptom onset than after (1·42, 1·30–1·55). After mass isolation of cases, quarantine of household contacts, and restriction of movement policies were implemented, household reproductive numbers declined by 52% among primary cases (from 0·25 [95% CI 0·24–0·26] to 0·12 [0·10–0·13]) and by 63% among secondary cases (from 0·17 [0·16–0·18] to 0·063 [0·057–0·070]). Within households, children and adolescents were less susceptible to SARS-CoV-2 infection but were more infectious than older individuals. Presymptomatic cases were more infectious and individuals with asymptomatic infection less infectious than symptomatic cases. These findings have implications for devising interventions for blocking household transmission of SARS-CoV-2, such as timely vaccination of eligible children once resources become available. National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities, US National Institutes of Health, and US National Science Foundation.

Differentiable programming is a fresh programming paradigm which composes parameterized algorithmic components and optimizes them using gradient search. The concept emerges from deep learning but is not limited to training neural networks. We present the theory and practice of programming tensor network algorithms in a fully differentiable way. By formulating the tensor network algorithm as a computation graph, one can compute higher-order derivatives of the program accurately and efficiently using automatic differentiation. We present essential techniques to differentiate through the tensor networks contraction algorithms, including numerical stable differentiation for tensor decompositions and efficient backpropagation through fixed-point iterations. As a demonstration, we compute the specific heat of the Ising model directly by taking the second-order derivative of the free energy obtained in the tensor renormalization group calculation. Next, we perform gradient-based variational optimization of infinite projected entangled pair states for the quantum antiferromagnetic Heisenberg model and obtain state-of-the-art variational energy and magnetization with moderate efforts. Differentiable programming removes laborious human efforts in deriving and implementing analytical gradients for tensor network programs, which opens the door to more innovations in tensor network algorithms and applications.

The current industrial ammonia synthesis relies on Haber–Bosch process that is initiated by the dissociative mechanism, in which the adsorbed N 2 dissociates directly, and thus is limited by Brønsted–Evans–Polanyi (BEP) relation. Here we propose a new strategy that an anchored Fe 3 cluster on the θ-Al 2 O 3 (010) surface as a heterogeneous catalyst for ammonia synthesis from first-principles theoretical study and microkinetic analysis. We have studied the whole catalytic mechanism for conversion of N 2 to NH 3 on Fe 3 /θ-Al 2 O 3 (010), and find that an associative mechanism, in which the adsorbed N 2 is first hydrogenated to NNH, dominates over the dissociative mechanism, which we attribute to the large spin polarization, low oxidation state of iron, and multi-step redox capability of Fe 3 cluster. The associative mechanism liberates the turnover frequency (TOF) for ammonia production from the limitation due to the BEP relation, and the calculated TOF on Fe 3 /θ-Al 2 O 3 (010) is comparable to Ru B5 site. The current industrial ammonia synthesis relies on the Haber-Bosch process that is limited by the Brønsted–Evans–Polanyi relation. Here, the authors propose a new strategy that an anchored Fe 3 on θ-Al 2 O 3 (010) surface serves as a heterogeneous single cluster catalyst for ammonia synthesis from first-principles calculations and microkinetic analysis.