scholarly journals Building high accuracy emulators for scientific simulations with deep neural architecture search

2021 ◽  
Author(s):  
Muhammad Firmansyah Kasim ◽  
D. Watson-Parris ◽  
L. Deaconu ◽  
S. Oliver ◽  
P. Hatfield ◽  
...  
Keyword(s):  
Large Scale ◽  
Scientific Discovery ◽  
Fusion Energy ◽  
High Energy ◽  
Training Data ◽  
High Energy Density ◽  
Neural Architecture ◽  
Large Scale Data ◽  
Scientific Simulations ◽  
Computational Discovery

Abstract Computer simulations are invaluable tools for scientific discovery. However, accurate simulations are often slow to execute, which limits their applicability to extensive parameter exploration, large-scale data analysis, and uncertainty quantification. A promising route to accelerate simulations by building fast emulators with machine learning requires large training datasets, which can be prohibitively expensive to obtain with slow simulations. Here we present a method based on neural architecture search to build accurate emulators even with a limited number of training data. The method successfully emulates simulations in 10 scientific cases including astrophysics, climate sci-ence, biogeochemistry, high energy density physics, fusion energy, and seismology, using the same super-architecture, algorithm, and hyperparameters. Our approach also inherently provides emulator uncertainty estimation, adding further confidence in their use. We anticipate this work will accelerate research involving expensive simulations, allow more extensive parameters exploration, and enable new, previously unfeasible computational discovery.

scholarly journals From natural to artificial photosynthesis

2013 ◽  
Vol 10 (81) ◽  
pp. 20120984 ◽  
Author(s):  
James Barber ◽  
Phong D. Tran
Keyword(s):  
Solar Energy ◽  
Large Scale ◽  
Nuclear Fusion ◽  
Fusion Energy ◽  
High Energy ◽  
Primary Energy ◽  
Energy Resources ◽  
High Energy Density ◽  
Chemical Bonds ◽  
Natural Photosynthesis

Demand for energy is projected to increase at least twofold by mid-century relative to the present global consumption because of predicted population and economic growth. This demand could be met, in principle, from fossil energy resources, particularly coal. However, the cumulative nature of carbon dioxide (CO 2 ) emissions demands that stabilizing the atmospheric CO 2 levels to just twice their pre-anthropogenic values by mid-century will be extremely challenging, requiring invention, development and deployment of schemes for carbon-neutral energy production on a scale commensurate with, or larger than, the entire present-day energy supply from all sources combined. Among renewable and exploitable energy resources, nuclear fusion energy or solar energy are by far the largest. However, in both cases, technological breakthroughs are required with nuclear fusion being very difficult, if not impossible on the scale required. On the other hand, 1 h of sunlight falling on our planet is equivalent to all the energy consumed by humans in an entire year. If solar energy is to be a major primary energy source, then it must be stored and despatched on demand to the end user. An especially attractive approach is to store solar energy in the form of chemical bonds as occurs in natural photosynthesis. However, a technology is needed which has a year-round average conversion efficiency significantly higher than currently available by natural photosynthesis so as to reduce land-area requirements and to be independent of food production. Therefore, the scientific challenge is to construct an ‘artificial leaf’ able to efficiently capture and convert solar energy and then store it in the form of chemical bonds of a high-energy density fuel such as hydrogen while at the same time producing oxygen from water. Realistically, the efficiency target for such a technology must be 10 per cent or better. Here, we review the molecular details of the energy capturing reactions of natural photosynthesis, particularly the water-splitting reaction of photosystem II and the hydrogen-generating reaction of hydrogenases. We then follow on to describe how these two reactions are being mimicked in physico-chemical-based catalytic or electrocatalytic systems with the challenge of creating a large-scale robust and efficient artificial leaf technology.

Organic solvent-assisted free-standing Li2MnO3·LiNi1/3Co1/3Mn1/3O2 on 3D graphene as a high energy density cathode

2015 ◽  
Vol 51 (91) ◽  
pp. 16381-16384 ◽  
Author(s):  
Yuelong Xin ◽  
Liya Qi ◽  
Yiwei Zhang ◽  
Zicheng Zuo ◽  
Henghui Zhou ◽  
...  
Keyword(s):  
Energy Density ◽  
Organic Solvent ◽  
Freeze Drying ◽  
Large Scale ◽  
High Energy ◽  
High Energy Density ◽  
Free Standing ◽  
3D Graphene ◽  
Active Particles

A novel organic solvent-assisted freeze-drying pathway, which can effectively protect and uniformly distribute active particles, is developed to fabricate a free-standing Li2MnO3·LiNi1/3Co1/3Mn1/3O2 (LR)/rGO electrode on a large scale.

High energy density aqueous zinc–benzoquinone batteries enabled by carbon cloth with multiple anchoring effects

2021 ◽  
Author(s):  
Zhiqiang Luo ◽  
Silin Zheng ◽  
Shuo Zhao ◽  
Xin Jiao ◽  
Zongshuai Gong ◽  
...  
Keyword(s):  
Energy Storage ◽  
Energy Density ◽  
Porous Carbon ◽  
Large Scale ◽  
High Energy ◽  
High Energy Density ◽  
Carbon Cloth ◽  
Anchoring Effects ◽  
High Theoretical Capacity ◽  
Energy Storage Applications

Benzoquinone with high theoretical capacity is anchored on N-plasma engraved porous carbon as a desirable cathode for rechargeable aqueous Zn-ion batteries. Such batteries display tremendous potential in large-scale energy storage applications.

scholarly journals Nitrogen-enriched graphene framework from a large-scale magnesiothermic conversion of CO2 with synergistic kinetics for high-power lithium-ion capacitors

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Chen Li ◽  
Xiong Zhang ◽  
Kai Wang ◽  
Xianzhong Sun ◽  
Yanan Xu ◽  
...  
Keyword(s):  
Energy Density ◽  
High Power ◽  
Power Output ◽  
Large Scale ◽  
Electrode Materials ◽  
Lithium Ion ◽  
High Energy ◽  
High Energy Density ◽  
Chemical Doping ◽  
Lithium Ion Capacitor

AbstractLithium-ion capacitors are envisaged as promising energy-storage devices to simultaneously achieve a large energy density and high-power output at quick charge and discharge rates. However, the mismatched kinetics between capacitive cathodes and faradaic anodes still hinder their practical application for high-power purposes. To tackle this problem, the electron and ion transport of both electrodes should be substantially improved by targeted structural design and controllable chemical doping. Herein, nitrogen-enriched graphene frameworks are prepared via a large-scale and ultrafast magnesiothermic combustion synthesis using CO2 and melamine as precursors, which exhibit a crosslinked porous structure, abundant functional groups and high electrical conductivity (10524 S m−1). The material essentially delivers upgraded kinetics due to enhanced ion diffusion and electron transport. Excellent capacities of 1361 mA h g−1 and 827 mA h g−1 can be achieved at current densities of 0.1 A g−1 and 3 A g−1, respectively, demonstrating its outstanding lithium storage performance at both low and high rates. Moreover, the lithium-ion capacitor based on these nitrogen-enriched graphene frameworks displays a high energy density of 151 Wh kg−1, and still retains 86 Wh kg−1 even at an ultrahigh power output of 49 kW kg−1. This study reveals an effective pathway to achieve synergistic kinetics in carbon electrode materials for achieving high-power lithium-ion capacitors.

scholarly journals LQR control of interleaved double dual boost converter for electrical vehicles and renewable energy conversion

2019 ◽  
Vol 16 (3) ◽  
pp. 1240
Author(s):  
J. S. V. Siva Kumar ◽  
P. Mallikarjunarao
Keyword(s):  
Fuel Cell ◽  
Automobile Industry ◽  
Large Scale ◽  
Petroleum Products ◽  
High Energy ◽  
High Energy Density ◽  
Control Technique ◽  
Boost Converters ◽  
Lqr Control ◽  
Electrical Vehicles

<p>The automobile industry is one of the major industries that are having its new innovations at a great pace according to the requirements of the day-to-day life. Due to the usage of conventional vehicles on a large scale which usually use petroleum products as fuel, is leading to a vast environmental effect, mainly due to the emission of greenhouse gases. So in order to reduce the ill effects of the greenhouse gas emissions great efforts are being put in   manufacturing of electrical vehicles. Among the currently available greenhouse technologies the fuel cell provides high energy density in spite of its expenses. So, in this aspect a required mechanism has to be adopted to make it energy efficient and affordable. In order to overcome the drawback of fuel cell i.e. low output voltage, the boost converters are to be used and to be more precise Non-isolated Interleaved Double Dual Boost (IDDB) converters are recommended which makes it efficient and also the reduction of overall vehicle weight can be achieved. The LQR control technique is applied in this work to make the transient response of the fuel cell powered IDDB converter for various load conditions effective. The verification of results is done with simulation techniques using MATLAB/Simulink.</p>

scholarly journals Discovering Latent Class Labels for Multi-Label Learning

2020 ◽  
Author(s):  
Jun Huang ◽  
Linchuan Xu ◽  
Jing Wang ◽  
Lei Feng ◽  
Kenji Yamanishi
Keyword(s):  
Large Scale ◽  
Latent Class ◽  
Training Data ◽  
Data Sets ◽  
Robust Learning ◽  
Large Scale Data ◽  
Novel Approach ◽  
Fixed Set ◽  
Class Labels ◽  
Scale Data

Existing multi-label learning (MLL) approaches mainly assume all the labels are observed and construct classification models with a fixed set of target labels (known labels). However, in some real applications, multiple latent labels may exist outside this set and hide in the data, especially for large-scale data sets. Discovering and exploring the latent labels hidden in the data may not only find interesting knowledge but also help us to build a more robust learning model. In this paper, a novel approach named DLCL (i.e., Discovering Latent Class Labels for MLL) is proposed which can not only discover the latent labels in the training data but also predict new instances with the latent and known labels simultaneously. Extensive experiments show a competitive performance of DLCL against other state-of-the-art MLL approaches.

Manganese phosphoxide/Ni5P4 hybrids as an anode material for high energy density and rate potassium-ion storage

2021 ◽  
Author(s):  
Sen Yang ◽  
Ting Li ◽  
Yiwei Tan
Keyword(s):  
Energy Density ◽  
Lithium Ion Batteries ◽  
Large Scale ◽  
Low Cost ◽  
Lithium Ion ◽  
High Energy ◽  
Potassium Ion ◽  
High Energy Density ◽  
Active Materials ◽  
Ion Storage

Potassium-ion batteries (PIBs) that serve as low-cost and large-scale secondary batteries are regarded as promising alternatives and supplement to lithium-ion batteries. Hybrid active materials can be featured with the synergistic...

Interfacial electron modulation of MoS2/black phosphorus heterostructure toward high-rate and high-energy density half/full sodium-ion batteries

2021 ◽  
Author(s):  
Chenrui Zhang ◽  
Tingting Liang ◽  
Huilong Dong ◽  
Junjun Li ◽  
Junyu Shen ◽  
...  
Keyword(s):  
Energy Density ◽  
Volume Expansion ◽  
Anode Materials ◽  
Large Scale ◽  
Electrochemical Reaction ◽  
High Energy ◽  
Sodium Ion ◽  
High Rate ◽  
High Energy Density ◽  
Sodium Ion Batteries

Sodium-ion batteries (SIBs) have been considered as promising candidates for large-scale energy storage. However, viable anode materials still suffer from sluggish electrochemical reaction kinetics and huge volume expansion during cycling,...

scholarly journals Sir John Edward Sulston CH. 27 March 1942—6 March 2018

2019 ◽  
Vol 67 ◽  
pp. 421-447
Author(s):  
Robert H. Waterston ◽  
Georgina Ferry
Keyword(s):  
Cell Fate ◽  
Large Scale ◽  
Wellcome Trust Sanger Institute ◽  
Scientific Discovery ◽  
Cell Lineage ◽  
Genome Project ◽  
Biomedical Ethics ◽  
Sanger Institute ◽  
Large Scale Data ◽  
Founding Director

In 2002 Sir John Sulston shared the Nobel Prize for Physiology or Medicine for his contribution to understanding the genetic control of cell fate during the development of the roundworm Caenorhabditis elegans . However, it was his position as one of the leaders of the international and publicly funded Human Genome Project that brought him to public prominence. Both his work on the worm cell lineage and his later commitment to genome sequencing as founding director of the Wellcome Trust Sanger Institute stemmed from his conviction that investing in large-scale data collection would have long-term benefits for future scientific discovery. He was a key figure in promoting the principle, now widely accepted, that genomic data should be universally and freely shared. After retiring from his post at the Sanger Institute he engaged with organizations with interests in biomedical ethics and global equality. He was a loyal and supportive colleague to many, delighting in the international collegiality of the ‘worm community’, of which he was a founding member.

Ionic liquid electrolytes supporting high energy density in sodium-ion batteries based on sodium vanadium phosphate composites

2018 ◽  
Vol 54 (28) ◽  
pp. 3500-3503 ◽  
Author(s):  
C. V. Manohar ◽  
Tiago Correia Mendes ◽  
Mega Kar ◽  
Dabin wang ◽  
Changlong Xiao ◽  
...  
Keyword(s):  
Energy Storage ◽  
Large Scale ◽  
Cost Effective ◽  
High Energy ◽  
Sodium Ion ◽  
High Energy Density ◽  
Sodium Ion Batteries ◽  
Vanadium Phosphate ◽  
Energy Storage Devices ◽  
Storage Devices

Sodium ion batteries (SIBs) are widely considered as alternative, sustainable, and cost-effective energy storage devices for large-scale energy storage applications.

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