Institution
Delft University of Technology
Education•Delft, Zuid-Holland, Netherlands•
About: Delft University of Technology is a education organization based out in Delft, Zuid-Holland, Netherlands. It is known for research contribution in the topics: Computer science & Catalysis. The organization has 37681 authors who have published 94404 publications receiving 2741710 citations. The organization is also known as: TU-Delft & Technische Hogeschool Delft.
Papers published on a yearly basis
Papers
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TL;DR: In this article, a new and simple mechanism of kerogen formation is proposed, which clarifies the interrelationships between extant biomass, kerogen, and fossil fuels, and it is shown that recognizable entities in kerogen and their extant counterparts suggest a new mechanism of formation.
584 citations
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TL;DR: On the basis of physiological as well as genetic properties, strains from the CEN.PK family were selected as a platform for cell-factory research on the stoichiometry and kinetics of growth and product formation.
583 citations
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TL;DR: The goal of this paper is to review both the understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.
Abstract: Product design is a highly involved, often ill-defined, complex and iterative process, and the needs and specifications of the required artifact get more refined only as the design process moves toward its goal. An effective computer support tool that helps the designer make better-informed decisions requires efficient knowledge representation schemes. In today's world, there is a virtual explosion in the amount of raw data available to the designer, and knowledge representation is critical in order to sift through this data and make sense of it. In addition, the need to stay competitive has shrunk product development time through the use of simultaneous and collaborative design processes, which depend on effective transfer of knowledge between teams. Finally, the awareness that decisions made early in the design process have a higher impact in terms of energy, cost, and sustainability, has resulted in the need to project knowledge typically required in the later stages of design to the earlier stages. Research in design rationale systems, product families, systems engineering, and ontology engineering has sought to capture knowledge from earlier product design decisions, from the breakdown of product functions and associated physical features, and from customer requirements and feedback reports. VR (Virtual reality) systems and multidisciplinary modeling have enabled the simulation of scenarios in the manufacture, assembly, and use of the product. This has helped capture vital knowledge from these stages of the product life and use it in design validation and testing. While there have been considerable and significant developments in knowledge capture and representation in product design, it is useful to sometimes review our position in the area, study the evolution of research in product design, and from past and current trends, try and foresee future developments. The goal of this paper is thus to review both our understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.
583 citations
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TL;DR: In this article, the authors apply a water-balance framework to catchments in the United States and find a greater percentage of precipitation as snowfall is associated with greater mean streamflow.
Abstract: Increased surface temperatures are expected to cause less precipitation in the form of snow. The impact of decreased snowfall has previously been assumed to not influence streamflow significantly. This work applies a water-balance framework to catchments in the United States and finds a greater percentage of precipitation as snowfall is associated with greater mean streamflow.
583 citations
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TL;DR: The observation of a quantized conductance plateau at 2e2/h in the zero-bias conductance measured in indium antimonide semiconductor nanowires covered with an aluminium superconducting shell strongly supports the existence of Majorana zero-modes in the system.
Abstract: Majorana zero-modes - a type of localized quasiparticle - hold great promise for topological quantum computing. Tunnelling spectroscopy in electrical transport is the primary tool for identifying the presence of Majorana zero-modes, for instance as a zero-bias peak in differential conductance. The height of the Majorana zero-bias peak is predicted to be quantized at the universal conductance value of 2e 2 /h at zero temperature (where e is the charge of an electron and h is the Planck constant), as a direct consequence of the famous Majorana symmetry in which a particle is its own antiparticle. The Majorana symmetry protects the quantization against disorder, interactions and variations in the tunnel coupling. Previous experiments, however, have mostly shown zero-bias peaks much smaller than 2e 2 /h, with a recent observation of a peak height close to 2e 2 /h. Here we report a quantized conductance plateau at 2e 2 /h in the zero-bias conductance measured in indium antimonide semiconductor nanowires covered with an aluminium superconducting shell. The height of our zero-bias peak remains constant despite changing parameters such as the magnetic field and tunnel coupling, indicating that it is a quantized conductance plateau. We distinguish this quantized Majorana peak from possible non-Majorana origins by investigating its robustness to electric and magnetic fields as well as its temperature dependence. The observation of a quantized conductance plateau strongly supports the existence of Majorana zero-modes in the system, consequently paving the way for future braiding experiments that could lead to topological quantum computing.
582 citations
Authors
Showing all 38152 results
Name | H-index | Papers | Citations |
---|---|---|---|
Albert Hofman | 267 | 2530 | 321405 |
Charles M. Lieber | 165 | 521 | 132811 |
Ad Bax | 138 | 486 | 97112 |
George C. Schatz | 137 | 1155 | 94910 |
Georgios B. Giannakis | 137 | 1321 | 73517 |
Jaap S. Sinninghe Damsté | 134 | 726 | 61947 |
Avelino Corma | 134 | 1049 | 89095 |
Mark A. Ratner | 127 | 968 | 68132 |
Jing Kong | 126 | 553 | 72354 |
Robert J. Cava | 125 | 1042 | 71819 |
Reza Malekzadeh | 118 | 900 | 139272 |
Jinde Cao | 117 | 1430 | 57881 |
Mike S. M. Jetten | 117 | 488 | 52356 |
Liquan Chen | 111 | 689 | 44229 |
Oscar H. Franco | 111 | 822 | 66649 |