Results 21 to 30 of about 2,147,957 (198)

Computational design of rare-earth reduced permanent magnets [PDF]

open access: yes, 2020
Multiscale simulation is a key research tool in the quest for new permanent magnets. Starting with first principles methods, a sequence of simulation methods can be applied to calculate the maximum possible coercive field and expected energy density ...
Arapan, Sergiu   +8 more
core   +1 more source

Nanophotonic computational design

open access: yesOptics Express, 2013
In contrast to designing nanophotonic devices by tuning a handful of device parameters, we have developed a computational method which utilizes the full parameter space to design linear nanophotonic devices. We show that our method may indeed be capable of designing any linear nanophotonic device by demonstrating designed structures which are fully ...
Lu, Jesse, Vuckovic, Jelena
openaire   +3 more sources

Computational design of metal-supported molecular switches: Transient ion formation during light- and electron-induced isomerisation of azobenzene [PDF]

open access: yes, 2018
In molecular nanotechnology, a single molecule is envisioned to act as the basic building block of electronic devices. Such devices may be of special interest for organic photovoltaics, data storage, and smart materials.
Maurer, Reinhard J., Reuter, Karsten
core   +2 more sources

Prediction of the functional class of lipid binding proteins from sequence-derived properties irrespective of sequence similarity

open access: yesJournal of Lipid Research, 2006
Lipid binding proteins play important roles in signaling, regulation, membrane trafficking, immune response, lipid metabolism, and transport. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting
H.H. Lin   +5 more
doaj   +1 more source

Cross-Sectional 4D-Printing: Upscaling Self-Shaping Structures with Differentiated Material Properties Inspired by the Large-Flowered Butterwort (Pinguicula grandiflora)

open access: yesBiomimetics, 2023
Extrusion-based 4D-printing, which is an emerging field within additive manufacturing, has enabled the technical transfer of bioinspired self-shaping mechanisms by emulating the functional morphology of motile plant structures (e.g., leaves, petals ...
Ekin Sila Sahin   +7 more
doaj   +1 more source

Advanced Timber Construction Industry: A Quantitative Review of 646 Global Design and Construction Stakeholders

open access: yesBuildings, 2023
There has been a multi-storey timber construction boom since the start of the millennium. While there is now a body of research on trends, benefits, and disadvantages of timber construction, there is not yet literature on the wider market or the impact ...
Luis Orozco   +6 more
doaj   +1 more source

Computational Design Thinking and Thinking Design Computing [PDF]

open access: yesConference Proceedings, 2019
In alignment with the rapid advancement of cyber-physical technologies in an information age, we are faced with complex problems that go beyond the kinds of challenges that designers had to deal with in the past. For many of these challenges we do not have established theories, methods, or tools to solve the problems.
openaire   +1 more source

A deep learning approach for detecting drill bit failures from a small sound dataset

open access: yesScientific Reports, 2022
Monitoring the conditions of machines is vital in the manufacturing industry. Early detection of faulty components in machines for stopping and repairing the failed components can minimize the downtime of the machine. In this article, we present a method
Thanh Tran   +2 more
doaj   +1 more source

Data-driven discovery of 2D materials by deep generative models

open access: yesnpj Computational Materials, 2022
Efficient algorithms to generate candidate crystal structures with good stability properties can play a key role in data-driven materials discovery.
Peder Lyngby, Kristian Sommer Thygesen
doaj   +1 more source

Representing individual electronic states for machine learning GW band structures of 2D materials

open access: yesNature Communications, 2022
The study introduces novel methods for representing electronic states as input to machine learning models, which is used to learn high-fidelity band structures of two-dimensional materials from low- fidelity input.
Nikolaj Rørbæk Knøsgaard   +1 more
doaj   +1 more source

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