scholarly journals Assembly of nothing: equilibrium fluids with designed structured porosity

Soft Matter ◽  
2016 ◽  
Vol 12 (10) ◽  
pp. 2663-2667 ◽  
Author(s):  
Beth A. Lindquist ◽  
Ryan B. Jadrich ◽  
Thomas M. Truskett
Keyword(s):  
Pair Interaction ◽  
Inverse Design ◽  
Inhomogeneous Fluid ◽  
Size And Morphology ◽  
Isotropic Pair

Inverse design was used to discover an isotropic pair interaction that assembles particles into an inhomogeneous fluid matrix surrounding pores of prescribed size and morphology.

THREE-SPIN CORRELATION OF THE ISING MODEL ON A KAGOMÉ LATTICE

1990 ◽  
Vol 04 (01) ◽  
pp. 123-130 ◽  
Author(s):  
K. Y. LIN ◽  
B. H. CHEN
Keyword(s):  
Ising Model ◽  
Spin Correlation ◽  
Pair Interaction ◽  
Kagome Lattice ◽  
Spin Correlations ◽  
Kagomé Lattice ◽  
Pair And Triplet Interactions ◽  
Isotropic Pair ◽  
Pair Interactions

Several local three-spin correlations are derived for the Ising model on a Kagomé lattice with anisotropic pair interactions. Three-spin correlation for three spins surrounding a triangle is derived for the Kagomé lattice Ising model with isotropic pair and triplet interactions at a particular temperature determined by pair interaction only.

Inverse design of self-assembling Frank-Kasper phases and insights into emergent quasicrystals

2017 ◽  
Author(s):  
Beth Lindquist ◽  
Ryan Jadrich ◽  
William Pineros ◽  
Thomas Truskett
Keyword(s):  
Machine Learning ◽  
Self Assembly ◽  
Design Strategy ◽  
Particle Systems ◽  
Inverse Design ◽  
Learning Approach ◽  
Self Assembling ◽  
Machine Learning Approach ◽  
Component Particle ◽  
Isotropic Pair

We discuss how a machine learning approach based on relative entropy optimization can be used as an inverse design strategy to discover isotropic pair interactions that self-assemble single- or multi-component particle systems into Frank-Kasper phases. In doing so, we also gain insights into self-assembly of quasicrystals.

Inverse design of self-assembling Frank-Kasper phases and insights into emergent quasicrystals

2017 ◽  
Author(s):  
Beth Lindquist ◽  
Ryan Jadrich ◽  
William Pineros ◽  
Thomas Truskett
Keyword(s):  
Machine Learning ◽  
Self Assembly ◽  
Design Strategy ◽  
Particle Systems ◽  
Inverse Design ◽  
Learning Approach ◽  
Self Assembling ◽  
Machine Learning Approach ◽  
Component Particle ◽  
Isotropic Pair

We discuss how a machine learning approach based on relative entropy optimization can be used as an inverse design strategy to discover isotropic pair interactions that self-assemble single- or multi-component particle systems into Frank-Kasper phases. In doing so, we also gain insights into self-assembly of quasicrystals.

AN INVERSE DESIGN METHOD FOR A WING IN FULL CRUISING CONFIGURATION OF A REGIONAL AIRCRAFT VIA RANS APPROACH

2020 ◽  
Vol 51 (1) ◽  
pp. 1-13
Author(s):  
Anatoliy Longinovich Bolsunovsky ◽  
Nikolay Petrovich Buzoverya ◽  
Nikita Aleksandrovich Pushchin
Keyword(s):  
Design Method ◽  
Inverse Design ◽  
Inverse Design Method

Inverse Design of a Thick Supercritical Airfoil.

2000 ◽  
Vol 43 (140) ◽  
pp. 61-66
Author(s):  
Tjoetjoek Eko PAMBAGJO ◽  
Kazuhiro NAKAHASHI ◽  
Shigeru OBAYASHI
Keyword(s):  
Inverse Design ◽  
Supercritical Airfoil
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