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The statistical physics of real-world networks
G. Cimini, T. Squartini, F. Saracco, D. Garlaschelli, A. Gabrielli, G.
Nature Reviews Physics
21 views
#networks #informationtheory #complexity
topic-5 (Extreme materials)
How much can we influence the rate of innovation?
T. Fink, M. Reeves
Science Advances
34 views
#innovation #strategy #management
topic-4 (Extreme materials)
Exactly solvable random graph ensemble with extensively many short cycles
F. Lopez, P. Barucca, M. Fekom, A. Coolen
Journal of Physics A: Mathematical and Theoretical
345 views
#randomgraphs #clustering #statisticalphysics
topic-5 (Extreme materials)
The organization of the interbank network and how ECB unconventional measures affected the e-MID overnight market
F. Lillo, P. Barucca
Computational Management Science
334 views
#finance #banking #risk
topic-6 (Extreme materials)
A complex network approach for the estimation of the energy demand of electric mobility
M. Mureddu, A. Facchini, A. Scala, G. Caldarelli, A. Damiano
Scientific Reports
94 views
#complexnetworks #energy #infrastructures
How well do experience curves predict technological progress? A method for making distributional forecasts
F. Lafond, A. Bailey, J. Bakker, D. Rebois, R. Zadourian, P. McSharry, D. Farmer
Technological Forecasting and Social Change
229 views
#technology #innovation #economics
topic-4 (Extreme materials)
A holistic approach for collaborative workload execution in volunteer clouds
S. Sebastio, M. Amoretti, A. Lafuente, A. Scala
ACM Transactions on Modeling and Computer Simulation
172 views
#growth #complexsystems #cloud
topic-2 (Extreme materials)
From ecology to finance (and back?): a review on entropy-based null models for the analysis of bipartite networks
M. Straka, G. Caldarelli, T. Squartini, F. Saracco
Journal of Statistical Physics
162 views
#ecology #finance #entropy
topic-5 (Extreme materials) topic-6 (Low-energy computing)
Maximum one-shot dissipated work from Rényi divergences
N. Halpern, A. Garner, O. Dahlsten, V. Vedral
Physical Review E
55 views
#entropy #informationtheory #statisticalphysics
topic-3 (Extreme materials)
Eigenvalues of subgraphs of the cube
B. Bollobás, J. Lee, S. Letzter
European Journal of Combinatorics
162 views
#graph #combinatorics #asymptoticbehaviour
topic-5 (Extreme materials)
Tackling information asymmetry in networks: a new entropy-based ranking index
P. Barucca, G. Caldarelli, T. Squartini
Journal of Statistical Physics
51 views
#complexnetworks #Shannonentropy #informationtheory
topic-5 (Extreme materials)
Reconstructing grain-shape statistics from electron back-scatter diffraction microscopy
R. Farr, Z. Vukmanovic, M. Holness, E. Griffiths
Physical Review Materials
206 views
#EBSD #ElectronMicroscopy #Materials
topic-1 (Extreme materials)
On defining the Hamiltonian beyond quantum theory
D. Branford, O. Dahlsten, A. Garner
Foundations of Physics
47 views
#Hamiltonian #probabilistictheories #energy
topic-3 (Extreme materials)
119 papers
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Reconstructing grain-shape statistics from electron back-scatter diffraction microscopy
R. Farr, Z. Vukmanovic, M. Holness, E. Griffiths
Physical Review Materials
2, 073804 (07/18)
A full, three-dimensional analysis of the shapes of grains in polycrystalline materials, such as rocks or ceramics, is difficult and costly. Here, the authors describe an approach that takes electron microscopy images of plane sections (together with crystal orientation data from the back-scattered electrons), and allows one to deduce information about the size and shape distribution of the randomly-oriented three-dimensional grains. The authors also provide an estimate of how much data is needed to achieve a certain level of confidence. Since this type of microscopy and image analysis is a highly effective and optimised technique, the new result promises to give much easier access to the three dimensional structures of many crystalline materials.
Synopsis: Grain Properties in a Single Shot
Reconstructing grain-shape statistics from electron back-scatter diffraction microscopy
APS Physics, 2018-07-31