Large negative linear compressibility of a porous molecular co-crystal

2020 ◽  
Vol 56 (31) ◽  
pp. 4324-4327
Author(s):  
Szymon Sobczak ◽  
Aleksandra Półrolniczak ◽  
Paulina Ratajczyk ◽  
Weizhao Cai ◽  
Andrzej Gładysiak ◽  
...  
Keyword(s):  
Linear Compressibility ◽  
Linear Compression

Porous 1,2-bis[2-methyl-5-(pyridyl)-3thienyl] cyclopentene cocrystal with 1,4-diiodotetrafluorobenzene exhibits large negative linear compression correlated with the shape of pores.

CNN performance dependence on linear image processing

2020 ◽  
Vol 2020 (10) ◽  
pp. 310-1-310-7
Author(s):  
Khalid Omer ◽  
Luca Caucci ◽  
Meredith Kupinski
Keyword(s):  
Image Processing ◽  
Texture Classification ◽  
Full Rank ◽  
Detection Performance ◽  
Ideal Observer ◽  
Training Data ◽  
Image Texture ◽  
Training Images ◽  
Analytic Expressions ◽  
Linear Compression

This work reports on convolutional neural network (CNN) performance on an image texture classification task as a function of linear image processing and number of training images. Detection performance of single and multi-layer CNNs (sCNN/mCNN) are compared to optimal observers. Performance is quantified by the area under the receiver operating characteristic (ROC) curve, also known as the AUC. For perfect detection AUC = 1.0 and AUC = 0.5 for guessing. The Ideal Observer (IO) maximizes AUC but is prohibitive in practice because it depends on high-dimensional image likelihoods. The IO performance is invariant to any fullrank, invertible linear image processing. This work demonstrates the existence of full-rank, invertible linear transforms that can degrade both sCNN and mCNN even in the limit of large quantities of training data. A subsequent invertible linear transform changes the images’ correlation structure again and can improve this AUC. Stationary textures sampled from zero mean and unequal covariance Gaussian distributions allow closed-form analytic expressions for the IO and optimal linear compression. Linear compression is a mitigation technique for high-dimension low sample size (HDLSS) applications. By definition, compression strictly decreases or maintains IO detection performance. For small quantities of training data, linear image compression prior to the sCNN architecture can increase AUC from 0.56 to 0.93. Results indicate an optimal compression ratio for CNN based on task difficulty, compression method, and number of training images.

Negative linear compressibility in nanoporous metal-organic frameworks rationalized by the empty channel structural mechanism

2021 ◽  
Author(s):  
Francisco Colmenero
Keyword(s):  
Crystal Structures ◽  
Metal Organic Frameworks ◽  
Structural Mechanism ◽  
Nanoporous Metal ◽  
Metal Organic ◽  
Linear Compressibility

Cobalt squarate hydroxide (Co3(C4O4)2(OH)2), zinc squarate tetrahydrate (ZnC4O4·4 H2O) and titanium oxalate trioxide dihydrate (Ti2(C2O4)O3·2 H2O) are nanoporous metal-organic frameworks possessing empty channels in their crystal structures. The crystal structures...

scholarly journals Evidence of Pressure-Induced Phase Transitions and Negative Linear Compressibility in Formamidinium Manganese-Hypophosphite Hybrid Perovskite

2021 ◽  
Author(s):  
Mirosław Ma̧czka ◽  
Mikołaj Kryś ◽  
Szymon Sobczak ◽  
Daniel Linhares Militão Vasconcelos ◽  
Paulo Tarso Cavalcante Freire ◽  
...  
Keyword(s):  
Phase Transitions ◽  
Hybrid Perovskite ◽  
Linear Compressibility

scholarly journals The Multidirectional Auxeticity and Negative Linear Compressibility of a 3D Mechanical Metamaterial

Materials ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2193 ◽  
Author(s):  
Krzysztof K. Dudek ◽  
Daphne Attard ◽  
Ruben Gatt ◽  
James N. Grima-Cornish ◽  
Joseph N. Grima
Keyword(s):  
Theoretical Model ◽  
Poisson’S Ratio ◽  
Three Dimensional ◽  
Poisson's Ratio ◽  
Negative Poisson’S Ratio ◽  
Structural Units ◽  
Loading Direction ◽  
Arbitrary Loading ◽  
Negative Poisson's Ratio ◽  
Linear Compressibility

In this work, through the use of a theoretical model, we analyse the potential of a specific three-dimensional mechanical metamaterial composed of arrowhead-like structural units to exhibit a negative Poisson’s ratio for an arbitrary loading direction. Said analysis allows us to assess its suitability for use in applications where materials must be able to respond in a desired manner to a stimulus applied in multiple directions. As a result of our studies, we show that the analysed system is capable of exhibiting auxetic behaviour for a broad range of loading directions, with isotropic behaviour being shown in some planes. In addition to that, we show that there are also certain loading directions in which the system manifests negative linear compressibility. This enhances its versatility and suitability for a number of applications where materials exhibiting auxetic behaviour or negative linear compressibility are normally implemented.

scholarly journals The Room Temperature Elastic Behaviour of CsH2PO4

1985 ◽  
Vol 38 (1) ◽  
pp. 63 ◽  
Author(s):  
S Prawer ◽  
TF Smith ◽  
TR Finlayson
Keyword(s):  
Elastic Constant ◽  
Young’S Modulus ◽  
Ultrasonic Velocity ◽  
Room Temperature ◽  
Elastic Anisotropy ◽  
Elastic Behaviour ◽  
Dihydrogen Phosphate ◽  
Velocity Measurements ◽  
Constant Matrix ◽  
Linear Compressibility

The components of the elastic constant matrix of monoclinic caesium dihydrogen phosphate (CDP) have been determined using ultrasonic velocity measurements to be Cl1 = 28� 83 � 0 '43, C22 = 26�67 � O� 37, C33 = 65 �45 � 0'48, C44 = 8 .1O� 0,15, Css = 5 �20� 0,24, C66 = 9�17 � 0,22, C12 = 1l'4�3'6, C13 = 42�87�1�58, CIS = 5'13�0'67, C23 = 14�5�4�4, C 2S = 8'4�4'3, C3S = 7�50�0�81 and C46 = -2�25�0�31 GPa. Calculations of the velocity surfaces, ray directions, Young's modulus surfaces and linear compressibility show marked elastic anisotropy, which has been correlated with the chain and layer-like structure of CDP.

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