Determination of a Mathematical Discrete Model for the Study of Thermoelectric Materials with the Use of the Microprobe

Author(s):  
Antonio Lopez ◽  
Francisco Villasevil ◽  
Rafael Pindado ◽  
German Noriega ◽  
Dieter Platzek
2019 ◽  
Vol 75 (a2) ◽  
pp. e321-e321
Author(s):  
Andreas Delimitis ◽  
Vidar Hansen ◽  
Elli Symeou ◽  
Theodora Kyratsi ◽  
Mona Wetrhus Minde ◽  
...  

Robotics ◽  
2018 ◽  
Vol 7 (3) ◽  
pp. 53 ◽  
Author(s):  
Muratulla Utenov ◽  
Tarek Sobh ◽  
Zhumadil Baigunchekov ◽  
Saltanat Zhilkibayeva ◽  
Sarosh Patel

This paper presents a theory for the analytical determination of internal forces in the links of planar linkage mechanisms and manipulators with statically determinate structures, considering the distributed dynamic loads. Linkage mechanisms and manipulators were divided into elements and joints. Discrete models were created for both the elements and the entire mechanism. The dynamic equations of equilibrium for the discrete model of the elements and the hinged and rigid joints, under the action of longitudinal and transverse distributed dynamic trapezoidal loads, were derived. In the dynamic equations of the equilibrium of the discrete model of the elements and joints, the connections between the components of the force vector in the calculated cross-sections and the geometric, physical, and kinematic characteristics of the element were established for its plane-parallel motion. According to the developed technique, programs were created in the Maple system, and animations of the motion of the mechanisms were produced. The links were constructed with the intensity of transverse- and longitudinal-distributed dynamic loads, bending moments, and shearing and normal forces, depending on the kinematic characteristics of the links.


2021 ◽  
Author(s):  
Jose J. Plata ◽  
Victor Posligua ◽  
Antonio Marquez ◽  
Javier Fernández Sanz ◽  
Ricardo Grau-Crespo

The use of computer simulation to predict the lattice thermal conductivity of materials has the potential to accelerate the discovery of new thermoelectric materials. However, the accurate prediction of this property from first principles, without input from experiment, is very computationally demanding, which limits the use of high-throughput strategies in thermoelectric materials design. We present here an accurate, fast, and non-empirical determination of the lattice thermal conductivities of a large family of semiconductors, with composition ABX2 (I-III-VI2), with A=Cu, Ag; B=Al, Ga, In, Tl; and X=S, Se, Te. We solve the Boltzmann transport equation with force constants derived from density functional theory calculations and machine-learning-based regression algorithms, reducing between one and two orders of magnitude the computational cost with respect to conventional approaches of the same accuracy. The results are in good agreement with available experimental data and allow us to rationalize the role of chemical composition, temperature and nanostructuring on the thermal conductivities across this important family of semiconductors.


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