Hardware and quantum mechanical calculations

The remarkable progress in the architecture, speed and capacity of computer hardware continues to drive the development of quantum mechanical methods, thus allowing calculations on increasingly complex systems. Using high-end computers, accurate quantum mechanical all-electron studies are now possible for solids such as transition metal compounds containing about fifty atoms per unit cell. Pseudo-potential plane-wave methods are being applied to unit cells with 400 silicon atoms, and organic molecules consisting of over 100 atoms have become tractable using ab initio methods. Smaller, yet still useful calculations can be carried out on workstations. The combination of graphics workstations and high-performance supercomputers, integrated in tightly coupled heterogeneous networks, has allowed the design of software systems with unprecedented convenience and visualization capabilities. Despite this progress, however, there is still an urgent need for new quantum mechanical methods which converge systematically to the exact solution of Schrodinger’s equation while maintaining a reasonable scaling of the computational effort with the system size.

Polymers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1914
Author(s):  
Alejandra Rubio Hernández-Sampelayo ◽  
Rodrigo Navarro ◽  
Ángel Marcos-Fernández

The synthesis of poly(urethane-urea) (PUUs) bearing deactivated diamines within the backbone polymer chain is presented. Several deactivated diamines present interesting properties for several applications in the biomaterial field due to their attractive biocompatibility. Through an activation with Chloro-(trimethyl)silane (Cl-TMS) during the polymerization reaction, the reactivity of these diamines against diisocyanates was triggered, leading to PUUs with high performance. Indeed, through this activation protocol, the obtained molecular weights and mechanical features increased considerably respect to PUUs prepared following the standard conditions. In addition, to demonstrate the feasibility and versatility of this synthetic approach, diisocyanate with different reactivity were also addressed. The experimental work is supported by calculations of the electronic parameters of diisocyanate and diamines, using quantum mechanical methods.


2020 ◽  
Vol 22 (10) ◽  
pp. 5985-5994
Author(s):  
Yin-Feng Wang ◽  
Tian Qin ◽  
Jia-Min Tang ◽  
Yan-Jiao Liu ◽  
Miao Xie ◽  
...  

Focusing on innovative high-performance single-pole double-throw nonlinear optical (NLO) molecular switches, two C3v configurations (1 and 3) and one D3h configuration (2) of bipyramidal CaN3Ca have been obtained by using quantum mechanical methods.


Author(s):  
Hitesh Yadav ◽  
Rita Chhikara ◽  
Charan Kumari

Background: Software Product Line is the group of multiple software systems which share the similar set of features with multiple variants. Feature model is used to capture and organize features used in different multiple organization. Objective: The objective of this research article is to obtain an optimized subset of features which are capable of providing high performance. Methods: In order to achieve the desired objective, two methods have been proposed. a) An improved objective function which is used to compute the contribution of each feature with weight based methodology. b) A hybrid model is employed to optimize the Software Product Line problem. Results: Feature sets varying in size from 100 to 1000 have been used to compute the performance of the Software Product Line. Conclusion: The results shows that proposed hybrid model outperforms the state of art metaheuristic algorithms.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yasmine S. Al-Hamdani ◽  
Péter R. Nagy ◽  
Andrea Zen ◽  
Dennis Barton ◽  
Mihály Kállay ◽  
...  

AbstractQuantum-mechanical methods are used for understanding molecular interactions throughout the natural sciences. Quantum diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] are state-of-the-art trusted wavefunction methods that have been shown to yield accurate interaction energies for small organic molecules. These methods provide valuable reference information for widely-used semi-empirical and machine learning potentials, especially where experimental information is scarce. However, agreement for systems beyond small molecules is a crucial remaining milestone for cementing the benchmark accuracy of these methods. We show that CCSD(T) and DMC interaction energies are not consistent for a set of polarizable supramolecules. Whilst there is agreement for some of the complexes, in a few key systems disagreements of up to 8 kcal mol−1 remain. These findings thus indicate that more caution is required when aiming at reproducible non-covalent interactions between extended molecules.


2021 ◽  
Vol 22 (9) ◽  
pp. 4378
Author(s):  
Anna Helena Mazurek ◽  
Łukasz Szeleszczuk ◽  
Dariusz Maciej Pisklak

This review focuses on a combination of ab initio molecular dynamics (aiMD) and NMR parameters calculations using quantum mechanical methods. The advantages of such an approach in comparison to the commonly applied computations for the structures optimized at 0 K are presented. This article was designed as a convenient overview of the applied parameters such as the aiMD type, DFT functional, time step, or total simulation time, as well as examples of previously studied systems. From the analysis of the published works describing the applications of such combinations, it was concluded that including fast, small-amplitude motions through aiMD has a noticeable effect on the accuracy of NMR parameters calculations.


2021 ◽  
Vol 17 (9) ◽  
pp. 5556-5567
Author(s):  
Sergio Pérez-Tabero ◽  
Berta Fernández ◽  
Enrique M. Cabaleiro-Lago ◽  
Emilio Martínez-Núñez ◽  
Saulo A. Vázquez

Author(s):  
Indar Sugiarto ◽  
Doddy Prayogo ◽  
Henry Palit ◽  
Felix Pasila ◽  
Resmana Lim ◽  
...  

This paper describes a prototype of a computing platform dedicated to artificial intelligence explorations. The platform, dubbed as PakCarik, is essentially a high throughput computing platform with GPU (graphics processing units) acceleration. PakCarik is an Indonesian acronym for Platform Komputasi Cerdas Ramah Industri Kreatif, which can be translated as “Creative Industry friendly Intelligence Computing Platform”. This platform aims to provide complete development and production environment for AI-based projects, especially to those that rely on machine learning and multiobjective optimization paradigms. The method for constructing PakCarik was based on a computer hardware assembling technique that uses commercial off-the-shelf hardware and was tested on several AI-related application scenarios. The testing methods in this experiment include: high-performance lapack (HPL) benchmarking, message passing interface (MPI) benchmarking, and TensorFlow (TF) benchmarking. From the experiment, the authors can observe that PakCarik's performance is quite similar to the commonly used cloud computing services such as Google Compute Engine and Amazon EC2, even though falls a bit behind the dedicated AI platform such as Nvidia DGX-1 used in the benchmarking experiment. Its maximum computing performance was measured at 326 Gflops. The authors conclude that PakCarik is ready to be deployed in real-world applications and it can be made even more powerful by adding more GPU cards in it.


Author(s):  
Luca Bertini ◽  
Maurizio Bruschi ◽  
Ugo Cosentino ◽  
Claudio Greco ◽  
Giorgio Moro ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document