TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted

TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted

Advanced Technologies for the Optimization of Internal Combustion Engines

This Special Issue puts together recent findings in advanced technologies for the optimization of internal combustion engines in order to help the scientific community address the efforts towards the development of higher-power engines with lower fuel consumption and pollutant emissions

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here

Design of a dependable interlock system for linear colliders

For high energy accelerators, the interlock system is a key part of the machine protection. The interlock principle is to inhibit the beam either on failure of critical equipment and/or on low beam quality evaluation. The dependability of such a system is the most critical parameter. This thesis presents the design of an dependable interlock system for linear collider with an application to the CLIC (Compact Linear Collider) project. This design process is based on the IEEE 1220 standard and is is divided in four steps. First,the specifications are established, with a focus on the dependability, more precisely the reliability and the availability of the system. The second step is the design proposal based on a functional analysis, the CLIC and interfaced systems architecture. Third, the feasibility study is performed, applying the concepts in an accelerator facility. Finally, the last step is the hardware verification. Its aim is to prove that the proposed design is able to reach the requirements

TRANSLATING CHEMISTRY, STRUCTURE, AND PROCESSING TO THE SOLID-STATE MORPHOLOGY AND FUNCTION OF ORGANIC SEMICONDUCTORS THROUGH COMPUTATIONAL MODELING AND SIMULATIONS

The immense synthetic design space and material versatility have driven the exploration and development of organic semiconductors (OSC) over several decades. While many OSC designs focus on the chemistries of the molecular or polymer building blocks, a priori, multiscale control over the solid-state morphology is required for effective application of the active layer in a given technology. However, molecular assembly during solid-state formation is a complex function interconnecting the building block chemistry and the processing environment. Insufficient knowledge as to how these aspects engage, especially at the atomistic and molecular scales, has so far limited the ability to predict OSC solid-state morphology, leaving Edisonian approaches as the stalwart methods. Therefore, through multiscale simulations combining atomistic quantum scale modeling and state-of-the-art molecular dynamics (MD) techniques, we aim to establish first principles understanding required to synthetically regulate solid-state morphology of organic semiconductors (OSC) as a function of molecular chemistry and processing. In turn, we try to understand the deceivingly simple yet complex mechanisms behind molecular aggregation and crystallization of OSC. Simultaneously, we develop semi-to-fully automated high-throughput schemes to automate the complex and labor-intensive analyses to generate data based on various crystal structures in different crystallization environments. Ultimately, we aim to bridge molecular-scale information revealed on solid-state physical organization, understood in the context of chromophore chemistry and the molecular environment, with the macro scale properties to uncover useful guidelines for rational design and morphology regulation of OSC systems