SCINE -- Software for Chemical Interaction Networks

Abstract

The software for chemical interaction networks (SCINE) project aims at pushing the frontier of quantum chemical calculations on molecular structures to a new level. While calculations on individual structures as well as on simple relations between them e.g., as given by an intrinsic reaction coordinate) have become routine in chemistry, new developments have pushed the frontier in the field to high-throughput calculations. Chemical relations may be created by a search for specific molecular properties in a molecular design attempt or they can be defined by a set of elementary reaction steps that form a chemical reaction network. The software modules of SCINE have been designed to facilitate such studies. The features of the modules are (i) general applicability of the applied methodologies ranging from electronic structure (no restriction to specific elements of the periodic table) to microkinetic modeling (with little restrictions on molecularity), full modularity so that SCINE modules can also be applied as stand-alone programs or be exchanged for external software packages that fulfill a similar purpose (to increase options for computational campaigns and to provide alternatives in case of tasks that are hard or impossible to accomplish with certain programs), (ii) high stability and autonomous operations so that control and steering by an operator is as easy as possible, and (iii) easy embedding into complex heterogeneous environments for molecular structures taken individually or in the context of a reaction network. A graphical user interface unites all modules and ensures interoperability. All components of the software have been made available open source and free of charge.

27 pages, 10 figures

References in corpus (72)

• CP2K: An Electronic Structure and Molecular Dynamics Software Package -- Quickstep: Efficient and Accurate Electronic Structure Calculations
• The density-matrix renormalization group in the age of matrix product states
• ANI-1: An extensible neural network potential with DFT accuracy at force field computational cost
• Recent developments in the PySCF program package
• A Universal Graph Deep Learning Interatomic Potential for the Periodic Table
• Less is more: sampling chemical space with active learning
• Physics-inspired structural representations for molecules and materials
• Automated Selection of Active Orbital Spaces
• The Density Matrix Renormalization Group in Chemistry and Molecular Physics: Recent Developments and New Challenges
• The density matrix renormalization group for ab initio quantum chemistry
• Tensor product methods and entanglement optimization for ab initio quantum chemistry
• MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields
• Measuring orbital interaction using quantum information theory
• Exploration of Reaction Pathways and Chemical Transformation Networks
• Automated construction of molecular active spaces from atomic valence orbitals
• How large should the QM region be in QM/MM calculations? The case of catechol O-methyltransferase
• The Exploration of Chemical Reaction Networks
• Bayesian Error Estimation in Density Functional Theory
• An Efficient Matrix Product Operator Representation of the Quantum-Chemical Hamiltonian
• Enabling New Flexibility in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers
• Heuristics-Guided Exploration of Reaction Mechanisms
• Entanglement Measures for Single- and Multi-Reference Correlation Effects
• Two-site entropy and quantum phase transitions in low-dimensional models
• Context-Driven Exploration of Complex Chemical Reaction Networks
• Systematic Quantum Mechanical Region Determination in QM/MM Simulation
• The Chronus Quantum (ChronusQ) Software Package
• Multi-reference perturbation theory with Cholesky decomposition for the density matrix renormalization group
• Large-scale quantum-dynamics with matrix product states
• The Delicate Balance of Static and Dynamic Electron Correlation
• autoCAS: a program for fully automated multi-configurational calculations
• Error-Controlled Exploration of Chemical Reaction Networks with Gaussian Processes
• Automated Identification of Relevant Frontier Orbitals for Chemical Compounds and Processes
• Systematic Error Estimation for Chemical Reaction Energies
• Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis
• Molassembler: Molecular graph construction, modification and conformer generation for inorganic and organic molecules
• Semiempirical Molecular Orbital Models based on the Neglect of Diatomic Differential Overlap Approximation
• Vibrational Density Matrix Renormalization Group
• MACE-OFF: Transferable Short Range Machine Learning Force Fields for Organic Molecules
• Interactive Chemical Reactivity Exploration
• Mechanism Deduction from Noisy Chemical Reaction Networks
• A nonorthogonal state-interaction approach for matrix product state wave functions
• Error Assessment of Computational Models in Chemistry
• Minimum Energy Paths and Transition States by Curve Optimization
• Expansive Quantum Mechanical Exploration of Chemical Reaction Paths
• Lifelong Machine Learning Potentials
• Optimization of highly excited matrix product states with an application to vibrational spectroscopy
• Self-Consistent Embedding of Density-Matrix Renormalization Group Wavefunctions in a Density Functional Environment
• Automated construction of quantum-classical hybrid models
• Steering Orbital Optimization out of Local Minima and Saddle Points Toward Lower Energy
• Self-Parametrizing System-Focused Atomistic Models
• Real-time Quantum Chemistry
• Pathfinder -- Navigating and Analyzing Chemical Reaction Networks with an Efficient Graph-based Approach
• The Polarizable Embedding Density Matrix Renormalization Group Method
• Corresponding Active Orbital Spaces along Chemical Reaction Paths
• Nuclear-Electronic All-Particle Density Matrix Renormalization Group
• Electron Dynamics with the Time-Dependent Density Matrix Renormalization Group
• Real-time feedback from iterative electronic structure calculations
• Navigating chemical reaction space with a steering wheel
• High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation
• On the Predictive Power of Chemical Concepts
• Accelerating Wave Function Convergence in Interactive Quantum Chemical Reactivity Studies
• Quantum Proton Effects from Density Matrix Renormalization Group Calculations
• Molecular propensity as a driver for explorative reactivity studies
• Immersive Interactive Quantum Mechanics for Teaching and Learning Chemistry
• Concentration-Flux-Steered Mechanism Exploration with an Organocatalysis Application
• Flexible DMRG-based framework for anharmonic vibrational calculations
• Ultra-Fast Semi-Empirical Quantum Chemistry for High-Throughput Computational Campaigns with Sparrow
• Quantum chemical roots of machine-learning molecular similarity descriptors
• Uncertainty-aware First-principles Exploration of Chemical Reaction Networks
• Automated Preparation of Nanoscopic Structures: Graph-Based Sequence Analysis, Mismatch Detection, and pH-Consistent Protonation with Uncertainty Estimates
• Ultra-fast Spectroscopy for High-Throughput and Interactive Quantum Chemistry
• Heuristics and Uncertainty Quantification in Rational and Inverse Compound and Catalyst Design

Cited by in corpus (6)

• Automated Microsolvation for Minimum Energy Path Construction in Solution
• Machine Learning Enhanced Calculation of Quantum-Classical Binding Free Energies
• QCMaquis 4.0: Multi-Purpose Electronic, Vibrational, and Vibronic Structure and Dynamics Calculations with the Density Matrix Renormalization Group
• Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks
• Lifelong Machine Learning Potentials for Chemical Reaction Network Explorations
• Automated Exploration of Radical-Molecule Chemistry: The Case of Oxirane + CH in the ISM