Overview

Welcome to the MQS Toolstack documentation for learning about modern calculation pipelines utilizing quantum chemistry and machine learning models.

The modular algorithms have been compiled for high performance CPUs, GPUs and QPUs and can be chained together in a flexible way to solve a wide range of use-case applications.

We provide integrated tools to apply the algorithms in a user-friendly way and leverage a combination of code oriented programming (SDK) and dashboard interfaces to let you gain control and an easy overview of results, datasets and settings.

• Dashboards

  MQS Dashboard

  MQS Cebule Engine

  JupyterLab

  Kubeflow

• Infrastructure

  High Performance Computing (HPC)

  Object Storage

  Git Version Control

  Container Registry

• Software Development Kit (SDK)

  Tasks

  SDK Functions & Arguments

  HPC via Kubernetes and SLURM

• Database & Datasets, MLIPs

  PubchemQC

  QMugs

  MLIP (Machine Learned Interatomic Potential), Machine Learned Force Fields (MLFF) Models

• DFT, Semi-empirical Methods & Tight-binding Models

  DFT, PW-DFT

  PM6, PM7

  GFNx-xTB, g-xTB

• Implicit Solvation Models

  COSMO (CPCM)

  PCM (DPCM)

  IEFPCM

• Statistical Thermodynamics: COSMO-RS/-SAC

  COSMO-RS/-SAC

  COSMO-RS with intermolecular dispersion

  COSMO-SAC-dsp

  eCOSMO-RS/-SAC

• Statistical Thermodynamics: NRTL

  NRTL, eNRTL

  Wilson

• Statistical Thermodynamics: UNIFAC

  Mod. UNIFAC, UNIFAC-IL, UNIFAC-VISCO

  UNIFAC 2.0

• Molecular Dynamics (MD)

  Born-Oppenheimer MD (BOMD)

  Car-Parrinello MD (CPMD)

  Path Integral MD (PIMD)

• Molecular Descriptors

  RDKit

  Geometric

  UNIFAC

  COSMO-RS/COSMO-SAC (sigma-profiles/-moments)

  BOMD-based Descriptors

• Reaction Networks

  Reaction pathway optimization

• Machine Learning (ML) & Artificial Intelligence (AI)

  Graph Neural Network (GNN) Library

  Generative Adversarial Network (GAN)

• Quantum Computing

  Fermion-Qubit Mapping & Measurement

  Tensor Networks & Variational Quantum Algorithms

  Zero-Noise Extrapolation (ZNE)

  Simulated & Quantum Annealing

  MQS Genetic Quantum Circuit Generator (Xenakis)

  MQS & Fraunhofer Benchmarking Framework

• Lab Connect

  UA + MQTT based Real-time Data Capturing & Storage Framework

  Robotics Lab Interface

  Bayesian Design of Experiments & Closed-loop Optimization

Examples / Use-cases

• COSMO and COSMO-RS/-SAC

  • How to run a COSMO calculation
  • How to run COSMO and COSMO-RS/-SAC sigma profile calculations on a dataset

• Molecular Dynamics

  • How to run a BOMD calculation
  • How to run a CPMD calculation
  • How to run force field MD calculations on a dataset

• Geometry Optimization Sequences

  • Sequential geometry optimization with MMFF94 force field and GFN2-xTB method followed by GNN based HOMO-LUMO gap prediction
  • Force field and semi-empirical/MLIP geometry optimization on a dataset

• Group Contribution

  • How to calculate surfactant or ionic liquid viscosity UNIFAC group contribution on a dataset

• Database & HOMO-LUMO Gap

  • Anion, cation, S0, D0, T0, Q0 states look-up
  • Get HOMO-LUMO ga from the PubchemQC PM6 and QMugs data set

• HOMO-LUMO Gap, Poly-chlorinated Biphenyls (PCBs) & Toxicity

  • Get HOMO-LUMO gap of PCBs and fine-tune DelFTa model for torsional angles and HOMO-LUMO gap based toxicity indicator
  • DelFTa Model prediction performance comparison for PCB molecules against PM6 data
  • GNN performance compared to DelFTa for PCB molecules

• Viscosity

  • How to run viscosity GNN training, fine-tuning, and prediction on a dataset

• Kubeflow

  • Fine-tuning a model via Kubeflow for toxicity predictions of PCB molecules
  • Prediction of toxicity of PCB molecules with trained model via Kubeflow

The MQS Toolstack allows you to tackle demanding problems within pharma, life science, chemistry and materials research.

Use-case Domain →	Formulation Development & Product Design	Upscaling & Process Simulations	Materials Design
Properties →	Solubility, Stability, Toxicity, Viscosity	Vapour-Liquid Equilibrium (VLE)	HOMO-LUMO Gap, Ground & Excited States
	Binding Analysis	Liquid-Liquid Equilibrium (LLE)	Seebeck Coefficient
		Solid-Liquid Equilibrium (SLE)	Solubility, Phase Stability
Use-case Examples →	(Bio)Pharma Solubility in Multi-compound Mixtures	Crystallizer Design for Purification Processes	OLED Materials
	Toxicity Checks in Pharma & Chemical Product Development	Solvents Analysis for CO2 Capture & CO2 Utilization Processes	Energy Storage Materials
	Human, Animal and Environmental Safety	Liquid-Liquid Chromatographic Separation	High-Entropy Alloys
	Beauty Care Product Design	Property data for Computational Fluid Dynamics (CFD)	Catalyst Design
	Integrated Drug Discovery & Formulation Analysis		Anti-corrosion and Functional Coatings

Feedback and questions

Do not hesitate to send us feedback, if you have any questions or if you find mistakes in the text, code snippets, equations, or any other flaw.

Please let us know through the support field in the MQS Dashboard or via contact (at) mqs [dot] dk.

Some notes on this documentation

• The table of content (ToC) is shown in desktop view on the right. When reading the documentation on a phone screen and navigating to a specific chapter, you will be able to see the table of contents by again opening the navigation menu and a symbol should show up next to the current opened chapter. This symbol opens up the ToC.