Computational Techniques for Modelling and Simulating Adsorption Processes for (Waste)Water Treatment / Anshul Yadav, Pawan Kumar Labhasetwar.

Format:

Book

Author/Creator:

Yadav, Anshul, author.

Labhasetwar, Pawan Kumar, author.

Language:

English

Subjects (All):

Environmentalism.

Water-supply.

Physical Description:

1 online resource (272 pages)

Edition:

1st ed.

Place of Publication:

London, England : IWA Publishing, 2025.

Summary:

As global water resources face growing threats from pollution and overuse, sustainable treatment solutions are urgently needed. Among these, adsorption stands out as an effective and versatile method for removing a broad spectrum of contaminants from water and wastewater. However, optimizing adsorption for large-scale applications is a complex challenge that demands both a solid understanding of adsorption science and the use of advanced computational tools. Computational Techniques for Modelling and Simulating Adsorption Processes for (Waste)Water Treatment addresses this challenge by providing a comprehensive guide integrating core adsorption principles with cutting-edge computational approaches for enhancing adsorption efficiency and system design.Structured to lead readers from fundamental concepts to advanced applications, the book includes: an overview of water pollution and treatment a detailed exploration of adsorption principles and models an introduction to general computational strategies for modelling and optimization, leading on to density functional theory, molecular dynamics, Monte Carlo simulations and QSAR techniques AI and machine learning in adsorption modelling computational fluid dynamics and system-level optimization. Together, these topics provide researchers, engineers, and practitioners with the tools needed to model, simulate, and optimize adsorption processes for more efficient and sustainable water treatment.

Contents:

Intro

Cover

Half Title

Title Page

Copyright Page

Contents

Foreword

Preface

Disclaimer

Acknowledgements

Chapter 1: (Waste)water treatment

1.1 INTRODUCTION

1.2 WATER POLLUTION: SOURCES, TYPES, AND EFFECTS

1.2.1 Sources of water pollution

1.2.1.1 Point source

1.2.1.2 Non-point source

1.2.1.3 Transboundary source

1.2.2 Types of water pollution

1.2.2.1 Groundwater pollution

1.2.2.2 Surface water pollution

1.2.3 Effects of water pollution

1.3 MAJOR POLLUTANTS IN WATER

1.3.1 Heavy metal ions

1.3.2 Nitrates/Nitrites

1.3.3 Geogenic contaminants

1.3.4 Pharmaceuticals and personal care products

1.3.5 Pesticides and herbicides

1.3.6 Dyes

1.3.7 Microbial contaminants

1.4 TECHNIQUES FOR (WASTE)WATER TREATMENT

1.4.1 Physical methods

1.4.2 Chemical methods

1.4.2.1 Neutralisation

1.4.2.2 Adsorption

1.4.2.3 Precipitation

1.4.2.4 Disinfection

1.4.2.5 Ion exchange

1.4.2.6 Advanced oxidation

1.4.3 Biological methods

1.4.3.1 Aerobic treatment techniques

1.4.3.2 Anaerobic treatment represents

1.5 STAGES IN (WASTE)WATER TREATMENT PROCESSES

1.5.1 Preliminary treatment

1.5.2 Primary treatment

1.5.3 Secondary treatment

1.5.4 Tertiary treatment

1.6 SUMMARY

Chapter 2: Adsorption process for wastewater treatment

2.1 INTRODUCTION

2.2 ADSORPTION PROCESS

2.3 FACTORS AFFECTING THE ADSORPTION PROCESS

2.3.1 Contact time

2.3.2 pH

2.3.3 Initial contaminant concentration

2.3.4 Adsorbent dose

2.3.5 Temperature

2.3.6 Presence of other ions

2.3.7 Adsorbent characteristics

2.4 CHARACTERISATION OF ADSORBENTS

2.4.1 Chemical characterisation

2.4.1.1 Ultra-violet-vis spectroscopy

2.4.1.2 Fourier-transform infrared spectroscopy

2.4.1.3 Raman spectroscopy

2.4.1.4 X-ray photoelectron spectroscopy.

2.4.1.5 X-ray absorption scattering

2.4.1.6 Energy-dispersive X-ray spectroscopy

2.4.1.7 Ultimate analysis

2.4.1.8 Zeta potential

2.4.1.9 Solid-state nuclear magnetic resonance

2.4.2 Physical characterisation

2.4.2.1 X-ray diffraction

2.4.2.2 Scanning electron microscopy/field emission scanning electron microscopy

2.4.2.3 Transmission electron microscopy

2.4.2.4 Atomic force microscopy

2.4.2.5 Surface area and porosimetry

2.4.2.6 Value stream mapping

2.4.2.7 Dynamic light scattering

2.4.3 Thermal characterisation

2.5 CLASSIFICATION OF THE ADSORPTION PROCESS

2.5.1 Type of interactions

2.5.1.1 Physical adsorption or physisorption

2.5.1.2 Chemical adsorption or chemisorption

2.5.2 Mode of operation

2.5.2.1 Batch adsorption

2.5.2.2 Continuous fixed-bed adsorption

2.6 EMPIRICAL ADSORPTION PROCESS MODELS

2.6.1 Adsorption isotherms

2.6.2 Adsorption kinetics

2.6.2.1 Pseudo-first-order models

2.6.2.2 Pseudo-second-order models

2.6.3 Adsorption thermodynamics

2.7 COMPUTATIONAL MODELLING, SIMULATION, AND OPTIMISATION OF THE ADSORPTION PROCESS

2.8 SUMMARY

Chapter 3: Computational techniques for simulation and optimisation of adsorption processes

3.1 INTRODUCTION

3.2 HIERARCHICAL MODELLING OF ADSORPTION PROCESSES

3.2.1 Molecular-level modelling

3.2.2 Mesoscale and macroscale modelling

3.3 OVERVIEW OF COMPUTATIONAL METHODS

3.3.1 Density functional theory calculations

3.3.2 Molecular dynamics and grand canonical Monte Carlo simulations

3.3.3 Quantitative structure-property relationship analysis

3.3.4 Artificial intelligence and machine learning

3.3.5 Process simulation and optimisation

3.4 CHALLENGES IN USING COMPUTATIONAL TOOLS IN THE ADSORPTION PROCESS

3.4.1 Learning and reproducibility challenges

3.4.2 Data challenges.

3.4.3 Benchmarking and validating challenges

3.4.4 Result comparison challenges

3.4.5 Explainability challenges

3.5 RECENT ADVANCES IN COMPUTATIONAL TOOLS

3.6 SUMMARY

Chapter 4: Density functional theory calculations for the adsorption process

4.1 INTRODUCTION

4.2 HISTORY AND EARLY DEVELOPMENTS

4.3 DENSITY FUNCTIONAL THEORY

4.3.1 Exchange-correlation energy

4.3.2 Spin polarisation

4.3.3 Dispersion corrections

4.3.4 Hybrid functionals

4.4 DENSITY FUNCTIONAL THEORY CALCULATION FOR ADSORPTION INTERACTIONS

4.4.1 Adsorption energy

4.4.2 Distance between two atoms

4.4.3 Frontier molecular orbitals

4.4.4 Mulliken and natural charges

4.4.5 Reactivity descriptors

4.4.6 Recovery time

4.4.7 Distortion energy

4.4.8 Charge density difference

4.4.9 Spin density

4.4.10 Density of states

4.4.11 Geometry optimisation

4.5 SOFTWARE PACKAGES FOR DENSITY FUNCTIONAL THEORY COMPUTATIONS

4.6 CASE STUDIES

4.6.1 Case study I: Adsorption of pesticides on boron nitride nanosheets

4.6.2 Structural properties

4.6.2.1 Adsorption energy and recovery time

4.6.2.2 Electronic properties

4.6.2.3 Reactivity descriptors

4.6.2.4 Reduced density gradient scatter and non-covalent interaction plots

4.6.3 Case study II: Adsorption of pharmaceutical and personal care products on graphene, boron nitride, and boron carbon nitride nanosheets

4.6.3.1 Structural properties

4.6.3.2 Adsorption energy and recovery time

4.6.3.3 Electronic properties

4.6.3.4 Reactivity descriptors

4.6.3.5 Reduced density gradient scatter and non-covalent interaction plots

4.7 SUMMARY

Chapter 5: Molecular dynamics and grand canonical Monte Carlo simulations of adsorption processes

5.1 INTRODUCTION

5.2 HISTORY AND EARLY DEVELOPMENTS

5.3 FUNDAMENTALS OF MOLECULAR SIMULATIONS.

5.3.1 Statistical mechanics and ensembles

5.3.1.1 Microcanonical ensemble (NVE)

5.3.1.2 Canonical ensemble (NVT)

5.3.1.3 Isothermal-isobaric ensemble (NPT)

5.3.1.4 Grand canonical ensemble (.µ.VT)

5.3.2 Molecular dynamics: theory and algorithms

5.3.2.1 Integration of equations of motion

5.3.2.2 Sampling dynamic properties

5.3.3 Monte Carlo and grand canonical Monte Carlo methods

5.3.3.1 Metropolis algorithm and importance sampling

5.3.3.2 Grand canonical Monte Carlo for adsorption studies

5.4 INTERATOMIC POTENTIALS AND FORCE FIELDS

5.4.1 Bonded interactions: bonds, angles, torsions

5.4.1.1 Bond stretching

5.4.1.2 Angle bending

5.4.1.3 Dihedral (torsional) rotations

5.4.2 Non-bonded interactions: van der Waals and electrostatics

5.4.2.1 van der Waals interactions

5.4.2.2 Electrostatic interactions

5.4.3 Long-range treatments: Ewald summation and particle mesh Ewald

5.4.4 Specialised force fields for adsorption systems

5.5 MODELLING ADSORBENTS AND FLUIDS

5.5.1 Structural models of adsorbents

5.5.1.1 Zeolites, carbons, metal organic frameworks, covalent organic frameworks, 2D materials

5.5.1.2 Introducing functional groups and defects

5.5.2 Water and solvent models

5.5.2.1 SPC, TIP3P, TIP4P, SPC/E

5.5.2.2 Polarisable and advanced water models

5.6 SIMULATION WORKFLOWS AND ANALYSES

5.6.1 Molecular dynamics workflows

5.6.1.1 System preparation and solvation

5.6.1.2 Equilibration, production runs, data sampling

5.6.1.3 Analysis: radial distribution function, mean-squared displacement, coordination numbers

5.6.2 Grand canonical Monte Carlo workflows

5.6.2.1 Setting chemical potential and temperature

5.6.2.2 Adsorption isotherms and heat of adsorption

5.6.2.3 Multi-component and competitive adsorption.

5.7 ADVANCED SIMULATION TECHNIQUES: HYBRID MOLECULAR DYNAMICS-GRAND CANONICAL MONTE CARLO APPROACHES

5.8 SOFTWARE PACKAGES FOR MOLECULAR DYNAMICS AND GRAND CANONICAL MONTE CARLO SIMULATIONS

5.9 CASE STUDIES

5.9.1 Case study I

5.9.1.1 Adsorption system

5.9.1.2 Radial distribution function

5.9.1.3 Mean-squared displacement

5.9.1.4 Potential mean force

5.9.2 Case study II

5.9.2.1 Adsorption system

5.9.2.2 Radial distribution function

5.9.2.3 Mean-squared displacement

5.10 SUMMARY

Chapter 6: Quantitative structure-property relationship analysis of adsorption processes

6.1 INTRODUCTION

6.2 HISTORY AND EARLY DEVELOPMENTS

6.3 QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIP ANALYSIS

6.3.1 Basic concepts

6.3.2 Principles underpinning quantitative structure-property relationship

6.3.3 Molecular descriptors

6.3.3.1 1D descriptors

6.3.3.2 2D descriptors

6.3.3.3 3D descriptors

6.3.3.4 Electronic descriptors

6.3.3.5 Thermodynamic descriptors

6.4 MODEL DEVELOPMENT WORKFLOW AND BEST PRACTICES FOR QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIP MODELLING

6.4.1 OECD principles

6.4.2 Data considerations

6.4.3 Descriptor selection

6.4.4 Validation methods

6.4.5 Multitask modelling

6.4.6 Applicability domain and predictive reliability

6.4.7 Interpretability

6.5 QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIP MODELLING OF ADSORPTION PROCESSES

6.5.1 Adsorbent and adsorbate specifics

6.5.2 Types of molecular descriptors in adsorption studies

6.5.3 Steps in developing quantitative structure-property relationship for adsorption

6.6 ADVANCED MODELLING APPROACHES

6.6.1 Hybrid and consensus models

6.6.2 Machine learning across adsorbent classes

6.6.3 Defect and stability considerations

6.7 SOFTWARE PACKAGES FOR QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIP ANALYSIS.

6.8 SUMMARY.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9781789063943

OCLC:

1553872026