Electrochemical energy storage: Theory meets industry

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If you are interested in attending this event, please visit the CECAM website here.

Workshop Description

1/ Introduction and motivation

How much energy can a device store? How fast can it be charged? These two questions are at the heart of the research on electrochemical energy storage (EES). Two main families of devices coexist: supercapacitors which accumulate the charge at the surface of the electrodes through ion adsorption [1,2], and batteries in which the storage mechanism is based on redox reactions occurring in the bulk electrodes [3]. Li-ion batteries have a high specific energy, keeping cellular phones, laptop and even cars working throughout several hours. For rapid power delivery and recharging, i.e. for high specific power applications, supercapacitors are then used.

Due to the recent advances in the field of materials science, the range of applications of EES devices has tremendously increased over the past two decades. The development of systems with improved performances and lower costs, as well as their large-scale production are now considered as vital issues for many countries. This can be seen from the recent creation of networks or institutes that gather academics and industrials, both at the national and European levels [4-6].

Most of the recent breakthroughs have however implied complex materials, often at the nanoscale. It is thus necessary to control the chemistry at the molecular level in all the active components of the devices, i.e. the two electrodes, the electrolytes. The various interfaces also have to be characterized and understood which implies considering potential dependent mechanistic approaches. Over the year, atomistic and molecular simulations have therefore appeared as one of the main keys to success in designing tomorrow’s high-energy and high-power EES devices, in complement with in situ and/or in operando spectroscopy techniques [7,8]. This is now well established in academic laboratories, which are now routinely building consortiums with synthesis, electrochemical and spectroscopic characterizations, together with modeling for developing new materials. However, this habit does not seem to be adopted yet by the industrial companies in the field. The objective of this workshop is therefore to bring together some of the worldwide experts in the field of EES simulations (and in particular the researchers who are developing the corresponding simulation tools) with the interested industrial partners. We hope that such a workshop could help bridging the gap between needs and supply, which would put simulation at the centre of the future industrial developments of EES devices.

2/ State-of-the-art

The state-of-the-art can be considered at two levels: 1/ Simulation methods which are routinely used to simulate EES devices. 2/ Initiatives which are currently undertaken to bring simulation tools and/or results within the reach of non-specialist users.

From the methodological point of view, many different methods are used or developed depending on the nature of the material, the targeted properties and the necessary time/length scales.
-The workhorse for studying the redox activity of bulk electrode materials is standard Density Functional Theory (DFT) since it is necessary to have access to the electronic structure.
-For electrolytes, determining the transport properties involves the use of molecular dynamics. Depending on the availability of correct force fields, classical or DFT-based MD are generally used [7].
-Then further statistics or larger systems are generally studied by using lattice-based methods, such as kinetic Monte Carlo or Lattice Boltzmann.

Generally, standard DFT or MD packages can be used to study bulk materials. However in the case of interfaces, additional difficulties need to be overcome so that several groups are developing specific methodologies and/or simulation packages [9-11].

Despite the large growth in the simulation communities (especially DFT and MD) over the past decades, using these tools often requires lots of efforts for experimentalists and/or engineers in the industry. For this reason, several groups are currently developing user-friendly interfaces, either in specific programs or directly accessible from website [12]. For efficiency reasons, it is necessary to develop high-throughput frameworks and to link these tools with accurate databases [13,14]. This implies that a common language is established between the communities of theorists and experimentalists, in order to build appropriate databases that will be helpful for material designers.

Finally, we should mention that several research groups are developing tools that aim to simulate systems at much larger scales [15,16]. The objective is to provide a direct link with experiments, by directly computing macroscale properties similar to the ones obtained in electrochemistry experiments. Such multi-scale methods, most often based on the Butler-Volmer equation, are typically top-down approaches that aim to account for the material or electrolyte specificity in an effective manner through appropriate parameterizations. Huge efforts are being devoted to the development of bottom-up approaches, with however major issues due to transferability between different scales.

 

References

[1] Simon, P. and Gogotsi, Y. Materials for electrochemical capacitors. Nature Mater., 7, 845 (2008).
[2] Béguin, F., Presser, V., Balducci, A. and Frackowiak, E. Carbons and electrolytes for advanced supercapacitors. Adv. Mater., 26, 2219 (2014).
[3] Armand, M. and Tarascon, J.-M. Building better batteries. Nature, 451, 652 (2008).
[4] RS2E, French network on electrochemical energy storage, http://www.energie-rs2e.com/fr
[5] ALISTORE, European Research Institute, http://www.alistore.eu/presentation
[6] The Faraday Institution, UK’s research institute for electrochemical energy storage, https://faraday.ac.uk/
[7] Cheng, L. et al. Accelerating electrolyte discovery for energy storage with high-throughput screening. J. Phys. Chem. Lett., 6, 283 (2015).
[8] Salanne, M. et al. Efficient storage mechanisms for building better supercapacitors. Nature Energy, 1, 16070 (2016).
[9] https://github.com/bjmorgan/lattice_mc
[10] Dalverny, A.-L., Filhol, J.-S. and Doublet, M.-L. Interface electrochemistry in conversion materials for Li-ion batteries, J. Mater. Chem., 21, 10134 (2011).
[11] Merlet, C., et al. Simulating supercapacitors: can we model electrodes as constant charge surfaces?, J. Phys. Chem. Lett., 4, 264 (2013).
[12] The Materials Project, https://materialsproject.org/press
[13] Jain, A. et al. A high-throughput infrastructure for density functional theory calculations, Comput. Mater. Sci., 50, 2295 (2011).
[14] Curtarolo, S. et al. The high-throughput highway to computational materials design, Nature Mater., 12, 191 (2013).
[15] MS-LiberT simulation package, http://modeling-electrochemistry.com/ms-liber-t/
[16] Farkondeh, M., Pritzker, M., Fowler, M. and Delacourt, C. Mesoscopic modeling of a LiFePO4 electrode: experimental validation under continuous and intermittent operating conditions

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Scientific reports from the 2018 E-CAM workshops are now available on our website

 

The scientific reports* from the following workshops conducted in year 3 of the project E-CAM (2018):

  1. E-CAM Scoping Workshop: “Solubility prediction”, 14 – 15 May 2018, Ecole Normale Supérieure de Lyon, France,
  2. E-CAM Scoping Workshop: “Dissipative particle dynamics: Where do we stand on predictive application?”, 24 – 26 April 2018, Daresbury Laboratory, United Kingdom,
  3. E-CAM Extended Software Development Workshop 11: “Quantum Dynamics”, 18 – 29 June 2018, Maison de la Simulation, France,

are now available for download on our website at this location. Furthermore, they will also be integrated in the CECAM Report of Activities for 2018, published every year on the website www.cecam.org.

 

*© CECAM 2018, all rights reserved.

Please address any comments or questions to info@e-cam2020.eu.

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Scoping workshop: Building the bridge between theories and software: SME as a boost for technology transfer in industrial simulative pipelines

If you are interested in attending this event, please visit the CECAM website here.

Workshop Description

In the computational chemistry/physics realm, statistical mechanics, electronic structure and multiscale modeling are three of the theoretical tools that enable understanding and modelling of physicochemical processes. Within these frameworks, several theoretical/computational methods have been reported in the literature over the last decades. Despite their remarkable value in terms of novel ideas and theories , such approaches are often far from a practical applicability within industrial settings [1]. This is mainly due to the fact that: i) these algorithms are often written in rather inefficient programming languages and therefore not fully optimized for new generation hardware architectures; ii) these methods can be very accurate from the physics standpoint, being however quite far away from the industrial needs of finding a suitable tradeoff between speed and accuracy [2]. Often, it can happen that experiments can paradoxically be faster (even though more expensive) than computational predictions. Therefore, companies in different areas are actively seeking more reliable, still rather fast, computational methods to reduce the overall costs of industrial R&D pipelines. Just to mention a few examples, this is the case for drug discovery, where companies are looking for innovative approaches to accurate kinetics and thermodynamics predictions, and the material industry, where designing new nanostructures with improved features could greatly benefit from computational simulations . There exists, however, a clear and long-lasting gap between the theoretical chemistry/physics community and industries, which are looking for efficient, user-friendly, and professional software solutions to be utilized in many different areas. Against this scenario, small/medium enterprises (SMEs) that develop simulative software can play an increasingly key role in, not only translating the science developed in academia via a proper technological transfer process, but also in building a scientific bridge between the industry requirements in terms of automation and the new theories and algorithms developed at an academic level, where it frequently happens that a systematic and practical exploitation of the algorithms is overlooked. It is crucial to remark that transforming academic algorithms into usable software is not only a matter of software engineering, but often also means reconsidering the original theories and formalisms, as a new algorithm working rather quickly and accurately on a system of a few hundred atoms, will not necessarily be appropriate for more complex systems with huge numbers of degrees of freedom. In this context, software development SMEs, which have a clear mission towards top level science suitable for industrial settings, may represent the missing link in the pipeline from-theory-to-software.

In the present E-CAM workshop we will discuss and dissect some key issues related to the aspects reported above. First, we will try to answer the question: which is the most appropriate propelling element of innovation, top-level academic science or industrial needs of accelerating R&D towards novel and cheaper products? Traditionally, the approach to technology is conceiving technology as a corollary of scientific research. However, there is compelling evidence that for several mid-term projects an industry-requirements-driven approach is largely feasible if not best suited. A tightly connected topic regards on how to match and synchronize curiosity driven research with industrial needs and how to manage the resulting, possibly academic/industrial mixed, intellectual property. Can this ‘engineering’ or ‘politechnique’ approach to science/technology transfer be the way to boost the technological SMEs European tissue? Furthermore, considering the scale at which economical phenomena happen today, in the workshop we will discuss whether European SMEs shall federate or merge and join efforts to reach the critical mass and create a significant reference point in the simulative domain worldwide (the American way?). Interestingly, universities and research centers throughout Europe could be the seeds, the starting glue, for this aggregation process. To reach such goals, the main keyword is coordination among the various CoE in Europe towards a coordinated scientific and technological strategy for the creation of professional software for industries and commercial exploitation.
In this E-CAM workshop, we aim at creating a forum where top-level scientists of E-CAM with expertise in statistical mechanics, multiscale modeling and electronic structure will discuss with representatives of pharmaceutical and material industries with the final objectives to identify the major gaps which still hamper a systematic exploitation of accurate computer simulations in industrial R&D. The presence of SMEs will also be crucial to understand whether potential gaps can be filled by small high-tech companies, with the final objective to define a clear workflow and build a bridge between new theories and professional software solutions. As anticipated, special attention will be given to the role of SMEs devoted to simulative software development. These may be key bridges between the academic developments and the creation of tools and interfaces easily transferrable to industrial partners. SMEs are, however, players with specific needs in the domain of intellectual property, developing a viable business model, and positioning themselves between academic research and industry. These aspects, and the possible relationship with the CoEs will be addressed in the workshop.

[1] Kuhn et al., “A Real-World Perspective on Molecular Design”, J. Med. Chem., 2016, 59 (9), pp 4087–4102

[2] Yibing Shan, Eric T. Kim, Michael P. Eastwood, Ron O. Dror, Markus A. Seeliger, and David E. Shaw. “How Does a Drug Molecule Find Its Target Binding Site?” J. Am. Chem. Soc., 2011, 133 (24), pp 9181–9183

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Scoping workshop: Solubility prediction

If you are interested in attending this event, please visit the CECAM website here.

Workshop Description

E-CAM is a H2020 project that aims to create, develop and sustain a European infrastructure for computational science applied to simulation and modelling of materials and of biologicalprocesses of industrial and societal interest. Building on the already significant network of 15 CECAM centres across Europe and the PRACE initiative, E-CAM creates a distributed centre for simulation and modelling across the electronic, molecular and continuum length scales. The
center builds on the considerable European expertise and capability in this area of significant industrial and scientific relevance. The objective is to make a very strong impact on the European economy through the development of a key industrial capability in the rapidly developing area of technological innovation through computer modelling.
The ambitious goals of E-CAM will be achieved through three complementary instruments: the development, testing, maintenance, and dissemination of software targeted at end-user needs. It will also provide an environment for the long-term optimisation and maintenance of academic codes and will help to ensure that, in future, these codes are properly exploited by industry.
CECAM will provide two scoping workshops per year. These will ensure a strong connect with our industrial partners. One of the two workshops will be broad in scope, allowing industrial partners from different sectors to interact and to discuss new pilot projects across all of the four scientific work packages of E-CAM. The second workshop will be deep, concentrating on one or two scientific areas of particular interest to a number of our partners.
At the Mainz scoping workshop in September 2016, industrial partners expressed a strong interest in the problem of the calculation of the prediction of solubility and this will be the subject of this scoping workshop.

It has been reported that over 75% of drug development candidates have low solubility based on the Biopharmaceutics Classification System (BCS). An increasing trend towards low solubility is a major issue for drug development as formulation of low solubility compounds can be problematic. Despite tremendous efforts, a definitive accurate and comprehensive approach to predicting solubility has proven elusive. Consequently, there have been a number of attempts to probe changes in solubility as a function of structural changes in specific classes of molecules as well as systematic approaches looking at matched molecular pairs to determine improved solubility as a function of inferred crystal packing disruption. The focus of this workshop could be on the tools that allow an unprecedented deconstruction of the relative importance of molecular solvation and crystal packing on solubility. Recent work includes a systematic experimental approach to examine key thermodynamic functions such as sublimation and hydration properties as a function of structural modifications and a comprehensive computational approach to lattice energy estimation from molecular descriptors. A recent review has analysed simple predictive methods for the estimation of aqueous solubility and the specific use of a chemical informatics and theory to predict the solubility of drug like molecules [1]. A recent paper highlights the potential of these approaches and the attempts to build scientific bridges across the two communities. The paper [2] uses co-crystals to optimise the dissolution rate of a psychotropic drug with known dissolution challenges.

Algorithms for solubility calculations have been carried out by two different general approaches [3]:

(1) the thermodynamic approach (of seeking the concentration at which the electrolyte chemical potential, in solution, is equal to that of the pure solid (2) a direct coexistence approach in which the solution is equilibrated with a solid configuration (typically either a slab or a selected crystal environment) and the electrolyte concentration in the solution phase sufficiently far from the crystal surface is taken to be the solubility [4].

The algorithms for the calculation of solubility will be examined in detail at the workshop. Essentially, the chemical potential of a salt, in the solid phase is given by Gibbs free energy per molecule, which in turn is related to the Helmholtz free energy of the solid estimated using the Einstein model and the molar volume of the solid at a fixed pressure, which can be determined by performing constant-NpT simulations of the solid at room temperature. The chemical potential of the solution can be calculated from the derivative of the Gibbs free energy of solution with respect to the number of molecules, The Gibbs free energy can be estimated using a coupling parameter method combined with a technique such a MBAR or WHAM [5]. The derivative is calculated numerically by performing a number of simulations at different solute concentrations. The solubility limit is obtained when the chemical potential of the solution and the solid are equal.

In the complementary area of structure activity relationships [6], we will discuss automatic model generation process for building QSAR models using Gaussian Processes, a powerful machine learning modeling method. We will examine the stages of the process that ensure models are built and validated within a rigorous framework: descriptor calculation, splitting data into training, validation and test sets, descriptor filtering, application of modeling techniques and selection of the best model. We will explore the effectiveness of the automatic model generation process for two types of data sets commonly encountered in building ADME QSAR models, a small set of in vivo data and a large set of physico-chemical data.

References

[1] D. Elder and R. Holm, Int. J. Pharm., 453, 3-11 (2013)
[2] D. Elder, R. Holm, R. de Diego, H. Lopez, Int. J. Pharm., 453, 88-100,(2013).
[3] I. Nezbeda, F. Moucka and W. R. Smith, Molecular Phys, 1665-1690 (2016).
[4] J. L. Aragones, E. Sanz, and C. Vega, J., Chem. Phys. 136, 244508 (2012).
[5] R. Gozalbes, , A. Pineda-Lucena, Bioorg Med Chem, 18, 7078–7084, (2010).
[6] J. Shaoxin Feng and Tonglei Li, J. Chem. Theory Comput., 2, 149-156 (2006).

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Scoping workshop: Dissipative particle dynamics – Where do we stand on predictive application?

If you are interested in attending this event, please visit the CECAM website here.

Workshop Description

Dissipative particle dynamics (DPD) has seen widespread uptake since its inception as a relatively simple and inexpensive coarse-grained modeling tool ideally suited to the study of soft condensed matter systems. DPD is perhaps unusual in that its development has been driven as much by the needs of industry as by academic research. We anticipate significant industrial participation, therefore we propose to allocate plenty of space to address industrial relevant use-cases in the proposed program (note that two of the organizers are from industry). Despite the scientific advances and the early industrial applications, there remain several open questions both in the foundations of the method and in advanced applications, (some of which are listed below) that prevent the method being used in a predictive fashion in an industrial setting.

We propose to bring together the leaders in the field to ask the question, where can DPD offer predictive insight currently, and what is required to improve the method and application to enable improved predictive capability in the future? We aim to share insights, identify approaches to solve key challenges, and hone the ongoing active research programme. A key driver of the workshop is also to maintain a close community in this field across academia and industry, necessary to move the field forwards. Note that the agenda of this workshop has been drafted to be in line with the E-CAM scoping workshop activities.

We aim to spend some time discussing the software landscape that supports the DPD community on the final day in the style of an E-CAM workshop and will touch upon where extreme scale computing can contribute. This is to ensure that the world-leading researchers in this field have are backed up by high quality software that is fit for purpose and to begin to bring the scientific leaders together with the leading software developers. Note that two members of the organizing committee are directly involved with the E-CAM project, respectively as Supervisor and Member of the Executive Board.

This proposal follows on from an earlier workshop held in 2014 “Dissipative particle dynamics: foundations to applications”. This workshop brought the community together for the first time since 2008 to identify and to discuss the challenges in the field. Topics such as “Is a consensus emerging about how to parameterize the method?” and using DPD to couple between atomistic and continuum length scales were discussed with great interest. The community identified a number of key areas for future development with specific emphasis on the fact that DPD should begin to move from a descriptive to predictive method over the next few years. Hence the focus of the current proposal. In 2018 four years will have passed since the previous workshop, in this time there have been a number of exciting developments in the parameterization of the DPD model and in the sophistication of the applications tackled with the method. We propose that now is a good time for the community to come together, supported by a CECAM workshop, to ask the question – is DPD moving to a predictive modeling and simulations tool for academics and industrial application.

Challenges

Some key barriers exist to applying DPD as a predictive model:

● Do robust parameterization methods exist that enable predictive simulations?
● Can such coarse-grained potentials be extended to different families of compounds or are they molecule/system-dependent?
● Is the application of electrostatics in DPD solved or not?
● How do we treat solvents of different nature?
● Do many-body method play an important role in predictive applications?
● What is the real computational gain in DPD? Time and length scales?
● Many industrial applications of DPD involve interactions with surfaces, can DPD provide realistic representation of these?
● Does the software exist to support predictive simulations?
● Do we have analytics to extract appropriate data from simulations, e.g., viscosity

Outputs

We would like to ensure the workshop is more than just a collection of talks. To this end we will to identify two or three key challenges and construct a roadmap to approaching them. This roadmap would form the basis for further meetings to discuss progress of those key challenges, e.g., a UK-based meeting hosted by CCP5 in 2019 with both academic and industrial participation.

Without prejudicing the outcome we expect that one of the challenges will be a consensus on parameterization methodology. A second key challenge could be focused towards a particular application area, for example surfactant phase science, rheology, interfacial structures, etc.

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Scoping Workshop: From the Atom to the Molecule

If you are interested in attending this workshop, please visit the CECAM website bellow.

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E-CAM Scoping Workshop: Simulation and Modelling in Industry

The meeting has been especially designed for industry and will focus on three main areas, providing:

  1. a) A detailed account of the state of the art our key areas of simulation and of data-driven modelling
  2. b) A discussion of the direction of the E-CAM project in years 2 and 3 to ensure that the project is addressing the needs of our industrial partners
  3. c) A forum for sharing best practices in simulation and modelling in industrial environments, including considerations of hardware and robust software.
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