Author Archives: Ageo Meier de Andrade

eSSENCE-EMMC Multiscale Modelling Meeting 2021 – 7-8 June on Zoom

The “eSSENCE-EMMC Multiscale Modelling Meeting 2021 – physics-based and data-driven” will be an online meeting held online 7- 8 June 2021. Registration is open! The program consists of five key-note talks followed by Q/A sessions, an e-poster session (no abstract needed), invited talks, and a panel discussion. Posters (with or without oral microspresentations) need to be registered by 1 June. All information is found at

Georg Kresse (Professor, University of Vienna, Austria)
“Finite temperature properties with first principles accuracy, is machine learning the way to go?”

Anders Hagfeldt (Professor, Vice-Chancellor, Uppsala University, Sweden)
“The nanoscience of solar power: observations from experiment and (some) insights from theory”

Julia Contreras-García (Professor, CNRS – Paris, France)
“Revealing intermolecular interactions, ionic and covalent bonding from the reduced density gradient and other tools”

Olle Häggström (Professor, Chalmers University of Technology, Sweden)
“AI and the Algorithms that govern your life (for better or worse)”

Alejandro A. Franco (Professor, Université de Picardie Jules Verne, France)
“Battery processes: Modelling at the coarse-grained and continuum levels”

Kersti Hermansson, Peter Broqvist and the rest of the organizing team
Uppsala University

Thermodynamics of dissociated water motifs at oxide-bulk water interfaces: The TiO2 anatase (0 0 1) case

Authors: Giuseppe Zollo, Kersti Hermansson, and Lorenzo Agosta

Water on metal oxides interfaces generate a variety of ordered motifs that depend on the structural properties of the exposed solid surfaces. Here we emphasize the importance of considering the thermodynamic state of the surrounding liquid to find the interface structures in real systems. In particular, using ab initio molecular dynamics, we have studied the thermodynamic behavior of the water induced reconstructed (WIR) anatase (0 0 1) surface under full hydration. The long standing issue of the reconstruction symmetry in this facet of the anatase, that is the TiO2 stable phase at the nanoscale, is addressed showing that the stable state for a WIR surface in vacuum and in bulk water are different, the latter depending on the thermodynamic state of the system. Thermally activated surface phase transitions between (2×4) and (2×3) symmetries are lead by the surface relaxation caused by the molecular adsorption and release phenomena at the interface. Our approach enables the validation to aqueous environment of surface-confined water structures derived in vacuum, emphasizing the role of the thermodynamics conditions for characterizing solid-liquid interfaces especially for nano sized systems.

Applied Surface Science, 550, 2021, 149354

Supercooled liquid-like dynamics in water near a fully hydrated titania surface: Decoupling of rotational and translational diffusion

Authors: Lorenzo Agosta, Mikhail Dzugutov, and Kersti Hermansson

We report an ab initio molecular dynamics (MD) simulation investigating the effect of a fully hydrated surface of TiO2 on the water dynamics. It is found that the universal relation between the rotational and translational diffusion characteristics of bulk water is broken in the water layers near the surface with the rotational diffusion demonstrating progressive retardation relative to the translational diffusion when approaching the surface. This kind of rotation–translation decoupling has so far only been observed in the supercooled liquids approaching glass transition, and its observation in water at a normal liquid temperature is of conceptual interest. This finding is also of interest for the application-significant studies of the water interaction with fully hydrated nanoparticles. We note that this is the first observation of rotation–translation decoupling in an ab initio MD simulation of water.

J. Chem. Phys. 154, 094708 (2021)

Curvature Constrained Splines for DFTB Repulsive Potential Parametrization

Authors: Akshay Krishna Ammothum Kandy, Eddie Wadbro, Balint Aradi, Peter Broqvist, and Jolla Kullgren 

The Curvature Constrained Splines (CCS) methodology has been used for fitting repulsive potentials to be used in SCC-DFTB calculations. The benefit of using CCS is that the actual fitting of the repulsive potential is performed through quadratic programming on a convex objective function. This guarantees a unique (for strictly convex) and optimum two-body repulsive potential in a single shot, thereby making the parametrization process robust, and with minimal human effort. Furthermore, the constraints in CCS give the user control to tune the shape of the repulsive potential based on prior knowledge about the system in question. Herein, we developed the method further with new constraints and the capability to handle sparse data. We used the method to generate accurate repulsive potentials for bulk Si polymorphs and demonstrate that for a given Slater-Koster table, which reproduces the experimental band structure for bulk Si in its ground state, we are unable to find one single two-body repulsive potential that can accurately describe the various bulk polymorphs of silicon in our training set. We further demonstrate that to increase transferability, the repulsive potential needs to be adjusted to account for changes in the chemical environment, here expressed in the form of a coordination number. By training a near-sighted Atomistic Neural Network potential, which includes many-body effects but still essentially within the first-neighbor shell, we can obtain full transferability for SCC-DFTB in terms of describing the energetics of different Si polymorphs.

J. Chem. Theory Comput. 2021, 17, 3, 1771–1781

Annual eSSENCE multiscale modelling meeting went digital in 2020

The adversities with covid-19 also brought the chance to re-think how conferences could still happen worldwide. It was not different from the 2020 eSSENCE Multiscale modelling of molecules in materials meeting on the 8th of June this year, the first time the conference was broadcasted to 599 registered participants from 51 countries in all continents.

From a conventional conference to a modern webinar

Kersti Hermansson, Professor in Inorganic Chemistry at Uppsala University and the main conference organizer, shared what kind of decisions were needed to make the conference happen.
Kersti: “In the midst of our planning for the June 2020 meeting, the consequences of the Corona pandemic hit us, and we had to decide whether to postpone, skip or pursue the conference plans. After some deliberation we opted for the latter, checked the willingness of the speakers to switch to webinar mode, sent out a new set of announcements to all the forums already contacted, and – most of all –we had to learn all the technical bits and pieces needed to run a smooth online meeting, which was totally new to all members of our research group”.

Professor Hermansson emphasizes the wish to arrange the conference with high interaction from the participants. “Overall, our philosophy was to make the online conference as similar as possible to our “normal” eSSENCE conferences in previous years. That is, we wanted to try to include all the same scientific ingredients as usual: keynote presentations of international authorities, invited talks, a presentation from the eSSENCE coordinator, poster session, panel discussion, vivid discussions, and the conference was as usual run from the Siegbahn Hall at the Ångström Laboratory, now with 15 sparse participants on-site to create the “ambiance” of an IRL meeting.

Figure. The Siegbahn Hall during the eSSENCE conference

The participants were from all over the globe, from both industry and universities

Over 210 academic institutions and 78 companies were represented at the conference. Among industrial participation, which accounted for 20% of the registered participants, companies such as Johson Matthey, Dassault Systemes, BIOVIA, AstraZeneca, Northvolt AB and many others were active during the scientific discussions, the poster session and panel discussion. 
The eSSENCE multiscale modelling meeting has built up some national recognition over the years, as evidenced by broad participation over the country. This year’s Swedish participation came from eSSENCE, from SeRC (SU, KTH, LiU), from e-science communities at CTH and GU, as well as from Högskolan in Gävle, Malmö Högskola, Örebro University and the Technical University of Luleå. As usual, eSSENCE@Lund was much supportive in the planning, and Magnus Ullner (LU) also took part in the implementation of the panel discussion.

Figure.Geographical distribution of the ~600 registered participants

The eSSENCE of complex systems

The conference’s main scientific topic in 2020 was “Multiscale modelling of materials and molecules ? in complex systems”, with the overall focus on methods and model development. The computational aspects of two large new European programmes were highlighted in the programme. Multiscale modelling in battery research was the topic of the first keynote lecture given by Professor Tejs Vegge from the Technical University of Denmark, one of Battery 2030+ research initiative leaders. Data-driven approaches of multiscale modelling were the main topic of the other two keynote lectures. Professor Anatole von Lilienfeld from the University of Base discussed the scientific community’s efforts on coupling data science, alchemy, and quantum machine learning. Professor Peter Coveney from University College London gave a fascinating lecture entitled “Big data: The end of the scientific method?” 
With the notable success of the conference, the organizers plan to keep the digital format for 2021. The organizers plan a 2-day conference, and a limited number of in-person attendance is being considered. Stay tuned for more information!

Phonon-Assisted Hot Carrier Generation in Plasmonic Semiconductor Systems

Authors: Yocefu Hattori, Jie Meng, Kaibo Zheng, Ageo Meier de Andrade, Jolla Kullgren, Peter Broqvist, Peter Nordlander, and Jacinto Sá

Plasmonic materials have optical cross sections that exceed by 10-fold their geometric sizes, making them uniquely suitable to convert light into electrical charges. Harvesting plasmon-generated hot carriers is of interest for the broad fields of photovoltaics and photocatalysis; however, their direct utilization is limited by their ultrafast thermalization in metals. To prolong the lifetime of hot carriers, one can place acceptor materials, such as semiconductors, in direct contact with the plasmonic system. Herein, we report the effect of operating temperature on hot electron generation and transfer to a suitable semiconductor. We found that an increase in the operation temperature improves hot electron harvesting in a plasmonic semiconductor hybrid system, contrasting what is observed on photodriven processes in nonplasmonic systems. The effect appears to be related to an enhancement in hot carrier generation due to phonon coupling. This discovery provides a new strategy for optimization of photodriven energy production and chemical synthesis.

Nano Lett. 2021, 21, 2, 1083–1089

Lignin Intermediates on Palladium: Insights into Keto‐Enol Tautomerization from Theoretical Modelling

Authors: Ageo Meier de Andrade, Pemikar Srifa, Peter Broqvist, and Kersti Hermansson

It has been suggested in the literature that keto‐to‐enol tautomerization plays a vital role for lignin fragmentation under mild conditions. On the other hand, previous modelling has shown that the adsorbed keto form is more stable than enol on the Pd(111) catalyst. The current density functional theory study of lignin model molecules shows that, in the gas‐phase, keto is more stable than enol, but on the Pd surface, we find enol conformers that are at least as stable as keto. This supports the experimental result that the favourable reaction pathway for lignin depolymerization involves keto‐enol tautomerization. An energy decomposition analysis gives insights concerning the origin of the fine energy balance between the keto and enol forms, where the molecule–surface interaction (−7 eV) and the molecular strain energy (+3 eV) are the main contributors to the adsorption energy.

ChemSusChem, 2020, 13, 6574-6581

CCS: A software framework to generate two-body potentials using Curvature Constrained Splines

Authors: Akshay Krishna A. K., Eddie Wadbro, Christof Köhler, Pavlin Mitev, Peter Broqvist, and Jolla Kullgren

We have developed an automated and efficient scheme for the fitting of data using Curvature Constrained Splines (CCS), to construct accurate two-body potentials. The approach enabled the construction of an oscillation-free, yet flexible, potential. We show that the optimization problem is convex and that it can be reduced to a standard Quadratic Programming (QP) problem. The improvements are demonstrated by the development of a two-body potential for Ne from ab initio data. We also outline possible extensions to the method.

Program summary
Program Title: CCS

CPC Library link to program files:

Developer’s repository link:

Licensing provisions: GPLv3

Programming language: Python

External routines/libraries: NumPy, matplotlib, ASE, CVXOPT

Nature of problem: Ab initio quantum chemistry methods are often computationally very expensive. To alleviate this problem, the development of efficient empirical and semi-empirical methods is necessary. Two-body potentials are ubiquitous in empirical and semi-empirical methods.

Solution method: The CCS package provides a new strategy to obtain accurate two body potentials. The potentials are described as cubic splines with curvature constraints.

Computer Physics Communications, 258, 107602, (2021);

The water/ceria(111) interface: Computational overview and new structures

Authors: Andreas Röckert, Jolla Kullgren, Peter Broqvist, Seif Alwan, and Kersti Hermansson
Thin film structures of water on the CeO2(111) surface for coverages between 0.5 and 2.0 water monolayers have been optimized and analyzed using density functional theory (optPBE-vdW functional). We present a new 1.0 ML structure that is both the lowest in energy published and features a hydrogen-bond network extending the surface in one-dimension, contrary to what has been found in the literature, and contrary to what has been expected due to the large bulk ceria cell dimension. The adsorption energies for the monolayer and multilayered water structures agree well with experimental temperature programmed desorption results from the literature, and we discuss the stability window of CeO2(111) surfaces covered with 0.5–2.0 ML of water.

Quantitative and qualitative performance of density functional theory rationalized by reduced density gradient distributions

Authors: Ageo Meier de Andrade, Jolla Kullgren and Peter Broqvist 

We evaluate the qualitative and quantitative accuracy of various flavors of density functionals with and without accounting for dispersion corrections. Our test system is nickel in the form of bulk, surfaces, and nanoparticles for which we compute structural properties, bulk cohesive energies, surface energies, and work functions and compare to experimental data. We find that the inclusion of any dispersion, either by an a posteriori correction or by a self-consistent treatment by explicitly computing the nonlocal correlation contribution to the total energy, has a significant effect on the calculated properties and improves the quantitative comparison to experiments. Besides the quantitative agreement, we also investigate qualitative features by comparing Wulff shapes of metal nanoparticles as obtained using the different density functionals. We find that all tested functionals predict similar Wulff shapes for nickel nanoparticles but still have some small differences. These results show that the relative energies calculated using the semilocal GGA and meta-GGA functionals, with and without dispersion, are quite similar. Our findings can also be generalized to other systems when rationalized in terms of the computed reduced density gradients. We find that the distribution of reduced density gradients in a material is correlated to the steepness of the exchange enhancement factor and propose that this information can be used as a quantitative guide when it comes to picking the most appropriate density functional for specific target systems as well as when it comes to extrapolating DFT data to predict experiments.

Phys. Rev. B 102, 2020, 075115