La modellistica molecolare per il design dei materiali

Massimo Celino Unità Tecnica Tecnologie dei Materiali Laboratorio Metodologie Diagnostiche ENEA, C. R. Casaccia, Roma

Computational MAterials Science and Technology Lab CMAST Laboratory : www.afs.enea.it/project/cmast

Inagurazione CRESCO4

ENEA, C. R. Portici 12.3.2014

Cristallo di TiO2

Peptide ingegnerizzato su nanotubo di carbonio

Laboratorio Virtuale

CMAST

www.afs.enea.it/project/cmast

La comunità di utenti CRESCO e loro partner formano un laboratorio virtuale dove sono condivise attività, codici, pubblicazioni, competenze etc.

STAFF ENEA-UTICT • Silvio Migliori • Giovanni Bracco • …… • ……

Laboratorio Virtuale CMAST

Caterina Arcangeli UTTMAT-DIAG

Francesco Buonocore UTTMAT-DIAG

Massimo Celino UTTMAT-DIAG

Roberto Grena UTRINN-PCI

Gianluca De Marzi Superconductivity Division

Simone Giusepponi UTICT-HPC

Pasquale Morvillo UTTP-FOTO

Partner non ENEA italiani

Università di Salerno Università di Camerino Università Tor Vergata Università La Sapienza Campus Biomedico Enginsoft Micron ……

Partner non ENEA stranieri

Università Bandung, Indonesia Università Zurigo, Svizzera CNRS – Francia Centro Ricerche Julich, Germ. Ik4-Tekniker - Spagna ORNL – USA Università Dallas – USA ......

ENEA Staff per le applicazioni ENEA Staff: System managers

La Dinamica Molecolare

Calcolo delle distanze tra gli atomi

Calcolo delle forze

Configurazione iniziale

Spostamento degli atomi

Calcolo delle grandezze fisiche

Scrittura del restart

Cristallo di TiO2

O

Ti

Grandezze fisiche e chimiche: energie di formazione e legame, grandezze strutturali, elettroniche ed ottiche

La modellistica molecolare permette di studiare

Biomolecole

Materiali

zig-zag edge armchair edge

Nanotechnologie

La modellistica molecolare

Interfaccia tra ferro (grigio) e piombo liquido (nero). In rosso gli atomi di ossigeno

Grafene

fosfofruttochinasi, enzima implicato nella glicolisi

Solfuro di Cadmio

2012

EU Brochure

Attività e progetti europei

Attività e progetti europei

Numero di progetti FP7 NMP che hanno utilizzato la modellistica numerica per lo studio dei materiali

Attività e progetti europei

Nuovi modeling tools

NMP 20 – 2014: Widening materials models NMP 23 – 2015: Novel materials by design for substituting critical materials: Proposals are called for to investigate the development of such materials by rational design, with focus on the combination of theory with large-scale computational screening. Validation by experimental methods should be included.

NMP 19 – 2015: Materials for severe operating conditions, including added-value functionalities: Projects should include appropriate numerical tools (e.g. density functional theory, molecular dynamics) to capture the multi-scale evolution of damage; and predictive modelling tools for materials operating in extreme environments NMP 22 – 2015: Fibre-based materials for non-clothing applications: Dedicated multiscale modelling and characterisation, and standardisation or the production of (certified) reference materials may also be addressed.

Supporto per attività sperimentali e tecnologiche

Horizon2020

FP7 NMP

Attività e progetti europei

The reason why industry uses modelling: • BASF uses these models for rapid screening and simulated tests of quantum chemistry (reaction mechanisms, kinetics, photo-physics, new chemistries),

complex liquid mixtures (formulations) and organic semiconductor properties (e.g. exciton or charge carrier mobilities).They are working on homogeneous and heterogeneous catalysis (mainly quantum chemistry)

• BMW wants to reduce development time, development cost and hardware for testing.

• DOW uses materials modelling going from molecular structure to processing and end-use properties, and back. They do fundamental modelling of reaction mechanisms, rheology, interfacial behaviour and selfassembly; rational design of formulations.

• INNOVENT uses modelling as it is often the only available mean to understand intrinsic properties and behaviour of magnetic, optical and semiconducting materials and it saves time and money when designing new device prototypes.

• JOHNSON-MATTHEY uses modelling to aid understanding and guide experimental work. Simulation offers a faster and cheaper method of designing systems, than an experimental "traial and error" approach. JOHNSON-MATTHEY does simulations of new alloys for fuel cell and electronic applications. They also do modelling of chemical reactions to predict the reactivity of their catalysts. These models can locate molecules within porous materials and provide understanding of diffusion and adsorption. This is used for automotive emissions after treatment systems and emission control catalysts.

• LYONDELL-BASELL predicts final product properties and performance with modelling. They also limit experimental cost and minimize time to develop new products, understand and control industrial processes.

• MERCK predicts specific material properties as a form of pre-screening. uses materials models for the estimations of electronic energy levels (e.g. HOMO / LUMO) in molecules / polymers.

• OERLIKON predicts the effect of the transmission system design on vehicle performance and energy efficiency with modelling.

• PHILIPS uses models to understand the underlying physics of devices and processes; to optimize product designs and processes, to shorten development and qualification time and to decrease the time-to-market.

• RISK-TECHNOLOGIES use multi-scale modelling of corrosion protection for new materials, testing and optimisation of new materials and new devices.

• SOLARONIX states that modelling helps to optimize solar equipment. Modelling helps screening new materials by discarding the ones that are not compatible seen their energetic levels.

• TOTAL uses modelling to understand the behaviour of certain materials under well-controlled conditions and to study physic-chemical properties of compounds, thermodynamics, CO2 storage, new active compounds (polymers and lubricants, etc.) for interface activities

• VOLKSWAGEN is using modelling to get a deeper insight into the battery cell behaviour.

• RISK-TECH uses dedicated Molecular Dynamics, Dissipative Particle Dynamics, Computational Fluid Dynamics, continuum mechanics, fluid-structure interaction software for simulated test of new materials and as the software allows optimising of the fitting parameters they can determine the optimal material characteristics. They analyse the effect of varying the nanocontainers fillings, particle-particle interactions, diffusivity parameter and the localization of the particles into the scratch. These findings provide guidelines for formulating nanocomposite coatings that effectively heal the surfaces through the self-assembly of the particles into the defects.

Benchmark Dinamica Molecolare su CRESCO4

Codice LAMMPS

Sistema: PdH

Pd H

Codice di Dinamica Molecolare classica LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator, http://lammps.sandia.gov)

Materiali per il nucleare: Corrosione da Pb liquido

Dall’esperimento al modello

L’effetto dell’ossigeno sciolto nel Pb liquido

“Inhibition of iron corrosion in high temperature stagnant liquid lead: A molecular dynamics study ”, A.Arkundato, Z.Suud, M.Abdullah, W.Sutrisno, M.Celino, Annals of Nuclear Materials 62 (2013) 298.

50000 atomi Codice Moldy

Materiali per l’accumulo di idrogeno

Thanks to Amelia Montone,

ENEA TEPSI Project

Dall’esperimento al modello

T= 700 K

Catalizzatore: T= 400 K

DFT model of hydrogen desorption from MgH2: The role of iron catalyst, S.Giusepponi, M.Celino, Int. J. Hydrogen Energy (2013).

L’interfaccia è studiata a diverse temperature e con diversi catalizzatori. Si misura la diffusione dell’idrogeno, le energie di formazione dei difetti e si determina il ruolo del catalizzatore

MgH2 Mg

Crescita del Grafene (Flagship Grafene)

Crescita di grafene su rame

Un foglio di rame viene inserito nel formo per la chemical vapor deposition process

Dall’esperimento al modello

1 2 3 4 5 6 7

-0.015

-0.010

-0.005

0.000

Ad

he

sio

n E

ne

rgy (

eV

/Å^2

)

graphene-surface (average) distance (Å)

LDA

Energia di adesione rame-grafene

Densità di carica e dipolo all’interfaccia

-15

-10

-5

0

5

10

En

erg

y (

eV

)

M K

Struttura a bande del grafene

Struttura a bande del grafene

F. Buonocore et al. Sottomesso (2014)

Dinamica Molecolare Classica è utilizzata per studiare come

aderisce un peptide su una superficie inorganica. Peptide

ingegnerizzato su superficie (101) di TiO2 nella fase anatase.

crystalline structure.

La dinamica mostra quali sono gli aminoacidi coinvolti

nell’adesione. Codice utilizzato GROMACS (version 4.5.4).

META Project, FP7 Marie Curie. Collaborazione con Tor Vergata e ORNL (USA)

1 microsecond trajectory Peptide 206 atoms 8000 water molecules 100 mM NaCl = 24771 atoms 72 cores (Oak Ridge National Labs) performance: 63 ns/day

Biomolecule: Peptidi ingegnerizzati on TiO2 surfaces

Organic functionalization of metal oxide surfaces: an atomic scale modeling approach C.Arcangeli, I.Borriello, G.Gianese, M.Celino, P.Morales, Nanosci. Nanotechnol. Lett. 5, 1147-1154 (2013).

Biomolecules: Virus-like particles (VLP)

Funzionalizzazione della superficie con epitopi per regolare la risposta immunologica: ottimizzazione e criteri di stabilità tramite Dinamica Molecolare

Arcangeli C. et al. J. Biomol. Struct. Dyn 2013 (DOI:10.1080/07391102.2013.785920)

Gli atomi sono colorati a seconda della loro esposizione al solvente: verdi poco esposti , blu molto esposti.

4 millions of atoms

GROMACS 4.5.4 on 128 cores - 0.3 ns/day

L’epitope 2F5 , inserito ai C-terminali di ogni proteina della VLP, è disegnata in giallo

• Structure-based design and experimental engineering of a plant virus nanoparticle for the presentation of immunogenic epitopes and as a drug carrier, C.Arcangeli, P.Circelli, M.Donini, AAA.Aljabali, E.Benvenuto, GP.Lomonossoff, C.Marusic. J. of Biomolecular Struc and Dynamics 32, 630-647 (2014).

• Local fivefold symmetry in liquid and undercooled Ni probed by x-ray absorption spectroscopy and computer simulations, A.Di Cicco, F.Iesari, S.De Panfilis, M.Celino, S.Giusepponi, A.Filipponi, Phys. Rev. B 89, 060102(R) (2014).

• Optical response of strongly absorbing inhomogeneous materials: Application to paper degradation, M.Missori, O.Pulci, L.Teodonio, C.Violante, I.Kupchak, J.Bagniuk, J.Lojewska, A.Mosca Conte, Phys. Rev. B 89, 054201 (2014).

• How phenyl makes a difference: mechanistic insights into the ruthenium(II)-catalysed isomerisation of allylic alcohols, S.Manzini, A.Poater, D.J.Nelson, L.Cavallo, S.P.Nolan. Chemical Science 2014,5, 180-188.

Pubblicazioni 2014

Pubblicazioni 2013

• Multi adducts of diphenylmethanofullerenes as electron acceptors for polymer solar cells: a quantum chemical study, P. Morvillo. J. of Nanoscience and Nanotechnology, 13, 5221-5226 (2013).

• A united event grand canonical Monte Carlo study of partially doped polyaniline,M.S.Byshkin, A.Correa, F.Buonocore, A.Di Matteo, G.Milano. J. Chem Phys. 139, 244906 (2013).

• Strain sensitivity and superconducting properties of Nb3Sn from first principles calculations, G.De Marzi, L.Morici, L.Muzzi, A.della Corte, M.Buongiorno Nardelli, J. Phys.: Condens. Matter 25 135702 (2013).

• Variability and expression profile of the DRF1 gene in four cultivars of durum wheat and one triticale under moderate water stress conditions, A.Latini, M.Sperandei, C.Cantale, C.Arcangeli, K.Ammar, P.Galeffi. Planta 237, 967-978 (2013).

• Exploring Electronic and Steric Effects on the Insertion and Polymerization Reactivity of Phosphinesulfonato Pd-II Catalysts, B.Neuwald, L.Falivene, L.Caporaso, L.Cavallo, S.Mecking. Chemistry-A European Journal 19, 17773-17788 (2013).

• Organic functionalization of metal oxide surfaces: an atomic scale modeling approach, C.Arcangeli, I.Borriello, G.Gianese, M.Celino, P.Morales, Nanosci. Nanotechnol. Lett. 5, 1147-1154 (2013).

• Surface states and electronic properties for small cadmium sulfide nanocluster, E.Burresi, M.Celino, Nanosci. Nanotechnol. Lett. 5, 1182-1187 (2013).

• Updating and revising "Proteins as networks: usefulnes of graph theory in protein science", A.Giuliani, L. Di Paola, P.Paci, M. De Ruvo, C.Arcangeli, D.Santoni, M.Celino. Chapter in book: Advances in Protein and Peptide Science, Vol. 1, Bentham, Editors: Ben Dunn (2013).

• DFT model of hydrogen desorption from MgH2: The role of iron catalyst, S.Giusepponi, M.Celino, Int. J. Hydrogen Energy (2013).

• Structure-based design and experimental engineering of a plant virus nanoparticle for the presentation of immunogenic epitopes and as a drug carrier, C.Arcangeli, P.Circelli, M.Donini, A.A.A.Aljabali, G.P.Lomonosso, E.Benvenuto, C.Marusic. J. Biomol. Struct. Dyn. (2013).

• GCMC simulation of hydrogen adsorption in densely packed arrays of Li-doped and hydrogenated carbon nanotubes, S.Mirabella, M.Celino, G.Zollo. J. Nanoparticle Research 10/2013, 15:2071.

• First-principles molecular dynamics study of glassy GeS2: Atomic structure and bonding properties, M.Celino, S.Le Roux, G.Ori, B.Coasne, A.Bouzid, M.Boero, C.Massobrio. Phys. Rev. B 88, 174201 (2013).

• Inhibition of iron corrosion in high temperature stagnant liquid lead: a molecular dynamics study, A.Arkundato, Z.Suud, M.Abdullah, W.Sutrisno and M.Celino. Annals of Nuclear Energy 62 298-306 (2013).

• The ideal tensile strength of tungsten and tungsten alloys by first-principles calculations, S.Giusepponi, M.Celino. J. of Nuclear Materials 435 (2013) 52-55.

• Recent progress in research on tungsten materials for nuclear fusion applications in Europe , M.Rieth, S.L.Dudarev, S.M. Gonzalez de Vicente, J.Aktaa, S. Giusepponi, M.Celino et al. J. of Nuclear Materials 432 (2012) 482-500.