Tapio Ala-Nissila

Tapio Ala-Nissila

Aalto-yliopisto

H-index: 61

Europe-Finland

About Tapio Ala-Nissila

Tapio Ala-Nissila, With an exceptional h-index of 61 and a recent h-index of 34 (since 2020), a distinguished researcher at Aalto-yliopisto, specializes in the field of Physics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Non-Stokesian dynamics of magnetic helical nanoswimmers under confinement

Unfolding system-environment correlation in open quantum systems: Revisiting master equations and the Born approximation

Nonmonotonic electrophoretic mobility of rodlike polyelectrolytes by multivalent coions in added salt

Quantum-corrected thickness-dependent thermal conductivity in amorphous silicon predicted by machine learning molecular dynamics simulations

Interactions between rigid polyelectrolytes mediated by ordering and orientation of multivalent nonspherical ions in salt solutions

Dynamics of fluctuations and thermal buckling in graphene from a phase-field crystal model

Estimating inter-regional mobility during disruption: Comparing and combining different data sources

Theoretical and computational analysis of the electrophoretic polymer mobility inversion induced by charge correlations

Tapio Ala-Nissila Information

University

Aalto-yliopisto

Position

and Loughborough University

Citations(all)

13753

Citations(since 2020)

4800

Cited By

10813

hIndex(all)

61

hIndex(since 2020)

34

i10Index(all)

259

i10Index(since 2020)

113

Email

University Profile Page

Aalto-yliopisto

Tapio Ala-Nissila Skills & Research Interests

Physics

Top articles of Tapio Ala-Nissila

Non-Stokesian dynamics of magnetic helical nanoswimmers under confinement

Authors

Alireza Fazeli,Vaibhav Thakore,Tapio Ala-Nissila,Mikko Karttunen

Journal

arXiv preprint arXiv:2311.00839

Published Date

2023/11/1

Electromagnetically propelled helical nanoswimmers offer great potential for nanorobotic applications. Here, the effect of confinement on their propulsion is characterized using lattice-Boltzmann simulations. Two principal mechanisms give rise to their forward motion under confinement: 1) pure swimming, and 2) the thrust created by the differential pressure due to confinement. Under strong confinement, they face greater rotational drag, but display a faster propulsion for fixed driving frequency in agreement with experimental findings. This is due to the increased differential pressure created by the boundary walls when they are sufficiently close to each other and the particle. Two new analytical relations are presented: 1) for predicting the swimming speed of an unconfined particle as a function of its angular speed and geometrical properties, and 2) an empirical expression to accurately predict the propulsion speed of a confined swimmer as a function of the degree of confinement and its unconfined swimming speed. At low driving frequencies and degrees of confinement, the systems retain the expected linear behavior consistent with the predictions of the Stokes equation. However, as the driving frequency and/or the degree of confinement increase, their impact on propulsion leads to increasing deviations from the Stokesian regime and emergence of nonlinear behavior.

Unfolding system-environment correlation in open quantum systems: Revisiting master equations and the Born approximation

Authors

AP Babu,Sahar Alipour,AT Rezakhani,Tapio Ala-Nissila

Journal

Physical Review Research

Published Date

2024/3/5

Understanding system-environment correlations in open quantum systems is vital for various quantum information and technology applications. However, these correlations are often overlooked or hidden in derivations of open-quantum-system master equations, especially when applying the Born approximation. To address this issue, given a microscopic model, we demonstrate how to retain system-environment correlation within commonly used master equations, such as the Markovian Lindblad, Redfield, second-order time convolutionless, second-order Nakajima-Zwanzig, and second-order universal Lindblad-like equations. We show that each master equation corresponds to a particular approximation on the system-environment correlation operator. In particular, our analysis exposes the form of the hidden system-environment correlation in the Markovian Lindblad equation derived using the Born …

Nonmonotonic electrophoretic mobility of rodlike polyelectrolytes by multivalent coions in added salt

Authors

Hossein Vahid,Alberto Scacchi,Maria Sammalkorpi,Tapio Ala-Nissila

Journal

Physical Review E

Published Date

2024/1/11

It is well established that when multivalent counterions or salts are added to a solution of highly charged polyelectrolytes (PEs), correlation effects can cause charge inversion of the PE, leading to electrophoretic mobility (EM) reversal. In this work, we use coarse-grained molecular-dynamics simulations to unravel the less understood effect of coion valency on EM reversal for rigid DNA-like PEs. We find that EM reversal induced by multivalent counterions is suppressed with increasing coion valency in the salt added and eventually vanishes. Further, we find that EM is enhanced at fixed low salt concentrations for salts with monovalent counterions when multivalent coions with increasing valency are introduced. However, increasing the salt concentration causes a crossover that leads to EM reversal which is enhanced by increasing coion valency at high salt concentration. Remarkably, this multivalent coion-induced …

Quantum-corrected thickness-dependent thermal conductivity in amorphous silicon predicted by machine learning molecular dynamics simulations

Authors

Yanzhou Wang,Zheyong Fan,Ping Qian,Miguel A Caro,Tapio Ala-Nissila

Journal

Physical Review B

Published Date

2023/2/6

Amorphous silicon (a-Si) is an important thermal-management material and also serves as an ideal playground for studying heat transport in strongly disordered materials. Theoretical prediction of the thermal conductivity of a-Si in a wide range of temperatures and sample sizes is still a challenge. Herein we present a systematic investigation of the thermal transport properties of a-Si by employing large-scale molecular dynamics (MD) simulations with an accurate and efficient machine learned neuroevolution potential (NEP) trained against abundant reference data calculated at the quantum-mechanical density-functional-theory level. The high efficiency of NEP allows us to study the effects of finite size and quenching rate in the formation of a-Si in great detail. We find that a simulation cell up to 64 000 atoms (a cubic cell with a linear size of 11 nm) and a quenching rate down to 10 11 K s− 1 are required for almost …

Interactions between rigid polyelectrolytes mediated by ordering and orientation of multivalent nonspherical ions in salt solutions

Authors

Hossein Vahid,Alberto Scacchi,Maria Sammalkorpi,Tapio Ala-Nissila

Journal

Physical Review Letters

Published Date

2023/4/14

Multivalent ions in solutions with polyelectrolytes (PEs) induce electrostatic correlations that can drastically change ion distributions around the PEs and their mutual interactions. Using coarse-grained molecular dynamics simulations, we show how in addition to valency, ion shape and concentration can be harnessed as tools to control rigid like-charged PE-PE interactions. We demonstrate a correlation between the orientational ordering of aspherical ions and how they mediate the effective PE-PE attraction induced by multivalency. The interaction type, strength, and range can thus be externally controlled in ionic solutions. Our results can be used as generic guidelines to tune the self-assembly of like-charged polyelectrolytes by variation of the characteristics of the ions.

Dynamics of fluctuations and thermal buckling in graphene from a phase-field crystal model

Authors

Enzo Granato,KR Elder,SC Ying,Tapio Ala-Nissila

Journal

Physical Review B

Published Date

2023/1/24

We study the effects of thermal fluctuations and pinned boundaries in graphene membranes by using a phase-field crystal model with out-of-plane deformations. For sufficiently long times, the linear diffusive behavior of height fluctuations in systems with free boundaries becomes a saturation regime, while at intermediate times the behavior is still subdiffusive as observed experimentally. Under compression, we find mirror buckling fluctuations where the average height changes from above to below the pinned boundaries, with the average time between fluctuations diverging below a critical temperature corresponding to a thermally induced buckling transition. Near the transition, we find a nonlinear height response in agreement with recent renormalization-group calculations and observed in experiments on graphene membranes under an external transverse force with clamped boundaries.

Estimating inter-regional mobility during disruption: Comparing and combining different data sources

Authors

Sara Heydari,Zhiren Huang,Takayuki Hiraoka,Alejandro Ponce de León Chávez,Tapio Ala-Nissila,Lasse Leskelä,Mikko Kivelä,Jari Saramäki

Journal

Travel Behaviour and Society

Published Date

2023/4/1

A quantitative understanding of people’s mobility patterns is crucial for many applications. However, it is difficult to accurately estimate mobility, in particular during disruption such as the onset of the COVID-19 pandemic. Here, we investigate the use of multiple sources of data from mobile phones, road traffic sensors, and companies such as Google and Facebook in modelling mobility patterns, with the aim of estimating mobility flows in Finland in early 2020, before and during the disruption induced by the pandemic. We find that the highest accuracy is provided by a model that combines a past baseline from mobile phone data with up-to-date road traffic data, followed by the radiation and gravity models similarly augmented with traffic data. Our results highlight the usefulness of publicly available road traffic data in mobility modelling and, in general, pave the way for a data fusion approach to estimating mobility flows.

Theoretical and computational analysis of the electrophoretic polymer mobility inversion induced by charge correlations

Authors

Xiang Yang,Sahin Buyukdagli,Alberto Scacchi,Maria Sammalkorpi,Tapio Ala-Nissila

Journal

Physical Review E

Published Date

2023/3/23

Electrophoretic (EP) mobility reversal is commonly observed for strongly charged macromolecules in multivalent salt solutions. This curious effect takes place, eg, when a charged polymer, such as DNA, adsorbs excess counterions so that the counterion-dressed surface charge reverses its sign, leading to the inversion of the polymer drift driven by an external electric field. In order to characterize this seemingly counterintuitive phenomenon that cannot be captured by electrostatic mean-field theories, we adapt here a previously developed strong-coupling-dressed Poisson-Boltzmann approach to the cylindrical geometry of the polyelectrolyte-salt system. Within the framework of this formalism, we derive an analytical polymer mobility formula dressed by charge correlations. In qualitative agreement with polymer transport experiments, this mobility formula predicts that the increment of the monovalent salt, the decrease …

Quantum-circuit refrigerator for reset of superconducting qubits

Authors

Mikko Möttönen,Timm Mörstedt,Vasilii Sevriuk,Matti Silveri,Gianluigi Catelani,Hao Hsu,Louis Lattier,Maaria Tiiri,Tapio Ala-Nissila,Arto Viitanen,Máté Jenei,Leif Grönberg,Wei Liu,Jami Rönkkö,Fabian Marxer,Matti Partanen,Jukka Räbinä,Johannes Heinsoo,Tianyi Li,Jani Tuorila,Vasilii Vadimov,Juha Hassel,Kuan Tan

Journal

Bulletin of the American Physical Society

Published Date

2023/3/8

Quantum-circuit refrigerator (QCR)[1] is an active on-chip component which can change the dissipation rate in superconducting microwave devices in-situ by orders of magnitude. The dissipation channels can be turned on and off by applying a dc or rf voltage, or both [2]. Such an additional energy input together with an energy quantum from the refrigerated quantum circuit promotes photon-assisted quasiparticle tunneling through a normal-metal-insulator-superconductor junction. Previously, we have experimentally demonstrated that a QCR can change the quality factor of a superconducting microwave resonator by several orders of magnitude also giving rise to an effective Lamb shift of the resonator frequency [3] and that the dissipation can be turned on or off in a few nanoseconds [4]. We have also demonstrated that a superconducting qubit can be reset with a QCR from 100% to a few percent population in less …

Variable thermal transport in black, blue, and violet phosphorene from extensive atomistic simulations with a neuroevolution potential

Authors

Penghua Ying,Ting Liang,Ke Xu,Jianbin Xu,Zheyong Fan,Tapio Ala-Nissila,Zheng Zhong

Journal

International Journal of Heat and Mass Transfer

Published Date

2023/3/1

Phosphorus has diverse chemical bonds, and even in its two-dimensional form, there are three stable allotropes: black phosphorene (Black-P), blue phosphorene (Blue-P), and violet phosphorene (Violet-P). Due to the complexity of these structures, no efficient and accurate classical interatomic potential has been developed for them. In this paper, we develop an efficient machine-learned neuroevolution potential model for these allotropes and apply it to study thermal transport in them via extensive molecular dynamics (MD) simulations. Based on the homogeneous nonequilibrium MD method, the thermal conductivities are predicted to be 12.5±0.2 (Black-P in armchair direction), 78.4±0.4 (Black-P in zigzag direction), 128±3 (Blue-P), and 2.36±0.05 (Violet-P) Wm− 1 K− 1. The underlying reasons for the significantly different thermal conductivity values in these allotropes are unraveled through spectral …

General-purpose machine-learned potential for 16 elemental metals and their alloys

Authors

Keke Song,Rui Zhao,Jiahui Liu,Yanzhou Wang,Eric Lindgren,Yong Wang,Shunda Chen,Ke Xu,Ting Liang,Penghua Ying,Nan Xu,Zhiqiang Zhao,Jiuyang Shi,Junjie Wang,Shuang Lyu,Zezhu Zeng,Shirong Liang,Haikuan Dong,Ligang Sun,Yue Chen,Zhuhua Zhang,Wanlin Guo,Ping Qian,Jian Sun,Paul Erhart,Tapio Ala-Nissila,Yanjing Su,Zheyong Fan

Journal

arXiv preprint arXiv:2311.04732

Published Date

2023/11/8

Machine-learned potentials (MLPs) trained against quantum-mechanical reference data have demonstrated remarkable accuracy, surpassing empirical potentials. However, the absence of readily available general-purpose MLPs encompassing a broad spectrum of elements and their alloys hampers the applications of MLPs in materials science. In this study, we present a feasible approach for constructing a unified general-purpose MLP for numerous elements and showcase its capability by developing a model (UNEP-v1) for 16 elemental metals (Ag, Al, Au, Cr, Cu, Mg, Mo, Ni, Pb, Pd, Pt, Ta, Ti, V, W, Zr) and their diverse alloys. To achieve a complete representation of the chemical space, we demonstrate that employing 16 one-component and 120 two-component systems suffices, thereby avoiding the enumeration of all 65 535 possible combinations for training data generation. Furthermore, we illustrate that systems with more components can be adequately represented as interpolation points in the descriptor space. Our unified MLP exhibits superior performance across various physical properties as compared to the embedded-atom method potential, while maintaining computational efficiency. It achieves a remarkable computational speed of atom step / second in molecular dynamics simulations using eight 80-gigabyte A100 graphics cards, enabling simulations up to 100 million atoms. We demonstrate the generality and high efficiency of the MLP in studying plasticity and primary radiation damage in the MoTaVW refractory high-entropy alloys, showcasing its potential in unraveling complex materials behavior. This work represents a …

Moiré patterns and inversion boundaries in graphene/hexagonal boron nitride bilayers

Authors

KR Elder,Zhi-Feng Huang,Tapio Ala-Nissila

Journal

Physical Review Materials

Published Date

2023/2/8

In this paper a systematic examination of graphene/hexagonal boron nitride (g/hBN) bilayers is presented, through a recently developed two-dimensional phase field crystal model that incorporates out-of-plane deformations. The system parameters are determined by closely matching the stacking energies and heights of g/hBN bilayers to those obtained from existing quantum-mechanical density functional theory calculations. Out-of-plane deformations are shown to reduce the energies of inversion domain boundaries in hBN, and the coupling between graphene and hBN layers leads to a bilayer defect configuration consisting of an inversion boundary in hBN and a domain wall in graphene. Simulations of twisted bilayers reveal the structure, energy, and elastic properties of the corresponding moiré patterns and show a crossover as the misorientation angle between the layers increases from a well-defined …

Polymer translocation in an environment of active rods

Authors

Hamidreza Khalilian,Jalal Sarabadani,Tapio Ala-Nissila

Journal

Physical Review Research

Published Date

2023/5/18

We consider the dynamics of a translocation process of a flexible linear polymer through a nanopore into an environment of active rods in the trans side. Using Langevin dynamics simulations, we show that the rods facilitate translocation to the trans side even when there are initially more monomers on the cis than on the trans side. Structural analysis of the translocating polymer reveals that active rods induce a folded structure to the trans-side subchain in the case of successful translocation events. By keeping the initial number of monomers on the cis-side subchain fixed, we map out a state diagram for successful events as a function of the rod number density for a variety of system parameters. This reveals competition between facilitation by the rods at low densities and crowding that hinders translocation at higher densities.

Electromagnetic response and optical properties of anisotropic CuSbS2 nanoparticles

Authors

Fahime Seyedheydari,Kevin Conley,Pasi Ylä-Oijala,Ari Sihvola,Tapio Ala-Nissila

Journal

JOSA B

Published Date

2022/7/1

We investigate the electromagnetic response of anisotropic (non-spherical) copper antimony disulfide (CuSbS_2) nanoparticles and layers embedded with them using computational methods. To this end, we calculate the scattering and absorption efficiencies of oblate spheroidal CuSbS_2 nanoparticles using the surface integral equation method. We find strong dependence of the response depending on the anisotropy of the spheroids and their orientation with respect to the electric field polarization of incoming radiation. Thin spheroids display a sharp plasmonic resonance in the ultraviolet, which is observed only for the electric field polarization along the short axis. Fano resonances that appear in the near infrared (NIR) blueshift when the short axis length is reduced, and they can be either strongly suppressed or enhanced depending on the relative orientation of the spheroid. We further investigate the optical …

Weakly pinned skyrmion liquid in a magnetic heterostructure

Authors

Rhodri Mansell,Yifan Zhou,Kassius Kohvakka,See-Chen Ying,Ken R Elder,Enzo Granato,Tapio Ala-Nissila,Sebastiaan Van Dijken

Journal

Physical Review B

Published Date

2022/8/10

Magnetic skyrmions are topologically distinct particles whose thermally activated motion could be used to implement probabilistic computing paradigms. While solid-liquid phase transitions in skyrmion lattices have been demonstrated, the behavior of a skyrmion liquid and the effects of pinning are largely unknown. Here we demonstrate the formation of a weakly pinned skyrmion liquid in a magnetic heterostructure. By inserting a Ru wedge layer at the ferromagnet/heavy metal interface we evaluate the dependence of skyrmion dynamics on the skyrmion size and density. Our experiments demonstrate that the diffusion of skyrmions is largest in dense liquids with small skyrmions. The thermal motion of skyrmions at room temperature easily overcomes the narrow distribution of pinning site energies in the granular film structure, satisfying a key requirement of probabilistic device architectures. Micromagnetic simulations …

GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations

Authors

Zheyong Fan,Yanzhou Wang,Penghua Ying,Keke Song,Junjie Wang,Yong Wang,Zezhu Zeng,Ke Xu,Eric Lindgren,J Magnus Rahm,Alexander J Gabourie,Jiahui Liu,Haikuan Dong,Jianyang Wu,Yue Chen,Zheng Zhong,Jian Sun,Paul Erhart,Yanjing Su,Tapio Ala-Nissila

Journal

J. Chem. Phys.

Published Date

2022

We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in Fan et al.[Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package gpumd. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models and demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more …

Self-assembly of two-component soft systems controlled by pairwise interactions.

Authors

Alberto Scacchi,Sousa Javan Nikkhah,Maria Sammalkorpi,Tapio Ala-Nissila

Journal

APS March Meeting Abstracts

Published Date

2022

Self-assembly in natural and synthetic molecular systems can create complex aggregates or materials whose properties and functionalities rise from their internal structure and molecular arrangement. The key microscopic features that control such assemblies remain poorly understood, nevertheless. We demonstrate how the intrinsic length scales and their interplay in terms of inter-species molecular interactions can be used to tune soft matter self-assembly. Using classical density functional theory, we apply our strategy to soft binary mixtures to create guidelines for tuning inter-molecular interactions that lead to transitions from a fully miscible, liquid-like uniform state to formation of simple and core-shell aggregates and mixed aggregate structures, as well as to a system that provides a transition from regular single-core particles to multi-core aggregates that exhibit multiple structural length scales. Our results aid in …

Adaptive and optimized COVID-19 vaccination strategies across geographical regions and age groups

Authors

Jeta Molla,Alejandro Ponce de León Chávez,Takayuki Hiraoka,Tapio Ala-Nissila,Mikko Kivelä,Lasse Leskelä

Journal

PLoS computational biology

Published Date

2022/4/7

We evaluate the efficiency of various heuristic strategies for allocating vaccines against COVID-19 and compare them to strategies found using optimal control theory. Our approach is based on a mathematical model which tracks the spread of disease among different age groups and across different geographical regions, and we introduce a method to combine age-specific contact data to geographical movement data. As a case study, we model the epidemic in the population of mainland Finland utilizing mobility data from a major telecom operator. Our approach allows to determine which geographical regions and age groups should be targeted first in order to minimize the number of deaths. In the scenarios that we test, we find that distributing vaccines demographically and in an age-descending order is not optimal for minimizing deaths and the burden of disease. Instead, more lives could be saved by using strategies which emphasize high-incidence regions and distribute vaccines in parallel to multiple age groups. The level of emphasis that high-incidence regions should be given depends on the overall transmission rate in the population. This observation highlights the importance of updating the vaccination strategy when the effective reproduction number changes due to the general contact patterns changing and new virus variants entering.

Helical flow states in active nematics

Authors

Ryan R Keogh,Santhan Chandragiri,Benjamin Loewe,Tapio Ala-Nissila,Sumesh P Thampi,Tyler N Shendruk

Journal

Physical Review E

Published Date

2022/7/7

We show that confining extensile nematics in three-dimensional (3D) channels leads to the emergence of two self-organized flow states with nonzero helicity. The first is a pair of braided antiparallel streams—this double helix occurs when the activity is moderate, anchoring negligible, and reduced temperature high. The second consists of axially aligned counter-rotating vortices—this grinder train arises between spontaneous axial streaming and the vortex lattice. These two unanticipated helical flow states illustrate the potential of active fluids to break symmetries and form complex but organized spatiotemporal structures in 3D fluidic devices.

Active Nematic Obstacle Courses

Authors

Ryan Keogh,Tyler Shendruk,Sumesh Thampi,Santhan Chandragiri,Tapio Ala-Nissila

Journal

APS March Meeting Abstracts

Published Date

2022

Active fluids, which spontaneously flow under their own internal energy, are commonly composed of nematic constituents, such as filamentous microtubules or rod-like bacteria. The activity and nematic elasticity generate a characteristic lengthscale that competes with any confining lengthscales. This competition of active length and confinement can lead to spatiotemporal ordered flow states, including vortex lattices and double helices in simple confining channels. Building upon recent work in confined active fluids, we employ a hybrid lattice Boltzmann and finite differences numerical solver to simulate an active nematic spontaneously flowing through an obstacle-laden channel. This geometry allows for an investigation of active nematic behaviour in heterogeneous environments. This talk will present our recent findings in channels with different obstacle configurations and imposed boundary conditions. We …

See List of Professors in Tapio Ala-Nissila University(Aalto-yliopisto)

Tapio Ala-Nissila FAQs

What is Tapio Ala-Nissila's h-index at Aalto-yliopisto?

The h-index of Tapio Ala-Nissila has been 34 since 2020 and 61 in total.

What are Tapio Ala-Nissila's top articles?

The articles with the titles of

Non-Stokesian dynamics of magnetic helical nanoswimmers under confinement

Unfolding system-environment correlation in open quantum systems: Revisiting master equations and the Born approximation

Nonmonotonic electrophoretic mobility of rodlike polyelectrolytes by multivalent coions in added salt

Quantum-corrected thickness-dependent thermal conductivity in amorphous silicon predicted by machine learning molecular dynamics simulations

Interactions between rigid polyelectrolytes mediated by ordering and orientation of multivalent nonspherical ions in salt solutions

Dynamics of fluctuations and thermal buckling in graphene from a phase-field crystal model

Estimating inter-regional mobility during disruption: Comparing and combining different data sources

Theoretical and computational analysis of the electrophoretic polymer mobility inversion induced by charge correlations

...

are the top articles of Tapio Ala-Nissila at Aalto-yliopisto.

What are Tapio Ala-Nissila's research interests?

The research interests of Tapio Ala-Nissila are: Physics

What is Tapio Ala-Nissila's total number of citations?

Tapio Ala-Nissila has 13,753 citations in total.

What are the co-authors of Tapio Ala-Nissila?

The co-authors of Tapio Ala-Nissila are Riccardo Ferrando, Martin Grant, Mikko Möttönen, Nikolas Provatas, Giulia Rossi, Zheyong Fan.

Co-Authors

H-index: 62
Riccardo Ferrando

Riccardo Ferrando

Università degli Studi di Genova

H-index: 54
Martin Grant

Martin Grant

McGill University

H-index: 48
Mikko Möttönen

Mikko Möttönen

Aalto-yliopisto

H-index: 46
Nikolas Provatas

Nikolas Provatas

McGill University

H-index: 40
Giulia Rossi

Giulia Rossi

Università degli Studi di Genova

H-index: 32
Zheyong Fan

Zheyong Fan

Aalto-yliopisto

academic-engine