**Prof. Dr. Kurt Binder**

**Institute
of Physics**

**Staudinger
Weg 7**

**55099**** Mainz**

**Curriculum vitae**

to Eduard Binder, technical engineer

and Anna Binder, née Eppel

1950 – 1962 Public
schools of

1962 – 1969 Studies
in Technical Physics

at the Technical

9 March 1965 I
State board examination

1967 – 1969 Doctoral
thesis at the Austrian Institute of

Atomic Physics,

tionsfunktionen von Ferromagnetika“ (Calculation of

the spin correlation functions in ferromagnets)

21 March 1969 PhD
in “Technical Sciences”

1969
Karoline
& Guido Krafft-Medal, Techn.
Univ.

(Prof. Dr. H. Maier-Leibnitz and Prof. Dr. H. Vonach)

31 March 1973 Laboratory,
8803

Condensed
Matter at the Free

(which I declined)

at the Technical

15 July 1977 Marriage
with Marlies Ecker

(born

leave of absence to direct the

Institute
of

since October 1983 Full
Professor for Theoretical Physics at the

Johannes Gutenberg-University in

– December 1992 for
the German federal state Rhineland-Palatinate

1985 The
chair offered to me at

computer Computations Research, I also declined

May 1986 – Jan 1996 Chairman
of the Coordination Committee of the Materials

since Feb. 1987 “adjunct
professor” at the Center for Simulational

Physics,

July 1987 – Dec. 2001 Speaker
for Special Research Program SFB 262, funded

by the German National Research Foundation DFG for

research on “The glass state and glass transition of

non-metallic amorphous materials”

July 1987 – July 1995 Appointment
to the “Scientific Advisory Board” at HLRZ

high-performance computing center
in

1988 – 1990 and Member
of the IUPAP Commission C3

1996 – 1999 “Thermodynamics
and Statistical Physics” as well as

the DNK (German national committee for IUPAP)

Max
Planck Institute for Polymer Research (

which I refused

Max
Planck Society

12 May 1992 Appointment
as Corresponding Member of the

German
Physical Society (DPG)

1999 – 2002 Chairman
of the IUPAP C3 Commission and

Member
of the IUPAP Executive Council

2001 Distinguished
as “Highly Cited Researcher” by ISI,

2001 (Sept. 6^{th}) Berni
J. Alder CECAM Prize (for Computational Physics) of the EPS

2003 (Jan. 15^{th})
– 2005 Elected for 2 years
as the Chairman of the Physics Department

(April 30^{th} )

2003 (Jan. 24^{th}) The Staudinger-Durrer-Prize (for outstanding contributions to Monte Carlo
Simulations) of the ETH Zürich

2003 (Feb. 21^{th}) Appointment as
Member of the

and Literature,

since 2006 Honorary Member of the British
Institute of Physics (IOP)

2003 (Oct.) Member of
the University Council of the

- 2006 (Sept.)

2005 (Nov. 2^{nd})
Appointment as
External Member of the

of Sciences,

2007 (Jan. 24^{th}) Honorary P

2007 (July 11^{th}) Receipt of the
Boltzmann Medal of IUPAP

2007 (Oct. 2007) Receipt of the
Gutenberg Fellowship of the Johannes

2008 - 2013 Scientific Advisory
Board of the Max Planck Institute

for Colloid- and Interface Research, Potsdam

since 2009 Member of the “Rat für Technology, Rheinland-Pfalz”

2009 (Sept. 23^{rd}) Receipt of the Lennard-Jones Medal by the Royal Society of Chemistry,

2010 – 2012 Member of the
Scientific Steering Committee of the

** **Partnership for Advanced Computing
in Europe (PRACE)

2011 Vice-Chair
of the Scientific Council of the John von

** **Neumann Institute for Computing
(NIC), Jülich

April 2011 Appointment
as member of the German Academy of Sciences Leopoldina/Halle/Germany

since 2012 Chair of the Scientific Council
of the john von Neumann Institute for Computing (NIC) Jülich

since 2012 Vice-chair of the Steering
Committee of the Gauss Center for Supercomptuing

since April 1^{st}, 2012 retired from active
service as Professor emeritus

Sept. 19^{th},
2012 Honorary
Medal “Marin Drinov” of the Bulgarian Academy of
Sciences

Jan.
30^{th}, 2013 Honorary
PhD by the Mathematical & Natural Science Department/Faculty of the
Heinrich-Heine University Duesseldorf for outstanding
contributions to the special research field “TR6” “Physics of colloidal
dispersions in external fields”

__Supervision
of Ph.D. theses/Betreuung von Doktorarbeiten__

Prior to the “Habilitation”
(1973), only an “inofficial” Ph.D. advisor status was
possible for the following two cases:

(i)
Volker Wildpaner “Berechnung der
Magnetisierung um Gitterfehler in einem Heisenberg Ferromagneten” Technische
Hochschule Wien, 1972

(ii)
Heiner-Müller-Krumbhaar “Bestimmung
kritischer Exponenten am Heisenberg-Ferromagneten mit einem selbstkonsistenten
Monte-Carlo Verfahren” Physik-Department, Technische Hochschule München, 1972

A) __Universität des
Saarlandes, Saarbrücken__

1.
Artur
Baumgärtner “Die verallgemeinerte
kinetische Ising-Kette: Ein Modell für

die Dynamik von Biopolymeren” 1977

2.
Claudia Billotet “Nichtlineare Relaxation bei Phaseübergängen:
Eine Ginzburg-Landau

Theorie mit Fluktuationen” 1979

3.
Rüdiger
Kretschmer “Kritisches Verhalten und
Oberflächeneffekte von Systemen mit

lang- und kurzreichweitigen
Wechselwirkungen: Phänomenologische Theorie und

Monte
Carlo Simulation” 1979

4.
Ingo
Morgenstern “Ising
Systeme mit eingefrorener Unordnung in zwei Dimensionen” 1980

B)
__Universität
zu Köln__

5.
Kurt Kremer “Untersuchungen zur statistischen Mechanik
von linearen Polymeren unter

verschiedenen
Bedingungen” 1983

6.
Jozsef Reger “Untersuchungen zur statistischen Mechanik
von Spingläsern” 1985

C)
__Johannes
Gutenberg Universität__

7.
Ingeborg
Schmidt “Oberflächenanreichung
und Wettingphasenübergänge in

Polymermischungen” 1986

8. Jannis Batoulis
“Monte Carlo Simulation von Sternpolymeren” 1987

9. Hans-Otto Carmesin “Modellierung von Orientierungsgläsern” 1988

10. Wolfgang Paul
“Theoretische Untersuchungen zur Kinetik von Phasenübergängen

erster Ordnung” 1989

11. Manfred Scheucher “Phasenverhalten und Grundzustandseigenschaften

kurzreichweitiger
Pottsgläser” 1990

12. Hans-Peter Wittmann
“Monte Carlo Simulationen des Glasübergangs von

Polymerschmelzen im Rahmen des Bondfluktuationsalgorithmus” 1991

13. Burkhard Dünweg “Molekulardynamik-Untersuchungen zur Dynamik von

Polymerketten in verdünnter Lösung” 1991

14. Friederike Schmid
“Volumen-Grenzflächeneigenschaften von Modellen kubisch-

raumzentrierter binärer Legierungen: Untersuchung mittels Monte Carlo
Simulation” 1991

15. Hans-Peter Deutsch
“Computer-Simulation von Polymer-Mischungen ” 1991

16. Werner Helbing “Quanten Monte Carlo Simulation eines
Rotatormoleküls” 1992

17. Dominik Marx
“Entwicklung von Pfadintegral Monte Carlo Methoden für adsorbierte

Moleküle mit inneren
Quantenfreiheitsgraden” 1992

18. Gernot Schreider “Hochtemperaturreihenentwicklungen zum geordneten
und unge-

ordneten
Potts-Modell” 1993

19. Jörg Baschnagel “Monte Carlo Simulationen des Glasübergangs und
Glaszustandes von

dichten dreidimensionalen Polymerschmelzen” 1993

20. Marco d’Onorio de Meo “Monte Carlo
Methoden zur Untersuchung reiner und

verdünnter Ferromagnete mit
kontinuierlichen Spins” 1993

21. Marcus Müller “Monte
Carlo Simulation zur Thermodynamik und Struktur von

Polymer-Mischungen”
1994

22. Klaus Eichhorn “Pottsmodelle zu Zufallsfeldern” 1995

23. Frank M. Haas
“Monolagen steifer Kettenmoleküle auf Oberflächen. Eine Monte Carlo

Simulationsuntersuchung” 1995

24. Matthias Wolfgardt “Monte Carlo Simulation zur Zustandsgleichung
glasartiger

Polymerschmelzen” 1995

25. Martin H. Müser “Klassische und quantenmechanische Computer
Simulationen zur

Orientierungsgläsern und Kristallen” 1995

26. Stefan Kappler
“Oberflächenspannung und Korrelationslängen im Pottsmodell”
1995

27. Felix S. Schneider
“Quanten-Monte-Carlo-Computersimulationsstudie der Dynamik des

inneren, quantenmechanischen
Freiheitsgrades eines Modell-Fluids in reeller Zeit”
1995

28. Katharina Vollmayr “Abkühlungsabhängigkeiten von strukturellen
Gläsern: Eine

Computersimulation”
1995

29. Volker Tries “Monte Carlo Simulationen realistischer
Polymerschmelzen mit einem

vergröberten Modell” 1996

30. Martina Kreer
“Quantenmechanische Anomalien bei Phasenübergängen in 2D:

Eine Pfadintegral-Monte-Carlo Studie zu H_{2
}und O_{2 }physisorbiert auf Graphit” 1996

31. Bernhard Lobe
“Stargraph-Entwicklungen zum geordneten und ungeordneten Potts-

Modell und deren Analysen” 1997

32. Stefan Kämmerer
“Orientierungsdynamik in einer unterkühlten Flüssigkeit: eine

MD-Simulation” 1997

33. Henning Weber “Monte
Carlo-Simulationen der Gasdiffusion in Polymermatrizen” 1997

34. Rüdiger Sprengard
“Raman-spectroscopyin Li_{2}OAl_{2}O_{3}SiO_{3}-
glass ceramics:
Simulation and crystal spectra and experimental investigations on the

Ceramization "1998

35. Frank F. Haas
“Oberflächeninduzierte Unordnung in binären bcc Legierungen” 1998

36. Jürgen Horbach “Molekulardynamiksimulationen zum Glasübergang von

Silikatschmelzen”
1998

37. Matthias Presber “Pfadintegral-Monte Carlo Untersuchungen zu
Phasenübergängen in

molekularen Festkörpern” 1998

38. Christoph Stadler
“Monte Carlo Simulation in Langmuir Monolagen” 1998

39. Andres Werner
“Untersuchung von Polymer-Grenzflächen mittels Monte Carlo

Simulationen” 1998

40. Christoph Bennemann
“Untersuchung des thermischen Glasübergangs von Polymer-

schmelzen
mittels Molekular-Dynamik Simulationen” 1999

41. Tobias Gleim
“Relaxation einer unterkühlten Lennard-Jones Flüssigkeit” 1999

42. Fathollah Varnik
“Molekulardynamik-Simulationen zum Glasübergang in

Makromolekularen Filmen” 2000

43. Dirk Olaf Löding “Quantensimulationen physisorbierter
Molekülschichten auf Graphit:

Phasenübergänge, Quanteneffekte, und
Glaseigenschaften” 2000

44. Alexandra Roder “Molekulardynamik-Simulationen zu
Oberflächeneigenschaften”

von Siliziumdioxidschmelzen“ 2000

45. Oliver Dillmann “Monte
Carlo Simulationen des kritischen Verhaltens von dünnen”

Ising Filmen”
2000

46. Harald Lange
“Oberflächengebundene flüssigkristalline Polymere in nematischer

Lösung: eine Monte Carlo
Untersuchung” 2001

47. Peter Scheidler
“Dynamik unterkühlter Flüssigkeiten in Filmen und Röhren” 2001

48. Claudio Brangian
“Monte Carlo Simulation of Potts-Glasses” 2002

49. Torsten Kreer
“Molekulardynamik-Simulation zur Reibung zwischen

polymerbeschichten Oberflächen”
2002

50. Stefan Krushev
“Computersimulationen zur Dynamik und Statistik von Polybutatien-

schmelzen” 2002

51. Susanne Metzger “Monte
Carlo Simulationen zum Adsorptionsverhalten von Homo-

Copolymeren”
2002

52. Claus Mischler
“Molekulardynamik-Simulation zur Struktur von SiO_{2}-Oberflächen mit

adsorbiertem Wasser” 2002

53. Ellen Reister “Zusammenhang zwischen der Einzelkettendynamik und
der Dynamik von

Konzentrationsfluktuationen
in mehrkomponentigen Polymersystemen: dynamische Mean-Field Theorie und Computersimulation” 2002

54. Anke Winkler
“Molekulardynamik-Untersuchungen zur atomistischen Struktur und

Dynamik von binären Mischgläsern Na_{2}O_{2}
und (Al_{2}O_{3}) (2SiO_{2})” 2002

55. Martin Aichele
“Simulation Studies of Correlation Functions and Relaxation in

Polymeric Systems” 2003

56. Peter M. Virnau “Monte
Carlo Simulationen zum Phasen-und Keimbildungsverhalten

von Polymerlösungen” 2003

57. Daniel Herzbach
“Comparison of Model Potentials for Molecular Dynamics Simulation

of Crystallline Silica” 2004

58. Hans R. Knoth
“Molekular-Dynamik-Simulation zur Untersuchung des Mischalkali-

Effekts in silikatischen
Gläsern” 2004

59. Florian Krajewski
“New path integral simulation algorithms and their application to

creep in the
quantum sine-Gordon chain” 2004

60. Ben Jesko
Schulz “Monte Carlo Simulation of Interface Transitions in Thin Film with

Competing Walls” 2004

61. Torsten Stühn “Molekular-Dynamik Computersimulation einer
amorph-kristallinen SiO_{2}

Grenzschicht” 2004

62. Ludger Wenning “Computersimulation zum Phasenverhalten binärer
Polymerbürsten ” 2004

63. Juan Guillermo Diaz Ochoa
“Theoretical investigation of the interaction of a polymer

film with a
nanoparticle” 2005

64. Federica Rampf “Computer Simulationen zur Strukturbildung von
einzelnen

Polymerketten” 2005

65. Michael Hawlitzky “Klassische und ab initio
Molekulardynamik-Untersuchungen zu

Germaniumdioxidschmelzen” 2006

66. Andrea Ricci “Computer
Simulations of two-dimensional colloidal crystals in

confinement”
2006

67. Antione Carré
“Development of emperical potentials for liquid
silica” 2007

68. Swetlana Jungblut “Mixtures of
colloidal rods and spheres in bulk and in confinement” 2008

69. Yulia Trukhina “Monte Carlo
Simulation of Hard Spherocylinders under confinement”
2009

70. Leonid Spirin “Molecular Dynamics
Simulations of sheared brush-like systems” 2010

71. Daniel Reith
“Computersimulationen zum Einfluß topologischer
Beschränkungen auf

Polymere” 2011

72. Alexander Winkler “Computer
simulations of colloidal fluids in confinement” 2012

73. David Winter “Computer
simulations of slowly relaxing systems in external fields” 2012

74. Dorothea Wilms “Computer simulations
of two-dimensional colloidal crystals under

confinement and shear” 2013

75. Benjamin Block “Nucleation
Studies on Graphics Processing Units” 2014

76. Fabian Schmitz “Computer
Simulation Methods to study Interfacial Tensions: From the

Ising Model to Colloidal Crystals”
2014

77. Antonia Statt “Monte Carlo
Simulations of Nucleation of Colloidal Crystals” 2015

__Main Research Interests__

1.
__Monte Carlo simulation as a
tool of computational statistical mechanics to study __

__phase____
transitions__

A main research
goal has been to develop Monte Carlo techniques for the numerical study of
classical interacting many body systems, with an emphasis on phase transitions
in condensed matter [33,41,76,153,189,205,244,321,491,551,630,970,1132, number
refer to the list of publications, see:publication
list Binder.] A central obstacle to overcome are finite size
effects: Ising and classical Heisenberg ferromagnets [5] exhibit the “finite size tail” in the root
mean square magnetization, which is strongly enhanced near the critical point
(due to the divergence of correlation length and susceptibility in the
thermodynamic limit), leading to finite size rounding and shifting of the
transition [16,29]. Combining this starting point with the finite size scaling
theory developed by M.E. Fisher at about the same time, numerous promising
first studies of phase transitions were given [33,41,75,76,92,103] but the main
breakthrough came from a study of the order parameter probability distribution
and its fourth order cumulant [135]. For different
system sizes the cumulants (studied as function of
the proper control parameter, e.g. temperature) intersect at criticality at an
(almost) universal value, and this allows an easy and unbiased estimation of
the critical point location. This method has helped to study phase transitions
and phase diagrams of many model systems and now is widely used by many
research groups. Lattice models for adsorbed monolayers at crystal surfaces
have been studied to clarify corresponding experiments (e.g. H on Pd (100) [127], H on Fe (100) [145,154] or CO and N_{2}
on graphite [398,411]. Lattice models for solid alloys have
been used to understand the ordering in Cu-Au alloys [16,124,210,215],
of Fe-Al alloys [355,380], and of magnetic ordering of EuS
diluted with SrS [86,103,105]. Recently finite size
scaling methods have also been used to study off-lattice models for the α
– β phase transition in SiO_{2} [676] and the vapor-liquid phase
transitions of CO_{2} [916] and various liquid mixtures [943] and good
agreement with experiment was found. The technique could also
be extended to very asymmetric systems, such as the Asakura-Oosawa
model for colloid-polymer mixtures [823] and rod-sphere mixtures [910].

Since finite size scaling in its standard formulation needs “hyperscaling” relations between critical exponents to hold (see e.g. [135]), nontrivial generalizations needed to be developed for cases where hyperscaling does not hold, such as model systems in more than 4 space dimensions [184,195,596] and Ising-type systems with quenched random fields (such as colloid-polymer mixtures inside a randomly-branched gel) [883,939,1016]. Other generalizations concern anisotropic critical phenomena [261, see---], e.g. critical wetting transitions [1061,1068,1095], and crossover from one universality class to another [369,524,593], e.g. when the effective interaction range increases the system criticality changes to become mean-field like (an application being binary polymer blends when the chain length of the macromolecules increases [414]). An important task in the study of phase transitions by simulations is the distinction of second order phase transitions from first-order ones, a problem studied in collaboration with David Landau since also the latter are rounded (and possibly shifted) by finite size (e.g. [182,212,262,375,1066]). Some of the “recipes” developed to study phase transitions by simulations using Monte Carlo methods are reviewed in [201,375,656,912]; we also note that finite size scaling concepts are also useful for Molecular Dynamics methods, and then allow also the study of dynamic critical behavior of fluids [801,868,873].

2.
__Monte Carlo simulation as a
tool to study dynamical behavior in condensed matter systems__

One can give the Monte Carlo sampling process a
dynamic interpretation in terms of a Markovian master equation [24]; on the one
hand, one can thus give statistical errors an appropriate interpretation in
terms of dynamic correlation functions of the appropriate stochastic model, and
understand what the slowest relaxing variables are: e.g., for a fluid these are
long wavelength Fourier components of the density, when the fluid is simulated
in the canonical ensemble. This “hydrodynamic
slowing down” [33,76] was not recognized in the early
literature on Monte Carlo simulations of fluids, where the relaxation of the
internal energy was advocated to judge the approach to equilibrium. In this way, it also becomes possible to understand that the
so-called “statistical inefficiency” of the Monte Carlo algorithm near
second-order phase transitions simply reflects critical slowing down, and it is
possible to study the latter systematically by Monte Carlo e.g. for finite
kinetic Ising models [26,1132], although even with
the computer power available in the 21^{st} century this is a demanding
task, and thus the early work [26] could not reach a meaningful accuracy.
A subtle aspect (that still does not seem to be widely recognized) is the fact
that critical slowing down leads to a systematic bias (due to finite time
averaging) in the sampling of susceptibilities using fluctuation relations
[298]. One also needs to be aware that the latter suffer from a lack of
self-averaging [214]. At first-order transitions, rather than
critical slowing down one may encounter metastability
and hysteresis [33,76], but on the other hand, the decay of metastable states
(via nucleation and growth) is an interesting problem, both from the point of
view of analytical theory [25], phenomenological theories based on the
dynamical evolution of the “droplet” size distribution [53] and via attempts to
directly study nucleation kinetic by simulation [27,30]. However, these
early studies of nucleation phenomena in kinetic Ising
models encountered two basic difficulties: (i) due to by far
insufficient computer resources, only nucleation barriers of a few times
the thermal energy were accessible. (ii) ambiguities
in the definition of “clusters” [51]. Both difficulties could only recently be
overcome [1090], showing that only the use of the Swendsen-Wang
definition of “physical clusters” allows a consistent description of nucleation
phenomena in the Ising model, and then the classical
theory of nucleation is compatible with the observations of the kinetics.

The dynamic interpretation of Monte Carlo sampling is the basis for a broad range of kinetic Monte Carlo studies of stochastic processes, such as diffusion in concentrated (and possibly interacting) lattice gases [126,146,163], surface diffusion [161] and kinetics of domain growth [168,179], and last but not least interdiffusion in alloys [263] and spinodal decomposition of alloys using the vacancy mechanism [297,301,319]. Other groups have taken the subject of kinetic Monte Carlo and developed it to become a powerful tool of computational materials science.

3.
__Spinodal____ decomposition and the non-existence of spinodal
curves__

While generalized nonlinear Cahn-Hilliard type equations for phase
separation kinetics could be derived from kinetic Ising
models [37], it was emphasized that the critical singularities that result from
the linearization of the Cahn-Hilliard equation are a mean-field artefact, and
rather one has a gradual and smooth transition between nonlinear spinodal decomposition and nucleation [52,53,68,80,87]. To
show this, a phenomenological description of spinodal
decomposition in terms of the dynamics of many growing clusters was developed
[68,70,80], which also allowed to understand the diffusive growth law for spinodal decomposition in liquid binary mixtures [43], and
provided a dynamic scaling concept for the structure factor of phase separating
systems [61,68,80]. It was numerically demonstrated by Monte Carlo estimations
of small subsystem free energies that the spinodal
has a well defined meaning
for subsystems with a linear dimension L that is small in comparison with the
correlation length [162,181], since the order parameter in such small
subsystems always is essentially homogeneous. For large L the distance of the “spinodal” from the coexistence curve decays with the minus 4^{th} power of L (in d=3 dimensions). Later this
observation was explained via the phenomenological
theory for the “droplet evaporation/condensation transition” [750]. The latter has been studied via simulations [966].

It needs to be emphasized that the above results apply for systems with short-range interactions. When the interaction range R diverges, nucleation gets more and more suppressed (since the interfacial free energy is proportional to R), and metastable states still have a large life time rather close to the mean field spindoal [169,219,221]. Similarly, for large R the linearized Cahn theory of spinodal decomposition is predicted to hold in the initial stages, and this has been verified for phase separation of symmetrical polymer mixtures, as reviewed in [288,702]. These Ginzburg criteria [169,219,221] explain why the spinodal is useful for mean field systems but not beyond [1074].

4.
__Surface critical phenomena,
interfaces, and wetting __

At the critical point of a ferro- or antiferromagnet critical correlations at a free surface show an anisotropic power law decay, and the critical exponents describing this decay differ from the bulk [19,31,42,48,151,270]. A phenomenological scaling theory for surface critical phenomena could be derived [19,31] in collaboration with Pierre Hohenberg, including scaling laws relating the new critical exponents to each other and to bulk ones, and numerical evidence from both systematic high temperature expansions and simulations was obtained to support this theoretical description. The Monte Carlo simulation method uses periodic boundary conditions throughout to describe bulk systems, but free boundary conditions in one direction (and periodic in the other) are used to study thin magnetic films [29]. Also small (super paramagnetic) particles can be studies [8], where a combination of surface and size effects matters (see also [1082]). In ferroelectrics and dipolar magnets even on the mean field level the description gets more complicated [91,137], due to the fact that depolarizing fields cannot be neglected. For short-range systems, on the other hand, estimations of the critical exponents associated with the “surface-bulk multicritical point” have remained a longstanding challenge [178,276,283,294]. An interesting extension also is needed for surface criticality if the bulk system exhibits a Lifshitz point [590,637], since then the system exhibits anisotropic critical behavior in the bulk. This problem was treated by deriving an appropriate Landau theory from the lattice mean field theory of a semi-infinite ANNNI model. A similar concept was used to describe the dynamics of surface enrichment, deriving the proper boundary conditions at a surface for a Cahn-Hilliard type description from a lattice formulation [325], which also is the starting point to study surface-directed spinodal decomposition [333,348,427,495,559,565,605,668,748,963]. Finally, critical surface induced ordering or disordering at bulk first-order transitions was studied [302,500,618]. Qualitatively, such transitions are understood in terms of the gradual unbinding of an interface between the ordered and disordered phase of the system from a surface, reminiscent of wetting phenomena.

In fact, the understanding of interfaces between coexisting phases has been one of the longstanding research interests as well. It was already realized soon [140] that sampling the size-dependence of the minimum of the distribution of the order parameter that describes the two coexisting phases yields information on the “surface tension” (i.e., the interfacial excess free energy). Originally developed for the Ising model [140] and then for lattice models of polymer mixtures [472], this method has become one of the widely used standard methods to estimate surface tensions at gas-liquid transitions (e.g. [823,916,943], but only recently could the subtle finite size corrections to this method be clarified [1119,1127].

An interesting property of interfaces is the order parameter profile across the interface [391,392]. In d=3 dimensions lattice models can show a roughening transition [260,391], where in the thermodynamic limit the interfacial width diverges. The interfacial width then scales logarithmically with the interfacial area [392,611,669,673,833,968,999], and the mean field (van der Waals, Cahn-Hilliard, etc) concept of an “intrinsic interfacial profile” becomes doubtful. While this logarithmic broadening of the interfacial profile could also be established for solid-fluid interfaces [968,999], in solid-solid interfaces elastic interactions may suppress this broadening [819], yielding a well-defined intrinsic profile again. Particularly interesting are interfaces confined between walls in thin film geometry [555,587,588]; the resulting anomalous dependence of the interfacial width on the film thickness could also be proven to occur in thin films of unmixed polymer blends through appropriate experiments [513,578].

Interfaces confined between parallel walls can also undergo an interface location/delocalization transition [272,442,468,503,571,638,653,659,681,820]. This transition is the analog of the interface unbinding from a surface of a semi-infinite system, i.e. wetting transition, which is a difficult critical phenomenon in the case of short-range forces [206,222,233,277,295,313,353,572,1024,1061,1092]. Interesting interface unbinding transitions were also found in wedges [764,767] and bi-pyramide confinement [815,835], giving rise to unconventional new types of critical phenomena. Also interesting first-order transitions such a capillary condensation [344,356,677] can be studied for systems confined in strips, cylindrical or slit-like pores [275,834,874,1006,1008]. Then also phenomena such as heterogeneous nucleation at walls [967,974,1062] come into play; however, this problem is difficult since it requires consideration of both curvature effects on the interfacial free energy [966,1011,1045,1047,1051] and possible effects due to the line tension [1021,1131]. First steps of a methodology to deal with all these problems via simulations were developed [966,968, 1011,1021,1029,1045,1047,1051,1057,1062,1131]. Particularly challenging is the treatment of crystal nucleation from fluid phases, since in general the interface free energy depends on the interface orientation relative to the lattice axes [1135,1137,1138]. A methodology to circumvent this problem was invented [1133,1135], analyzing the equilibrium between a crystal nucleus and surrounding fluid in a finite simulation box, using a new method to sample the fluid chemical potential.

5.
__Spin glasses and
glass-forming fluids __

The “standard model” for spin glasses is the Edwards-Anderson model, i.e. an Ising Hamiltonian where the exchange coupling is a random quenched variable, either drawn from a Gaussian distribution or chosen as +/- J. First Monte Carlo simulations of this model in d=2 dimensions [60,66] showed a cusp-like susceptibility peak similar to experiment; however, now it is known that this peak simply is an effect of the finite (short) observation time, and spin glass-like freezing in d=2 occurs at zero temperature only [104,106]. Recursive transfer matrix calculations [104,106] showed that at T=0 spin-glass-type correlations exhibit a power law decay with distance in the +/-J model. The spin-glass correlation length and associated susceptibility diverge with power laws of 1/T as the temperature T tends to zero [106]. Also a more realistic site disorder model for the insulating spin glasses EuS diluted with SrS was developed, and good agreement with experiment was found [86,105], and critical magnetic fields in spin glasses were discussed [164,171]. Also some aspects of random field Ising models [159,174,421] and random field Potts models [479,521] were considered. Together with Peter Young a comprehensive review on spin glasses was written, encompassing experiments, theory, and simulation; this highly cited paper still is the standard review of the field.

Considering Edwards-Anderson models where spins are replaced by
quadrupole moments one obtains models for “quadrupolar
glasses” [234,238,250,268,291,306,474,515,567,583,679,691,694,730,766], which
can be realized experimentally by diluting molecular crystals with atoms which
have no quadrupole moment (e.g. N_{2} diluted with Ar,
or K(CN) diluted with K Cl [387]). An atomistic model for such a system was simulated in [540], and a detailed review is found in
[387].

Also various contributions were made attempting to elucidate the “grand challenge problem” how a supercooled fluid freezes into a glass. First studies were devoted to develop a lattice model for the glass transition of polymers, introducing “frustration” in the bond fluctuation model via energetic preference for long bonds, which “waste” lattice sites for further occupation by monomers [334,374,388,400,405,417,423,433,435,476,493,496,506,528,549,696]. It was shown that much of the experimental phenomenology could be reproduced (stretched relaxation, time-temperature superposition principle, Vogel-Fulcher relation describing the increase of the structural relaxation time, and evidence in favor of the mode coupling theory as a description of the initial stages of slowing down). Many of these features could also be demonstrated by molecular dynamics simulations of a more realistic off-lattice bead spring model of macromolecules [577,598,600,617,628,708,709], including an analysis of the surface effects on the glass transition in thin polymer films [708,709]. However, a particular highlight of the bond fluctuation model studies was the evidence [493,506,528] that the Gibbs-DiMarzio description of the “entropy catastrophe” at the Kauzman temperature is an artefact of rather inaccurate approximations. Also attempts to map the lattice model to real polymers gave promising results [329,519].

Molecular dynamics simulations were also carried
out for two other models of glassforming fluids, the Kob-Anderson binary Lennard-Jones mixture
[510,568,684,690,738] and a model for SiO_{2} and its mixtures with other
oxides [531,535,568,569,597,632,649,672,685] in particular; the logarithmic
dependence of the apparent glass transition temperature on the cooling rate
[510,535], evidence for the Goetze mode coupling
theory [586], evidence for growing dynamic length scales extracted from surface
effects [690,738,756,781], and percolative sodium
transport in sodium disilicate melts [736] deserve to
be mentioned. However, none of these studies
gave insight whether or not the structural relaxation time truly diverges at nonzero
temperatures, and what a proper “order parameter” distinguishing the glass from
the supercooled fluid is. The current state of the
art is summarized in a textbook (written with W. Kob) [1035]

6.
__Studies of macromolecular
systems__

While a formulation of a Monte Carlo Renormalization Group scheme [121 aimed at a better understanding of the critical exponents describing the self-avoiding walk problem, the first simulation of a dense melt of short chains [128] was motivated by experimental work [130,150] that gave evidence for the Rouse-like motions of the monomers only, not for snakelike “reptation” of the chain in a tube formed by its environment. However, later simulations of much longer chains [307,339,379,418,666] succeeded to study the crossover from the Rouse model to reptation in detail.

A famous problem of polymer science is the adsorption transition of a long flexible macromolecule from a dilute solution (under good solvent conditions) at an attractive wall [149,745,763,1012,1034,1083,1084]. In early work [149], recognizing the analogy to the surface-bulk multicritical point of the phase transitions of semi-infinite n-vector models, the deGennes conjecture for the crossover exponent could be disproven, but the precise value of this exponent has remained controversial for decades, and only recent work [1083] applying the pruned-enriched Rosenbluth method to very long chain molecules and using a comparative study of various ranges of the adsorption potential could clarify the situation. However, open questions still remain concerning the adsorption of semiflexible chains [1084]. The latter show a complicated crossover behavior also in bulk solution, particularly when exposed to stretching forces, which could be elucidated only recently [1039,1052,1077]. The fact that the standard definition of the persistence length of semiflexible polymers holds only for Gaussian “phantom chains” [933] has hampered progress in this field, in particular when the extension to polymers with complex chemical architecture (such as “bottlebrush polymers” [877,904,985,1025,1055]) is considered.

A very interesting problem involving only the statistical mechanics of a single chain concerns confinement inside a tube [188,899,934,1000] or in between parallel plates [455,566,935], or the competition between chain collapse in poor solvents [148,439,969,978] and adsorption [915,945,948,1129]. Related single chain phase transitions (which often show inequivalence between different ensembles of statistical mechanics due to the geometrical constraints that are present) concern the “escape transition” of compressed mushrooms [609,610] or compressed polymers [1107] or the “coil-bridge”-transition [1118]. Polymer collapse in poor solvents gives rise to a rich phase diagram, when bottle-brushes are considered, due to pearl necklace type structures [988,997,1010].

While for phase transition of single chains their connectivity provides unique features, phase transitions in many-chain systems often have analogs in small molecule systems, but show also characteristic differences due to the large size of a polymer coil. Nucleation and spinodal decomposition in polymer mixtures for very long chains behave almost mean-field like [166,169,399]; with respect to the critical point of unmixing, crossover from Ising to mean field behavior is observed with increasing distance from the critical point [390,399,414]. Nevertheless, the Flory-Huggins theory for polymer blends is fairly inaccurate [226], when one extracts Flory-Huggins parameter from scattering experiments via this theory a spurious concentration dependence results [240,264] and the chain linear dimensions depend on the thermodynamic state [251], particularly in semidilute solutions [446]. But early versions of integral equation theories of blends even performed worse [338]. In d=2 dimensions, however, the critical temperature scales sublinearly with chain length [744,828]. Particularly interesting is mesophase separation in block copolymer melts [315,318], where simulations revealed a pretransitional stretching (into a dumbbell-like conformation) of the chains, in agreement with experiments performed independently at the same time. Also the interplay of confinement in thin films and lamellar ordering produces a rich phase diagram, relevant for experiment [385,432,622,623], while block copolymers in selective solvent show micelle formation [585,602,654,664,878,930]. These simulations (for finite chain lengths) clearly reveal the shortcomings of the “selfconsistent field theory”, which in theoretical polymer physics often is taken as something like the “gold standard”. Also simulations of “polymer brushes” (chains grafted densely with one chain end on a planar or curved substrate) [336,365,381,434,461,697,750,771,790,837,847,869,906,944,1017,1043,1059,1067,1069 1073,1093,1116,1124] have revealed similar limitations of the standard theories. Thus, Monte Carlo simulation for polymeric systems has become a particularly fruitful method.

**MEMBERSHIPS**

-** **Deutsche Physikalische
Gesellschaft (German Physical Society)

- Hochschulverband (union of the
institutes of higher education in

- Institute of
Physics, UK (Fellow)

SFB 130 “Ferroelectrics” 1976 – 1978 (heading a
subdivision)

SFB 125 “Magnetic moments in metals” 1978 – 1983

SFB 41 “Macromolecules” 1984 – 1987 (heading a
subdivision)

SFB 262 “The glass state and glass transition of
non-metallic

amorphous materials” (heading a subdivision 1987-2001)

SFB 625 “From single molecules to nanoscopic structural materials”

(heading
a subdivision 2002-2013)

SFB TR6 “Physics of Colloidal Dispersions in
External Fields”

(heading a
subdivision 2002-2013)

1975
NATO Advanced Study
Institute, Geilo, Norway

as of 1975 MECO (Middle European Cooperation on
Statistical Physics)

1979
ICM (International
Conference on Magnetism)

1979
Jülicher Ferienkurs – The Physics of Alloys,

1980
IUPAP Conference on
Statistical Physics,

1981
Les Houches
“

1982
Jülicher Ferienkurs – The Physics of Polymers,

1983
IUPAP Conference on
Statistical Physics,

1985
ICM (International
Conference on Magnetism)

1986
IUPAP Conference on
Statistical Physics,

1989
IUPAP Conference on
Statistical Physics,

1992
IUPAP Conference on
Statistical

1993
13^{th} General
Conference of the EPS Condensed Matter Division,

1995
IUPAP Conference on
Statistical Physics,

1995 Director of Euroconference “Monte Carlo and Molecular Dynamics of
Condensed Matter Systems”

Como, Italy (with G. Ciccotti)

1996 EPS-APS Conference on Computational Physics,

1998 EPS-APS-IUPAP Conference on Computational Physics,

2000 Co-Director of NATO ARW “Multiscale Simulations in Chemistry and Biology”, Eilat,

Israel (with A. Brandt and J. Bernholc)

2001
IUPAP Conference on
Statistical Physics,

2001 EPS-APS-IUPAP Conference on
Computational Physics, CCP 2001,

2002
EPS-APS-IUPAP Conference on Computational Physics, CCP2002,

2004 IUPAP
Conference on Statistical Physics,

2004 EPS-APS-IUPAP
Conference on Computational Physics, CCP2004,

2005 Co-Director
of Erice Summer School,

2007 IUPAP
Conference on Statistical Physics,

** **2007 EPS-APS-IUPAP Conference on Computational Physics, CCP2007,

since 2010 Steering Committee of the Granada Seminar
on Computational and Statistical Physics

2010 IUPAP
Conference on Statistical Physics, Cairns, Australia

2010 EPS-APS-IUPAP
Conference on Computational Physics, CCP2010, Trondheim, Norway

2011 Liquid
Matter Conference, Vienna, Austria

2013 IUPAP
Conference on Statistical Physics, Seoul, Korea

2015 EPS-APS-IUPAP
Conference on Computational Physics, CCP 2015, Guwahati, India

2016 IUPAP
Conference on Statistical Physics, Lyon, France

1979
Springer,
Berlin *Monte Carlo Methods in Statistical Physics *(2^{nd}
Edition 1986)

1984 Springer,
*Applications of the Monte Carlo Method in Statistical Physics*

* *(2^{nd}
Edition)

1992
Springer,
*The Monte Carlo
Method in Condensed Matter Physics*

1995
Oxford
University Press, New York *Monte Carlo and Molecular Dynamics Simulations in
Polymer Science*

1996
Societa Italiana di Fisica, Bologna

*Monte Carlo and
Molecular Multiscale Computational Methods in Chemistry and*

* Physics*

2001
IOS
Press, Amsterdam *Multiscale Computational Methods in Chemistry and*

* Physics*

2006 Springer, *Computer Simulations in Condensed
Matter: From Materials*

*to**
Chemical Biology I, II*

1979 – 1982, 1988 – 1990 Editorial
board *Journal of Statistical Physics*

1984 – 1989 Editorial board *Journal of Computational Physics*

as of 1983 Editorial board *Ferroelectrics Letters*

as of 1987 Editorial board *Computer Physics Communications*

as of
1991 Editorial board *International
Journal of Modern Physics C (Physics and Computers)*

as of 1992 Editorial board *Die Makromolekulare
Chemie, Theory and Simulations*

1993 – 1996 Advisory board *Journal of Physics: Condensed Matter*

as of 1996 Advisory board *Physica**
A*

as of 1998 Editorial
boards, *Monte Carlo Methods and Applications*

2000-2002 Editorial board, *European Journal of Physics*

2000-2002 Editorial board, *Journal
of Statistical Physics*

2000-2003 Editorial
board, *Europhysics** Letters* Editorial board, *Journal of Statistical
Physics*

2003-2005
*Current Opinion in Materials Science*

2003-2005 *Physical Chemistry and Chemical Physics*

as of 2010 Journal
of Statistical Physics

2006-2011 *Journal of Physics A: Mathematics and General*

2011-2013 Advisory Board, *Journal of Chemical
Physics*

**REVIEWING**

I provide expert reviews for the
following institutions:

Membership in SFB expert reviewal groups *( Bayreuth,
Bochum-Düsseldorf-Essen, Bonn, Tübingen-Stuttgart,*

__Austrian Fund to promote scientific
research (__

__National Science Foundation__ (

__NATO Division for Scientific Affairs__ (

__Science Foundation of the Czech Republic,
of Israel, the Netherlands,
etc.__

__German Israeli Foundation (GIF)__

__BSF (Binational USA-Israel Science Foundation)__

__Referee for
numerous journals__: *Phys.
Rev. Lett., Phys. Rev. A, B, E, Physics Letters, Journal of Physics A, C, F, Europhysics Lett., Journal de Physique (Paris), Zeitschrift für Physik B, Journal of Chemical Physics,
Solid State Comm., Physics Reports, Advances in Physics, Journal of Statistical
Physics, Journal of Computational Physics, Physica
status solidi, Canadian Journal of Physics, Surface Science, Computer Phys. Commun., Colloid & Polymer Sci., Die makromolekulare Chemie, Journal of Polymer Science,
Macromolecules, Ferroelectrics, Journal of Noncrystalline
Solids, Nuclear Physics B, Langmuir; Revs.** Mod. Phys.; Eur. Phys. J. B, E; J. Phys. **Chem**. B, etc.*

Once in a while I find time to be at home. I enjoy playing the piano and do work in our garden.