631 research outputs found
Pair correlation function of short-ranged square-well fluids
We have performed extensive Monte Carlo simulations in the canonical (NVT)
ensemble of the pair correlation function for square-well fluids with well
widths ranging from 0.1 to 1.0, in units of the diameter
of the particles. For each one of these widths, several densities and
temperatures in the ranges and
, where is the
critical temperature, have been considered. The simulation data are used to
examine the performance of two analytical theories in predicting the structure
of these fluids: the perturbation theory proposed by Tang and Lu [Y. Tang and
B. C.-Y. Lu, J. Chem. Phys. {\bf 100}, 3079, 6665 (1994)] and the
non-perturbative model proposed by two of us [S. B. Yuste and A. Santos, J.
Chem. Phys. {\bf 101}, 2355 (1994)]. It is observed that both theories
complement each other, as the latter theory works well for short ranges and/or
moderate densities, while the former theory does for long ranges and high
densities.Comment: 10 pages, 10 figure
Heat capacity of square-well fluids of variable width
We have obtained by Monte Carlo NVT simulations the constant-volume excess
heat capacity of square-well fluids for several temperatures, densities and
potential widths. Heat capacity is a thermodynamic property much more sensitive
to the accuracy of a theory than other thermodynamic quantities, such as the
compressibility factor. This is illustrated by comparing the reported
simulation data for the heat capacity with the theoretical predictions given by
the Barker-Henderson perturbation theory as well as with those given by a
non-perturbative theoretical model based on Baxter's solution of the
Percus-Yevick integral equation for sticky hard spheres. Both theories give
accurate predictions for the equation of state. By contrast, it is found that
the Barker-Henderson theory strongly underestimates the excess heat capacity
for low to moderate temperatures, whereas a much better agreement between
theory and simulation is achieved with the non-perturbative theoretical model,
particularly for small well widths, although the accuracy of the latter worsens
for high densities and low temperatures, as the well width increases.Comment: 11 pages, 4 figures; figures now include additional perturbation
data; to be published in Mol. Phy
Phase diagram of patchy colloids: towards empty liquids
We report theoretical and numerical evaluations of the phase diagram for
patchy colloidal particles of new generation. We show that the reduction of the
number of bonded nearest neighbours offers the possibility of generating liquid
states (i.e. states with temperature lower than the liquid-gas critical
temperature) with a vanishing occupied packing fraction (), a case which
can not be realized with spherically interacting particles. Theoretical results
suggest that such reduction is accompanied by an increase of the region of
stability of the liquid phase in the (-) plane, possibly favoring the
establishment of homogeneous disordered materials at small , i.e. stable
equilibrium gels.Comment: 4 pages, 4 figures, revised version, accepted in Phys. Rev. Let
¡Gamificad, insensatos!
El auge de la Gamificación en los últimos años parece imparable. Cientos de publicaciones, cursos y charlas nos dan pautas, recetas, experiencias y formas de convertir actividades “serias” en experiencias de juego gratificantes. La enseñanza no podía ser menos y también se está adentrando en el mundo de la diversión que emana del diseño de los videojuegos. Pese a todo, desgarradores lamentos y llantos desconsolados se siguen oyendo por los pasillos de los departamentos. Sollozos que anhelan estudiantes trabajadores, motivados, que lean, entiendan y presten atención, que estudien y pregunten o, por lo menos, que muestren respeto en clase. En la desesperada huida de las clases tradicionales, la Gamificación se presenta como el mesías que traerá un nuevo reinado de paz y prosperidad educativa. Además, las recetas son tan claras y lgorítmicas que ya han aparecido las primeras webs y servicios que nos añaden la capa de diversión a nuestras clases automáticamente. “Un clic aquí y dos allá y tus estudiantes nunca volverán a ser los mismos”, nos dicen. A veces los profesores parecemos principiantes: otros han tenido que venir a ponerle el palo a nuestro mocho. ¿Y qué es lo que debemos hacer ahora? Este artículo presenta un combate intelectual entre la Gamificación actual, tal y como se predica por doquier, y la experiencia acumulada de un grupo de profesores que lleva años utilizando los videojuegos y la filosofía de juego en la enseñanza. El punto de vista es crítico y práctico a la par, con la intención de transmitir las lecciones aprendidas y, sobre todo, los errores comunes en la concepción y aplicación de la Gamificación. Aviso: este artículo contiene subjetividad explícita e intencionada. No se ha maltratado ningún método científico, pero tampoco se le han hecho arrumacos.Gamification is growing unstoppable in latest years. Hundreds of publications, courses and talks give us guidelines, recipes, experiences and new ways of transforming “serious” activities into joyful playing experiences. Education has also joined the funny world that comes from game design, as you might expect. However, heartbreaking moans and desperate sobs continue to fill up departamental corridors. Sobs that yearn for diligent, motivated students; those who read, pay attention and understand, who study and ask questions..., or, at least, who show some respect during lessons. In this desperate escape from traditional lessons, Gamification shows itself as a kind of new messiah that will bring a new kingdom of peaceful and thriving education. Moreover, as recipes are so simple and algorithmical, they have given birth to websites and services that offer us an easy way to add fun to our lessons. “One click here, two there and your students will never be the same”, they ensure to us. Sometimes, we teachers seem novices: others have come before to add a stick to our mops. What are we supposed to do now? This paper presents an intelectual fighting between present Gamification models, as they are shown everywhere, and the accumulated experience of a group of teachers that have been usig games and game philosophy in their lessons for years. The analysis perspective is both critical and practical, with the aim of showing the lessons learnt together with misconceptions and common pitfalls in putting Gamification into practice. Warning: this paper contains explicit and planned subjectivity. Although no scientific method has been abused, none has received endearments
The vanishing limit of the square-well fluid: the adhesive hard sphere model as a reference system
We report a simulation study of the gas-liquid critical point for the
square-well potential, for values of well width delta as small as 0.005 times
the particle diameter sigma. For small delta, the reduced second virial
coefficient at the critical point B_2*c is found to depend linearly on delta.
The observed weak linear dependence is not sufficient to produce any
significant observable effect if the critical temperature T_c is estimated via
a constant B_2*c assumption, due to the highly non linear transformation
between B_2*c and T_c. This explains the previously observed validity of the
law of corresponding states. The critical density rho_c is also found to be
constant when measured in units of the cubed average distance between two
bonded particles (1+0.5 delta)/sigma. The possibility of describing the delta
-> 0 dependence with precise functional forms provides improved acccurate
estimates of the critical parameters of the adhesive hard-sphere AHS model.Comment: 14 pages, 4 figures, 2 table
Third-order thermodynamic perturbation theory for effective potentials that model complex fluids
We have performed Monte Carlo simulations to obtain the thermodynamic properties of fluids with two kinds of hard-core plus attractive-tail or oscillatory potentials. One of them is the square-well potential with small well width. The other is a model potential with oscillatory and decaying tail. Both model potentials are suitable for modeling the effective potential arising in complex fluids and fluid mixtures with extremely-large-size asymmetry, as is the case of the solvent-induced depletion interactions in colloidal dispersions. For the former potential, the compressibility factor, the excess energy, the constant-volume excess heat capacity, and the chemical potential have been obtained. For the second model potential only the first two of these quantities have been obtained. The simulations cover the whole density range for the fluid phase and several temperatures. These simulation data have been used to test the performance of a third-order thermodynamic perturbation theory (TPT) recently developed by one of us [ S. Zhou Phys. Rev. E 74 031119 (2006)] as compared with the well-known second-order TPT based on the macroscopic compressibility approximation due to Barker and Henderson. It is found that the first of these theories provides much better accuracy than the second one for all thermodynamic properties analyzed for the two effective potential models
Phase diagram and structural properties of a simple model for one-patch particles
We study the thermodynamic and structural properties of a simple, one-patch
fluid model using the reference hypernetted-chain (RHNC) integral equation and
specialized Monte Carlo simulations. In this model, the interacting particles
are hard spheres, each of which carries a single identical,
arbitrarily-oriented, attractive circular patch on its surface; two spheres
attract via a simple square-well potential only if the two patches on the
spheres face each other within a specific angular range dictated by the size of
the patch. For a ratio of attractive to repulsive surface of 0.8, we construct
the RHNC fluid-fluid separation curve and compare with that obtained by Gibbs
ensemble and grand canonical Monte Carlo simulations. We find that RHNC
provides a quick and highly reliable estimate for the position of the
fluid-fluid critical line. In addition, it gives a detailed (though
approximate) description of all structural properties and their dependence on
patch size.Comment: 27 pages, 10 figures, J. Chem. Phys. in pres
La nueva realidad de la educación ante los avances de la inteligencia artificial generativa
It is increasingly common to interact with products that seem “intelligent”, although the label “artificial intelligence” may have been replaced by other euphemisms. Since November 2022, with the emergence of the ChatGPT tool, there has been an exponential increase in the use of artificial intelligence in all areas. Although ChatGPT is just one of many generative artificial intelligence technologies, its impact on teaching and learning processes has been significant. This article reflects on the advantages, disadvantages, potentials, limits, and challenges of generative artificial intelligence technologies in education to avoid the biases inherent in extremist positions. To this end, we conducted a systematic review of both the tools and the scientific production that have emerged in the six months since the appearance of ChatGPT. Generative artificial intelligence is extremely powerful and improving at an accelerated pace, but it is based on large language models with a probabilistic basis, which means that they have no capacity for reasoning or comprehension and are therefore susceptible to containing errors that need to be contrasted. On the other hand, many of the problems associated with these technologies in educational contexts already existed before their appearance, but now, due to their power, we cannot ignore them, and we must assume what our speed of response will be to analyse and incorporate these tools into our teaching practice.Cada vez es más común interactuar con productos que parecen “inteligentes”, aunque quizás la etiqueta “inteligencia artificial” haya sido sustituida por otros eufemismos. Desde noviembre de 2022, con la aparición de la herramienta ChatGPT, ha habido un aumento exponencial en el uso de la inteligencia artificial en todos los ámbitos. Aunque ChatGPT es solo una de las muchas tecnologías generativas de inteligencia artificial, su impacto en los procesos de enseñanza y aprendizaje ha sido notable. Este artículo reflexiona sobre las ventajas, inconvenientes, potencialidades, límites y retos de las tecnologías generativas de inteligencia artificial en educación, con el objetivo de evitar los sesgos propios de las posiciones extremistas. Para ello, se ha llevado a cabo una revisión sistemática tanto de las herramientas como de la producción científica que ha surgido en los seis primeros meses desde la aparición de ChatGPT. La inteligencia artificial generativa es extremadamente potente y mejora a un ritmo acelerado, pero se basa en lenguajes de modelo de gran tamaño con una base probabilística, lo que significa que no tienen capacidad de razonamiento ni de comprensión y, por tanto, son susceptibles de contener fallos que necesitan ser contrastados. Por otro lado, muchos de los problemas asociados con estas tecnologías en contextos educativos ya existían antes de su aparición, pero ahora, debido a su potencia, no podemos ignorarlos solo queda asumir cuál será nuestra velocidad de respuesta para analizar e incorporar estas herramientas a nuestra práctica docente
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