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The complementarity of experiment, theory, and simulation may be illustrated by a phase diagram of a ternary system. The balance between the three components lies in the center of the triangle. The full black line represents the early binary interaction between experiment and theory and the rise of simulation. Its end point approximates the present state of affairs. The blue dashed line indicates the “Experiments—no thank you!” scenario [30]. The black dashed line suggests a more probable future development. The system may have other dimensions not yet known as computer simulation was not perceived when Kamerlingh Onnes gave his inaugural lecture in 1882. 

The complementarity of experiment, theory, and simulation may be illustrated by a phase diagram of a ternary system. The balance between the three components lies in the center of the triangle. The full black line represents the early binary interaction between experiment and theory and the rise of simulation. Its end point approximates the present state of affairs. The blue dashed line indicates the “Experiments—no thank you!” scenario [30]. The black dashed line suggests a more probable future development. The system may have other dimensions not yet known as computer simulation was not perceived when Kamerlingh Onnes gave his inaugural lecture in 1882. 

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This paper is a contribution to the NIST Centennial 2001. It presents the first complete English translation of the inaugural speech of Heike Kamerlingh Onnes on the occasion of his appointment as Professor at the University of Leiden (The Netherlands) in 1882. The speech is a snapshot of the scientific landscape of that time and lays out a vision....

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... suggested to call B ( T ), C ( T ), ... “virial coeffi- cients.” Here, p denotes pressure, v the molar volume, T the absolute temperature, and R the universal gas constant. Mason and Spurling noted the special importance of the virial equation of state because of its sound theoretical foundation [21]. One approach is to calculate the pressure from one of the partition functions of statistical mechanics. This introduces the inverse temperature ␤ = 1/ T as the natural variable that reflects the unattainability of absolute zero, and which as early as 1964 was called “cryos” by a countryman of Kamerlingh Onnes, Professor Frederik Belinfante, then of Purdue University [22]. The appropriateness of an inverse temperature scale in view of the Third Law of Thermodynamics has been mentioned by Zemansky [23] and others even though such propositions are often based on considerations of the opposite extreme, the infinite-temperature limit. The rapid progress of low-temperature physics in going ever further down will create a growing need for a measure that is appropriate in that domain and thermo- dynamically consistent with the divergence at absolute zero. The present empirical temperature scale does not need to be replaced by an inverse temperature scale because it is consistent with the physiological sensation of hot and cold and thus useful. Rather, the linear scale and the more logical ␤ -scale should be embraced as complementary measures similar to the complementary use of reciprocal quantities such as density and volume, viscosity and fluidity, or conductance and resistance. It is noteworthy that our understanding of temperature has been expanded recently by developments of statistical thermodynamics and computer simulation [24, 25]. Kamerlingh Onnes’ speech was full of enthusiasm about the prospects that the development of experimental science into metrology offered. It culminated in the famous motto “Through measurement to knowledge.” However, he had a balanced view of the mutual fertilization between experiment and theory, and gave credit to van der Waals, whose work “stimulated numerous measurements in this field.” This binary system of knowledge acquisition through the interplay of experiment and theory has expanded into a ternary system with the advent of computers and the development of methods to employ them. Fig. 1 is an attempt to illustrate this interplay using an analog from mixture thermodynamics. Computer simulation of thermodynamic fluid properties began with the Metropolis algorithm [26, 27], which forms the basis of Monte Carlo simulations by applied statistical mechanics. The molecular-dynamics technique originated a short time later in the work of Alder and Wainwright [28, 29]. This expanded simulation capabilities to transport properties. Propelled by an exponential doubling of processor speed every 18 months (“Moore’s law”), computer simulation is now becoming a third method of knowledge acquisition that complements experiment and theory. Some protagonists seem to be overwhelmed by enthusiasm and suggest a superiority of computer simulations over measurements [30]. This attitude reminds one of 1 Cor. 12:21: “The eye cannot say to the hand, ‘I have no need of you,’ nor can the head say to the feet, ‘I have no need of you.’ ” [31]. There are at least two reasons why measurement will not be made obsolete by computer simulation. One is of a cognitive nature and the other is of an organizational nature. Kamerlingh Onnes’ speech provides guidance in both respects. The cognitive difference between measurements and simulations can be stated quite simply, as follows. Simulations observe the behavior of a model system in a ...

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... Generally, we come across such a situation in a "serendipity condition": we find something while looking for another. A typical illustration is the revealing of the superconductivity phenomenon by Kamerlingh Onnes (1853-1926), (Nobel 1913: for his investigations on the properties of matter at low temperatures which led, inter alia, to the production of liquid helium) [16]. In this context, he was studying the problems connecting to the effects of low temperatures on electronics. ...
... Usually, we come across such a case in a "serendipity situation": we discover something while looking for another. A representative illustration is the revealing of superconductivity phenomenon by Kamerlingh Onnes (1853-1926), (Nobel 1913: for his investigations on the properties of matter at low temperatures which led, inter alia, to the production of liquid helium) [13]. In this circumstance, he was studying the problems relating to the effects of low temperatures on electronics. ...
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Matching of a real procedure with its virtual model is performed in a variety of natural and artificial situations. The exercise of this concept in science, technology, and innovation is assessed in this review. This involves off-line as well as real-time pairing practices. The off-line case regards mainly management and ruling of elegant theories, computing tools imitating physical paradigms and computer aided design. The real-time pairing concerns in particular natural phenomena, online matching devices in autonomous automated systems and in complex procedures. The article is constituted of three consequential divisions: the observation-theory framework, innovations relative to matching concepts, and observation-modeling matching in complex procedures. The paper first presents a framework for the observation-theory pair. This will highlight the complementary aspect of such a duo, its ability to validate or invalidate an elegant theory, its use to explicate an observation, and finally, how a theory can unify different observations into an elegant mathematical representation. At the end of this section, innovative computing tools that imitate physical paradigms are exposed. In the following section, the paper then illustrates recent innovations relating to the notions of pairing concerning theories addressing natural functions and design approaches in industry, as well as the task of matching virtual estimates to their actual values in automated systems. The role of the observation-modeling pair in complex procedures is then investigated in the last part. In this frame, matched twins in complex procedures are examined, highlighting the concept of the digital twin. Examples of use of this concept are presented to illustrate the range of its applications in different domains, including energy, production, maintenance, mobility, healthcare, smart cities, etc. Doi: 10.28991/HEF-2021-02-04-010 Full Text: PDF
... More than one hundred years after the statement that certainty in science requires the confirmation of insights by measurement [1], the scientific community is acknowledging a reproducibility crisis in the last few years [2]. ...
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... Quantitative calculations of the properties of liquids with complex molecular structures, such as studied in this work, are not yet within reach of ab initio methods. Measurements will remain the primary path to knowledge in the foreseeable future [81]. ...
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The viscosities of three pentaerythritol tetraalkanoate ester base oils and one fully formulated lubricant were measured with an oscillating piston viscometer in the overall temperature range from 275 K to 450 K with pressures up to 137 MPa. The alkanoates were pentanoate, heptanoate, and nonanoate. Three sensing cylinders covering the combined viscosity range from 1 mPa·s to 100 mPa·s were calibrated with squalane. This required a re-correlation of a squalane viscosity data set in the literature that was measured with a vibrating wire viscometer, with an estimated extended uncertainty of 2 %, because the squalane viscosity formulations in the literature did not represent this data set within its experimental uncertainty. In addition, a new formulation for the viscosity of squalane at atmospheric pressure was developed that represents experimental data from 169.5 K to 473 K within their estimated uncertainty over a viscosity range of more than eleven orders of magnitude. The viscosity of squalane was measured over the entire viscometer range, and the results were used together with the squalane correlations to develop accurate calibrating functions for the instrument. The throughput of the instrument was tripled by a custom-developed LabVIEW application. The measured viscosity data for the ester base oils and the fully formulated lubricant were tabulated and compared with literature data. An unpublished viscosity data set for pentaerythritol tetrapentanoate measured in this laboratory in 2006 at atmospheric pressure from 253 K to 373 K agrees with the new data within their experimental uncertainty and confirms the deviations from the literature data. The density data measured in this project for the three base oils deviate from the literature data in a way that is by sign and magnitude consistent with the deviations of the viscosity data. This points to differences in the sample compositions as the most likely cause for the deviations.
... "Through measurement to knowledge," coined by Kamerlingh Onnes in 1882, succinctly conveys the critical role of measurement in science (Laesecke, 2002). historically, significant advances in scientific understanding have followed advances in measurement and observation. ...
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... I n 1882, in a lecture at the University of Leiden, Nobel prizewinner Heike Kammerlingh Onnes coined the motto: "Through Measurement to Knowledge" [1]. In that same lecture, he gave many historical examples of how measurements have fostered insight, including accounts of how Coulomb and Faraday used torsion-balance measurements to learn the fundamental properties of electromagnetic forces. ...
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... It is interesting to note that if it is true that the first part of the whole program of researches in low temperatures at Leiden was specially focused on liquefaction of gases and related areas, the subject of electricity, and specifically the behavior of electrical properties in the same zone, not only arose the interest of Kamerlingh Onnes from the beginnings of his work, but also became one of the parts of what he called "the unity of natural phenomena" [39]. It is clearly revealed in his lecture on the importance of quantitative research on the occasion of his appointment as professor of experimental physics at the University of Leiden in 1882, in which Kamerlingh Onnes devoted an appreciable portion to different electrical subjects [40]. ...
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Liquefaction of helium and the discovery of superconductivity are two of the most striking developments in low temperature physics. The fact that both were carried out in the laboratories of Kamerlingh Onnes at Leiden is not mere coincidence; the first one was indispensable for the researches that led to the second one. On the same way, liquefaction of helium was the consequence of several decades of efforts addressed to the process for liquefy the so-called then 'permanent gases'. A whole study of this remarked subject must then include developments that extended, in his decisive step, more than a half of a century and that connect researches of many scientists throughout several European countries.
... Liquid helium has been studied for the past 100 years, and there is no question that liquid helium is of central importance in this field. (I would like to turn readers' attention to Ref. [1]. It presents the first complete English translation of the inaugural speech of Heike Kamerlingh Onnes at the University of Leiden in 1882. ...
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We derive an analytical expression for a critical temperature of spontaneous symmetry breaking in a repulsive hard-core interacting Bose system. We show that the critical temperature of spontaneous symmetry breaking in a hard-core interacting Bose system is determined by the three physical parameters: the density of Bose liquid at absolute zero (rho_0), the mass (m) and the hard sphere diameter (sigma) of a boson. The formula that we have derived is Tc = rho_0 pi hbar^2 sigma / m^2 kB. We report Tc of liquid helium-4 is 2.194 K, which is significantly close to the lambda temperature of 2.1768 K. The deviation between the predicted and experimental values of the lambda temperature is less than 1%. Comment: 4 pages, 5 figures; v2 typos corrected, a reference added
... The difference between simulation and experiment has been succinctly stated by Laesecke and van der Gulik (2002). Simulations provide insight into the behavior of a model system in a given thermodynamic state for specified interactions (electronic wave function and/or force fields used to approximate the real interactions). ...
Chapter
The Leiden Physics Cabinet dates back to 1675, when the professor of philosophy Burchard de Volder (1643–1709) was given permission to set up a small house as the Theatrum Physicum, next to the Hortus Botanicus botanical gardens. In 1742, the Cabinet was elevated to the largest collection of instruments in the world when the Leiden University governors bought the private collection of Willem Jacob ’s Gravesande. In the nineteenth-century the Leiden Physics Cabinet began to lag behind. In 1859, it moved into a new building in the inner city. Splendid feats have been accomplished and pioneering discoveries made, such as the liquefaction of helium (1908) and the discovery of superconductivity (1911), both by Heike Kamerlingh Onnes. In fact, Kamerlingh Onnes introduced what was later to be known as Big Science. With his orchestrated approach to research he set an example that was followed by other laboratories.