1976
DOI: 10.1103/physrevb.14.2812
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Thermodynamic theory of thin-filmHe3-He

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Cited by 22 publications
(13 citation statements)
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“…12) allows one to obtain the concentration and pressure profiles in the vapor and liquid phases of the mixture, as represented in Fig. 1.…”
Section: Concentration and Pressure Profiles In The Mixturementioning
confidence: 99%
See 1 more Smart Citation
“…12) allows one to obtain the concentration and pressure profiles in the vapor and liquid phases of the mixture, as represented in Fig. 1.…”
Section: Concentration and Pressure Profiles In The Mixturementioning
confidence: 99%
“…3, where we have plotted for each starting concentration xa the corresponding transition temperature T,(xa); "'... T~(xa) is defined as the higher temperature for which a solution P< Ps of Eq. (11) or (12) exists, P~ being the freezing pressure of the mixture (-25 atm around 1 K). This diagram illustrates strikingly the influence of walls on the nucleation of transitions: For a given concentration the onset wall superfluidity temperature is noticeably higher than the bulk transition temperature, except above 1.9 K, where the unfavorable pressure effect overcomes the rise of 4He concentration (see Fig.…”
Section: P |mentioning
confidence: 99%
“…That H rises with /3 is also commensurate with other measurements on the compressed mass region. 5 ' 7 ' 9 The energy-gap value, r, may reflect the nature of the substrate via the van der Waals force which produces the compression at the substrate. The neutron scattering substrate, Graphon, is characterized by a van der Waals strength about three and a half times greater than that for our substrate.…”
Section: Two-dimensional Interface Excitations: Measurements In 3 He-mentioning
confidence: 99%
“…This gradient in x is partly in a region where the superfluid is normal, even though rich in 4 He. This mechanism effectively limits the mixture to an L eff smaller than L. This effect can be estimated using a continuous model [29]. Irrespective of these refinements, it is clear that the finite-size scaling prediction based on the same geometrical confinement, but a changing j 0 ͑x͒, works well.…”
mentioning
confidence: 98%