Antiferromagnetism and Superconductivity in UPt_3

The short ranged antiferromagnetism recently seen in UPt_3 is proved incompatible with two dimensional (2D) order parameter models that take the antiferromagnetism as a symmetry breaking field. To adjust to the local moment direction, the order parameter twists over very long length scales as per the Imry-Ma argument. A variational solution to the Ginzburg-Landau equations is used to study the nature of the short ranged order. Although there are still two transitions, the lower one is of first order -- in contradiction to experiments. It is shown that the latent heat predicted by the 2D models at the lower transition is too large not to have been seen. A simple periodic model is numerically studied to show that the lower transition can not be a crossover either.Comment: To appear in Journal of Physics: Condensed Matter. 9 pages, 2 figure

Selective nitrogen adsorption via backbonding in a metal-organic framework with exposed vanadium sites.

Industrial processes prominently feature π-acidic gases, and an adsorbent capable of selectively interacting with these molecules could enable important chemical separations1-4. Biological systems use accessible, reducing metal centres to bind and activate weakly π-acidic species, such as N2, through backbonding interactions5-7, and incorporating analogous moieties into a porous material should give rise to a similar adsorption mechanism for these gaseous substrates8. Here, we report a metal-organic framework featuring exposed vanadium(II) centres capable of back-donating electron density to weak π acids to successfully target π acidity for separation applications. This adsorption mechanism, together with a high concentration of available adsorption sites, results in record N2 capacities and selectivities for the removal of N2 from mixtures with CH4, while further enabling olefin/paraffin separations at elevated temperatures. Ultimately, incorporating such π-basic metal centres into porous materials offers a handle for capturing and activating key molecular species within next-generation adsorbents

Identification of Non-unitary triplet pairing in a heavy Fermion superconductor UPt_3

A NMR experiment recently done by Tou et al. on a heavy Fermion superconductor UPt$_3$ is interpreted in terms of a non-unitary spin-triplet pairing state which we have been advocating. The proposed state successfully explains various aspects of the seemingly complicated Knight shift behaviors probed for major orientations, including a remarkable d-vector rotation under weak fields. This entitles UPt$_3$ as the first example that a charged many body system forms a spin-triplet odd-par ity pairing at low temperatures and demonstrates unambiguously that the putative spin-orbit coupling in UPt$_3$ is weak.Comment: 4 pages, 2 eps figures, to be published in J. Phys. Soc. Jpn. 67 (1998) No.

An Effective Theory for Midgap States in Doped Spin Ladder and Spin-Peierls Systems: Liouville Quantum Mechanics

In gapped spin ladder and spin-Peierls systems the introduction of disorder, for example by doping, leads to the appearance of low energy midgap states. The fact that these strongly correlated systems can be mapped onto one dimensional noninteracting fermions provides a rare opportunity to explore systems which have both strong interactions and disorder. In this paper we show that the statistics of the zero energy midgap wave functions in these models can be effectively described by Liouville Quantum Mechanics. This enables us to calculate the disorder averaged N-point correlation functions of these states (the explicit calculation is performed for N=2,3). We find that whilst these midgap states are typically weakly correlated, their disorder averaged correlation are power law. This discrepancy arises because the correlations are not self-averaging and averages of the wave functions are dominated by anomalously strongly correlated configurations.Comment: 13 page latex fil

Quasiparticle localization in superconductors with spin-orbit scattering

We develop a theory of quasiparticle localization in superconductors in situations without spin rotation invariance. We discuss the existence, and properties of superconducting phases with localized/delocalized quasiparticle excitations in such systems in various dimensionalities. Implications for a variety of experimental systems, and to the properties of random Ising models in two dimensions, are briefly discussed.Comment: 10 page

Transport and the Order Parameter of Superconducting UPt3

We calculate the ultrasonic absorption and the thermal conductivity in the superconducting state of UPt$_{3}$ as functions of temperature and direction of propagation and polarization. Two leading candidates for the superconducting order parameter are considered: the $E_{1g}$ and $E_{2u}$ representations. Both can fit the data except for the ultrasonic absorption in the $A$ phase. To do that, it is necessary to suppose that the system has only a single domain, and that must be chosen as the most favorable one. However, the $E_{2u}$ theory requires fine-tuning of parameters to fit the low temperature thermal conductivity. Thus, transport data favor the $E_{1g}$ theory. Measurements of the thermal conductivity as a function of pressure at low temperature could help to further distinguish the two theories.Comment: 7 pages, 4 figure

Nonmonotonous Magnetic Field Dependence and Scaling of the Thermal Conductivity for Superconductors with Nodes of the Order Parameter

We show that there is a new mechanism for nonmonotonous behavior of magnetic field dependence of the electronic thermal conductivity of clean superconductors with nodes of the order parameter on the Fermi surface. In particular, for unitary scatterers the nonmonotony of relaxation time takes place. Contribution from the intervortex space turns out to be essential for this effect even at low temperatures. Our results are in a qualitative agreement with recent experimental data for superconducting UPt_3. For E_{2u}-type of pairing we find approximately the scaling of the thermal conductivity in clean limit with a single parameter x=T/T_c\sqrt{B_{c2}/B} at low fields and low temperatures, as well as weak low-temperature dependence of the anisotropy ratio K_{zz}/K_{yy} in zero field. For E_{1g}-type of pairing deviations from the scaling are more noticeable and the anisotropy ratio is essentially temperature dependent.Comment: 37 pages, 8 Postscript figures, REVTE

Phase diagram of UPt3_3 in the E1gE_{1g} model

The phase diagram of the unconventional superconductor UPt$_3$ is explained under the long-standing hypothesis that the pair wavefunction belongs to the $E_{1g}$ representation of the point group. The main objection to this theory has been that it disagrees with the experimental phase diagram when a field is applied along the c-axis. By a careful analysis of the free energy this objection is shown to be incorrect. This singlet theory also explains the unusual anisotropy in the upper critical field curves, often thought to indicate a triplet pair function.Comment: 11 pages, Revtex, 2 figures (uuencoded, gzip'ed Postscript

Single Sample Expression-Anchored Mechanisms Predict Survival in Head and Neck Cancer

Gene expression signatures that are predictive of therapeutic response or prognosis are increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of expression arrays remains an unmet challenge. Additionally, there is surprisingly little gene overlap among distinct clinically validated expression signatures. These “causality challenges” hinder the adoption of signatures as compared to functionally well-characterized single gene biomarkers. To increase the utility of multi-gene signatures in survival studies, we developed a novel approach to generate “personal mechanism signatures” of molecular pathways and functions from gene expression arrays. FAIME, the Functional Analysis of Individual Microarray Expression, computes mechanism scores using rank-weighted gene expression of an individual sample. By comparing head and neck squamous cell carcinoma (HNSCC) samples with non-tumor control tissues, the precision and recall of deregulated FAIME-derived mechanisms of pathways and molecular functions are comparable to those produced by conventional cohort-wide methods (e.g. GSEA). The overlap of “Oncogenic FAIME Features of HNSCC” (statistically significant and differentially regulated FAIME-derived genesets representing GO functions or KEGG pathways derived from HNSCC tissue) among three distinct HNSCC datasets (pathways:46%, p<0.001) is more significant than the gene overlap (genes:4%). These Oncogenic FAIME Features of HNSCC can accurately discriminate tumors from control tissues in two additional HNSCC datasets (n = 35 and 91, F-accuracy = 100% and 97%, empirical p<0.001, area under the receiver operating characteristic curves = 99% and 92%), and stratify recurrence-free survival in patients from two independent studies (p = 0.0018 and p = 0.032, log-rank). Previous approaches depending on group assignment of individual samples before selecting features or learning a classifier are limited by design to discrete-class prediction. In contrast, FAIME calculates mechanism profiles for individual patients without requiring group assignment in validation sets. FAIME is more amenable for clinical deployment since it translates the gene-level measurements of each given sample into pathways and molecular function profiles that can be applied to analyze continuous phenotypes in clinical outcome studies (e.g. survival time, tumor volume)

Single Sample Expression-Anchored Mechanisms Predict Survival in Head and Neck Cancer

Gene expression signatures that are predictive of therapeutic response or prognosis are increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of expression arrays remains an unmet challenge. Additionally, there is surprisingly little gene overlap among distinct clinically validated expression signatures. These “causality challenges” hinder the adoption of signatures as compared to functionally well-characterized single gene biomarkers. To increase the utility of multi-gene signatures in survival studies, we developed a novel approach to generate “personal mechanism signatures” of molecular pathways and functions from gene expression arrays. FAIME, the Functional Analysis of Individual Microarray Expression, computes mechanism scores using rank-weighted gene expression of an individual sample. By comparing head and neck squamous cell carcinoma (HNSCC) samples with non-tumor control tissues, the precision and recall of deregulated FAIME-derived mechanisms of pathways and molecular functions are comparable to those produced by conventional cohort-wide methods (e.g. GSEA). The overlap of “Oncogenic FAIME Features of HNSCC” (statistically significant and differentially regulated FAIME-derived genesets representing GO functions or KEGG pathways derived from HNSCC tissue) among three distinct HNSCC datasets (pathways:46%, pOncogenic FAIME Features of HNSCC can accurately discriminate tumors from control tissues in two additional HNSCC datasets (n = 35 and 91, F-accuracy = 100% and 97%, empirical pp = 0.0018 and p = 0.032, log-rank). Previous approaches depending on group assignment of individual samples before selecting features or learning a classifier are limited by design to discrete-class prediction. In contrast, FAIME calculates mechanism profiles for individual patients without requiring group assignment in validation sets. FAIME is more amenable for clinical deployment since it translates the gene-level measurements of each given sample into pathways and molecular function profiles that can be applied to analyze continuous phenotypes in clinical outcome studies (e.g. survival time, tumor volume).</p