Yefan Tian- Doctor of Philosophy
- PostDoc Position at Cornell University
Yefan Tian
- Doctor of Philosophy
- PostDoc Position at Cornell University
Working on low temperature physics
About
43
Publications
7,026
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386
Citations
Introduction
I am Yefan Tian, Ph.D. and M.S. in Physics, B.S. in Applied Physics. My research interests are mainly focusing on experimental condensed matter and materials physics. I also joined D3EM program using machine learning to discover and design energy materials. See more on https://www.yefantian.com/.
Skills and Expertise
Current institution
Additional affiliations
May 2014 - May 2015
Position
- Research Assistant
January 2021 - present
April 2016 - present
Education
August 2015 - December 2020
August 2015 - August 2016
August 2011 - June 2015
Publications
Publications (43)
Evidence of fluctuations in transport have long been predicted in ³He. They are expected to contribute only within 100μK of Tc and play a vital role in the theoretical modeling of ordering; they encode details about the Fermi liquid parameters, pairing symmetry, and scattering phase shifts. It is expected that they will be of crucial importance for...
By monitoring the quality factor of a quartz tuning fork oscillator we have observed a fluctuationd-driven reduction in the viscosity of bulk ³ He in the normal state near the superfluid transition temperature, T c . These fluctuations, which are only found within 100 μK of T c , play a vital role in the theoretical modeling of ordering; they encod...
Because of the extreme purity, lack of disorder, and complex order parameter, the first-order superfluid ³ He A–B transition is the leading model system for first order transitions in the early universe. Here we report on the path dependence of the supercooling of the A phase over a wide range of pressures below 29.3 bar at nearly zero magnetic fie...
We have observed a fluctuation-driven reduction in the viscosity of bulk $^3$He in the normal state near the superfluid transition. While fluctuations are ubiquitous in two dimensional superconducting materials, in three dimensions fluctuations are thought to be limited to a very narrow region near the superfluid transition temperature, $T_c$, and...
![(Color online) The PLTS temperature TPLTSh\documentclass[12pt]{minimal}...](publication/360607902/figure/fig1/AS:1183723076755458@1659232982703/Color-online-The-PLTS-temperature-TPLTShdocumentclass12ptminimal_Q320.jpg)
![(Color online) The PLTS temperature TPLTSl\documentclass[12pt]{minimal}...](publication/360607902/figure/fig2/AS:1183723076763660@1659232982740/Color-online-The-PLTS-temperature-TPLTSldocumentclass12ptminimal_Q320.jpg)
We provide the conversion parameters to allow a 3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^3$$\end{document}He melting curve thermometer to be used to calibrate...
Because of the extreme purity, lack of disorder, and complex order parameter, the first-order superfluid ³ He A-B transition is the leading model system for first order transitions in the early universe. Here we report on the path dependence of the supercooling of the A phase over a wide range of pressures below 29.3 bar at nearly zero magnetic fie...
Precise measurements of the dissipation and resonant frequency of a torsion pendulum reveal an anomaly in the inferred viscosity and normal density of liquid 3He near the superfluid transition. We present an argument that the anomaly originates in the large viscosity and large viscosity change of the normal component in the torsion tube in the vici...
We have applied nuclear magnetic resonance spectroscopy to study the distinctive network of nodal lines in the Dirac semimetal ZrSiTe. The low-T behavior is dominated by a symmetry-protected nodal line, with NMR providing a sensitive probe of the diamagnetic response of the associated carriers. A sharp low-T minimum in the NMR shift and (T1T)−1 pro...
We apply 125Te nuclear magnetic resonance (NMR) spectroscopy to investigate the Dirac semimetal ZrTe5. With the NMR magnetic field parallel to the b axis, we observe significant quantum magnetic effects. These include an abrupt drop at 150 K in spin-lattice relaxation rate. This corresponds to a gap-opening transition in the Dirac carriers, likely...
We examine the discontinuous first-order superfluid He3 A to B transition in the vicinity of the polycritical point (2.232 mK and 21.22 bar). We find path-dependent transitions: cooling at fixed pressure yields a well-defined transition line in the temperature-pressure plane, but this line can be reliably crossed by depressurizing at nearly constan...
We have applied nuclear magnetic resonance spectroscopy to study the distinctive network of nodal lines in the Dirac semimetal ZrSiTe. The low-T behavior is dominated by a symmetry-protected nodal line, with NMR providing a sensitive probe of the diamagnetic response of the associated carriers. A sharp low-T minimum in NMR shift and (T1T)−1
provide...
In this work, we describe the results of 125Te NMR measurements vs crystal orientation on an aligned-crystal sample of the topological chalcogenide ZrTe5. Results measured with B along the a crystal axis indicate a Lifshitz transition with the chemical potential crossing a gapped Dirac node. With a magnetic field of B = 9T parallel to the b axis we...
In this work, we have applied Te nuclear magnetic resonance (NMR) spectroscopy combined with density functional theory (DFT) to characterize the electronic structure of a single crystal sample of ZrSiTe. Both the NMR shift and the spin-lattice relaxation rate (1/T1) clearly show minima at 20 K. The observed T-dependence corresponds to the chemical...
We apply 125Te nuclear magnetic resonance (NMR) spectroscopy to investigate the Dirac semimetal ZrTe5. With the NMR magnetic field parallel to the b-axis, we observe significant quantum magnetic effects. These include an abrupt drop at 150 K in spin-lattice relaxation rate. This corresponds to a gap-opening transition in the Dirac carriers, likely...
We report ⁹³Nb and ¹²¹Sb NMR and ⁵⁷Fe Mössbauer studies combined with DFT calculations of Nb1−xTixFeSb (0 ≤ x ≤ 0.3), one of the most promising thermoelectric systems for applications above 1000 K. These studies provide local information about defects and electronic configurations in these heavily p-type materials. The NMR spin-lattice relaxation r...
In this work, we report nuclear magnetic resonance (NMR) combined with density functional theory studies of the transition metal dichalcogenide ZrTe2. The measured NMR shift anisotropy reveals a quasi-two-dimensional behavior connected to a topological nodal line close to the Fermi level. With the magnetic field perpendicular to the ZrTe2 layers, t...
In this paper, the hyperkagome lattice of Gd spins in a garnet compound, Gd3CrGa4O12, is studied using bulk measurements and density functional computations, and the observation of large magnetocaloric effect corresponding to an entropy change, ΔS
m
= 45 J kg-1K-1 (≈ 45 J mol-1K-1) at 2 K, 8 T is reported. Though the compound defies long-range magn...
In this work, we report nuclear magnetic resonance (NMR) combined with density functional theory (DFT) studies of the transition metal dichalcogenide ZrTe2. The measured NMR shift anisotropy reveals a quasi-2D behavior connected to a topological nodal line close to the Fermi level. With the magnetic field perpendicular to the ZrTe2 layers, the meas...
We report 59 Co, 93 Nb, and 121 Sb nuclear magnetic resonance measurements combined with density functional theory (DFT) calculations on a series of half-Heusler semiconductors, including NbCoSn, ZrCoSb, TaFeSb, and NbFeSb, to better understand their electronic properties and general composition-dependent trends. These materials are of interest as...
We report 59Co, 93Nb, and 121Sb nuclear magnetic resonance (NMR) measurements combined with density functional theory (DFT) calculations on a series of half-Heusler semiconductors, including NbCoSn, ZrCoSb, TaFeSb and NbFeSb, to better understand their electronic properties and general composition-dependent trends. These materials are of interest a...
Machine learning was utilized to efficiently boost the development of soft magnetic materials. The design process includes building a database composed of published experimental results, applying machine learning methods on the database, identifying the trends of magnetic properties in soft magnetic materials, and accelerating the design of next-ge...
Talk should be given in APS March meeting 2020 canceled due to coronavirus.
Talk should be given in APS March meeting 2020 canceled due to coronavirus.
(Accepted by Acta Materialia: https://www.sciencedirect.com/science/article/abs/pii/S1359645420303451?via%3Dihub)
Machine learning was utilized to efficiently boost the development of soft magnetic materials. The design process includes building a database composed of published experimental results, applying machine learning methods on the databas...
Cu NMR measurements are reported for the Cu-rich phase of Cu12+xSb4S13 (x ≤ 2) and compared to Cu12Sb4S13. We identify the NMR signatures of the phase segregation into Cu-poor (x ≈ 0) and Cu-rich (x ≤ 2) phases, with the metal-insulator transition observed in Cu12Sb4S13 suppressed in the Cu-rich phase. Based on NMR T1 and T2 measurements, the resul...
[to appear on Materials Today Physics] We report NMR and M\"{o}ssbauer studies along with DFT calculations of Nb$_{1-x}$Ti$_x$FeSb ($0\leqslant x \leqslant0.3$), one of the most promising thermoelectric systems. These studies provide local information about defect changes and atomic configurations in these heavily $p$-type materials. The NMR spin-l...
{63}$Cu NMR measurements are reported for the Cu-rich phase of \ch{Cu_{12+x}Sb4S13} ($x \lesssim 2$) and compared to \ch{Cu12Sb4S13}. We identify the NMR signatures of the phase segregation into Cu-poor ($x \approx 0$) and Cu-rich ($x \lesssim 2$) phases, with the metal-insulator transition observed in \ch{Cu12Sb4S13} suppressed in the Cu-rich phas...
We report 125Te NMR measurements of the topological quantum material ZrTe5. Spin-lattice relaxation results, well explained by a theoretical model of Dirac electron systems, reveal that the topological characteristic of ZrTe5 is T-dependent, changing from weak topological insulator to strong topological insulator as temperature increases. Electroni...
We report $^{59}$Co NMR and transport measurements on $n$-type filled skutterudites Ba$_x$Yb$_y$Co$_4$Sb$_{12}$ and $A$$_x$Co$_4$Sb$_{12}$ ($A$= Ba, Sr), promising thermoelectric materials. The results demonstrate consistently that a shallow defect level near the conduction band minimum dominates the electronic behavior, in contrast to the behavior...
We report $^{125}$Te NMR measurements of the topological quantum material ZrTe$_5$. Spin-lattice relaxation results, well-explained by a theoretical model of Dirac electron systems, reveal that the topological characteristic of ZrTe$_5$ is $T$-dependent, changing from weak topological insulator to strong topological insulator as temperature increas...
We report 59Co NMR and transport measurements on n-type filled skutterudites BaxYbyCo4Sb12 and AxCo4Sb12 (A = Ba or Sr), promising thermoelectric materials. The results demonstrate consistently that a shallow defect level near the conduction-band minimum dominates the electronic behavior, in contrast to the behavior of unfilled CoSb3. To analyze th...
Considered as one of the most promising thermoelectric families, skutterudite CoSb shows a high ZT value when prepared with filler atoms such as Ba, Sr, Yb, etc. We report Co NMR and transport measurements on Ba Yb Co Sb and A Co Sb (A = Ba, Sr) as promising thermoelectric candidates. To analyze the experimental results, we developed a formalism fo...
To significantly expedite the material discovery and design process, we demonstrated a machine learning study of the Febased soft magnetic materials database composed of published experimental results, which can be used to efficiently understand and optimize different properties of soft magnetic materials, thus accelerating the design process of n...
We present a ⁶³Cu and ⁶⁵Cu NMR study of Cu12Sb4S13 the basis for tetrahedrite thermoelectric materials. In addition to electronic changes observed at the Tc= 88 K metal-insulator transition, we find that locally there are significant structural changes occurring as the temperature extends above Tc, which we associate with Cu atom displacements away...
To investigate the electronic behavior and magnetic properties of NbFeSb, we have performed 93Nb NMR, specific heat and magnetic measurements on NbFeSb samples heat treated at high temperatures. Magnetic measurements, combined with an observed Schottky anomaly and changes in the NMR line width indicate the presence of a 0.2% concentrated native mag...
NMR study of partially filled skutterudites
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Three-dimensional (3D) nanoarchitectures can improve the performance of electrical energy storage systems. In this paper, combining an improved solvothermal method with calcination treatment, thin layer carbon-coated MoO2 nanoparticles with the size of 20-50 nm were uniformly dispersed in 3D graphene aerogel (abbreviated as MoO2@C-Gas). The hybrid...
In this paper, we tentatively assign the Y(4140), Y(4274) and X(4350) to be the scalar and tensor $cs\bar{c}\bar{s}$ tetraquark states, respectively, and study them with the QCD sum rules. In the operator product expansion, we take into account the vacuum condensates up to dimension-10. In calculations, we use the formula $\mu = \sqrt{M^2_{X/Y/Z}-(...
Questions
Questions (3)
Just saw more and more news about blockchain techniques. Is there any existing work or idea or proposal of using blockchain on scientific research? (Not related to bitcoin at all. Blockchain should have huge potential not just for bitcoin.)
Machine learning is hot in all fields, including physics. However, I cannot see a great future of ML in physics due to its nature based on statistics rather than physics. I always think it is absolutely not a bad idea to try our best to use ML in physics and maybe we can get something out of it. However, is it possible that ML will eventually become HUGE IN PHYSICS and then the fourth angle of physics, besides experimental, theoretical and calculational approaches.
