Condensed Matter Physics Seminars are held on weekly on Thursdays from 3:00 to 4:00 PM in N288 ESC during the Fall and Winter semesters.
Condensed Matter Research at BYU
Local and intermediate-range order in functional solid-state materials (Campbell).
Systems of interest include fast-ion conductors, ferroelectric relaxors, magnetoresistive manganites, and microporous catalysts. Nanoscale structural features influence the macroscopic properties of many fascinating crystalline materials. These structures can be either static or dynamic, and consist of structural changes that spatially cooperate within regions as small as a nearest-neighbor bond (local order) or as large as a few tens of nanometers (intermediate-range order). We are developing new ways to "see" three-dimensional nanostructures in solid-state materials using advanced x-ray and neutron scattering tools, and to track them as a function of the properties that they influence. In addition to in-house diffraction experiments, we utilize state-of-the-art national and international scattering facilities, where we can probe subtle features that were previously inaccessible.
When a crystalline solid undergoes a phase transition that changes its internal structure, interesting new physical properties may arise (e.g. magetism, piezoelectricity, multiferroicity, etc). We apply the principles of group theory to the study of phase transitions that systematically lower crystal symmetry. This project has been ongoing since 1983, and involves the development of ISOTROPY software suite, which has greatly enhanced experimental and theoretical studies of material structure. We are currently working to extend these methods and tools to multi-dimensionally modulated crystals, which exhibit superspace symmetry, and which are immediately relevant to exciting new developments in condensed matter physics ranging from high-Tc superconductivity to topological spin structures.
Characterization of magnetic nanostructures by magnetometry, microscopy and X-ray spectroscopies (Chesnel)
Nanomagnetism is the study of the magnetic properties of materials at the nanometric scale. Examples of magnetic nanostructures are magnetic domains in ferromagnetic thin films and bulk materials, or assemblies of superparamagnetic nanoparticles. Many of these materials present potential interests for technological applications such as in the magnetic data storage industry. We are interested more fundamentally in characterizing the spatial morphology of such magnetic nanostructures and their behavior under the influence of temperature, external magnetic field and magnetic history. We use various tools to investigate these parameters:
Magnetic force microscopy (MFM) gives the possibility to image magnetic domains, through the dipolar interaction between the microscope probe and the magnetic stray field arising from the surface of the sample. We are currently using MFM to investigate the striped magnetic domains in CoPt films, as well as to try imaging the magnetic state of magnetite nanoparticles.
Magnetometry techniques allow the investigation of the magnetization behavior of a material under an in-situ magnetic field. We are planning to implement a Hall-Effect Magnetometer, as well as a Vibrating Sample Magnetometer. These devices will measure the magnetization as a function of magnetic field up to one tesla. In particular this will allow the measurement of hysteresis loops.
X-ray spectroscopy techniques give access to very small spatial and temporal scale information, by using the x-ray light produced by synchrotron radiation sources. We are using more specifically x-ray magnetic dichroism as well as x-ray magnetic scattering to investigate both the electronic and magnetic properties of the material. Furthermore we use coherent x-ray light at specific wavelengths in order to investigate the local morphology of the materials.
Optical measurements of spin lifetimes in semiconductors (Colton).
Spin states of electrons in semiconductors have been proposed for use in prospective "quantum computers". In order to be a viable candidate for this type of quantum computer, the material has to have good spin properties -- specifically, the spins must not change states uncontrollably due to interactions with their environment, or at least the time scales of such state changes must be relatively long. This research has focused on experimental measurements of spin lifetimes in the semiconductor GaAs (gallium arsenide), its alloys, and in semiconductor nanostructures based on GaAs & alloys. Experimental techniques combine optical spectroscopies such as photoluminescence and reflectivity with magnetic resonance of the electron and nuclear spins. Experiments are done at very low temperatures (1.5 K) and large magnetic fields (1+ tesla).
Nanoscale fabrication and imaging, experimental (Davis)
Biological Membrane Surface Imaging. The atomic force microscope is used to image soft biological structures in fluid with resolution down to the molecular level. Studies include membrane formation, protein incorporation and protein diffusion dynamics. In collaboration with David Busath (Physiology and Developmental Biology). Research supported by BYU mentoring funds.
Biomolecular electronics. Proteins and nucleic acids are candidate structures for self assembled molecular electronic materials. Conductivity measurements are performed on single horse spleen and bacterial ferritin molecules. In collaboration with Gary Watt (Chemistry and Biochemistry) and John Harb (Chemical Engineering). Research supported by NASA and BYU mentoring funds.
Nanoscale chemical patterning. Nanoscale chemical patterning of silicon and germanium surfaces has applications ranging from biomaterials to molecular electronics. An atomic force microscope probe is used to pattern surfaces with lines down to 20 nm across. In collaboration with Matthew Linford (Chemistry and Biochemistry). Research supported by NSF and BYU mentoring funds.
Nanotube mechanics. We are developing self-aligned processes for mechanical attachment of carbon nanotubes and perform atomic force microscope (AFM) based nanotube mechanics and adhesion and measurements. In collaboration with Matthew Linford (Chemistry and Biochemistry), David Tannenbaum (Pomona College), and Paul McEuen (Cornell University). Research supported by NSF.
Computational Magnetic Properties of Superconductors (Transtrum)
Superconductivity is a material state with two distinguishing properties: zero electrical resistance and magnetic field repulsion. The precise response of a superconductor to a magnetic field depends on many factors, such as the geometry of the superconducting sample, materials properties, and the magnitude, orientation, and time dependence of the magnetic field. Various materials and configurations lead to many different behaviors with useful applications, from powerful superconducting magnets to magnetic shields. We explore these properties computationally by numerically solving the equations for several models of superconductivity in diverse geometries.
Computational Modeling of emergent behavior in complex systems (Transtrum)
The macroscopic world we know is both incredibly complex and surprisingly comprehensible. Everyday, macroscopic objects consist of ~10^23 particles interacting in complex ways. In spite of this complexity, we can often model systems in relatively simple ways that belie their underlying complexity. These simple macroscopic behaviors are emergent properties of the system. Although the macroscopic behaviors are ultimately derived from the microscopic physical laws, the emergent physics is often completely different from the microscopic description. We work to derive models that describe the emergent physics from microscopic models of the system using a mixture of computational and theoretical techniques. We are currently working to derive effective models of bio-chemical systems related to cancer, as well as other models in more traditional areas of physics.
Computational Materials Science (Hart)
My research foci include high-throughput computational materials science, developing algorithms for alloy modeling, thermodynamic simulations, lattice-configuration enumeration, and using compressive sensing for building physical models. I am a co-developer of the UNCLE code for cluster expansion modeling.
High-throughput computational materials science (HTCMS) applies quantum-mechanical calculations (Density-Functional Theory, DFT) to a vast number of potential structures and materials combinations to build databases of results that can then be mined, either directly or machine learning techniques, to find promising new materials that can be verified in the laboratory. HTCMS requires extensive computing facilities, an automatic framework for generating, storing, and analyzing the results, and state of the art DFT codes.
Alloy modeling in my group utilizes HTCMS and cluster expansion.
CE-flash: An automatic framework combined with a Bayesian-inference-based compressive sensing algorithm for model building has made it possible to generate alloy models at an unprecedented rate and without any human interaction.
In collaboration with Rodney Forcade, we developed an efficient algorithm for enumerating derivative superstructures of any lattice. This has immediate application in lattice-gas models like the cluster expansion but has been used to generate trial structures for high-throughput and combinatorial searches by other groups. It can also be applied to special quasirandom structure generation and site occupancy disorder studies.