Physics Commons^™

Application Of Wavelet Analysis On Transient Rlectivity In Ultra-Thin Films, S. Yousefi Saraf, R. Trappen, S. Kumari, G. Bhandari, N. Mottaghi, C. Y. Huang, G. B. Cabrera, A. D. Bristow, M. B. Holcomb

Faculty & Staff Scholarship

Applications of wavelet analysis in ultra-thin film transient reflectivity (TR) measurements have been investigated. Advantages of utilizing different localized wavelet bases, in position and time, have been addressed on the residual TR signals. Morse wavelets have been used to obtain information from the abrupt oscillatory modes in the signal, which are not distinguishable with conventional methods such as Fourier transforms. These abrupt oscillatory modes are caused by the surface, interface, or any short-lived oscillatory modes which are suppressed in the TR signal in ultra-thin films. It is demonstrated that by choosing different Morse wavelets, information regarding different oscillatory modes in …

Automated Polarization-Dependent Multidimensional Coherent Spectroscopy Phased Using Transient Absorption, J. K. Wahlstrand, G. M. Wernsing, J. Paul, A. D. Bristow

Faculty & Staff Scholarship

: An experimental apparatus is described for multidimensional optical spectroscopy with fully automated polarization control, based on liquid crystal variable retarders. Polarization dependence of rephasing two-dimensional coherent spectra are measured in a single scan, with absolute phasing performed for all polarization configurations through a single automated auxiliary measurement at the beginning of the scan. A factor of three improvement in acquisition time is demonstrated, compared to the apparatus without automated polarization control. Results are presented for a GaAs quantum well sample and an InGaAs quantum well embedded in a microcavity

Micro/Nanofabrication And Characterization Of Advanced Materials And Devices, Yanxi Li, Liang He, Mengyu Yan, Zhengjun Wang

Faculty & Staff Scholarship

No abstract provided.

Multidimensional Item Response Theory And The Force And Motion Conceptual Evaluation, Jie Yang, Cabot Zabriskie, John Stewart

Faculty & Staff Scholarship

Many studies have examined the structure and properties of the Force Concept Inventory (FCI); however, far less research has investigated the Force and Motion Conceptual Evaluation (FMCE). This study applied Multidimensional Item Response Theory (MIRT) to a sample of N ¼ 4528 FMCE post-test responses. Exploratory factor analysis showed that 5, 9, and 10-factor models optimized some fit statistics. The FMCE uses extensive blocking of items into groups with a common stem; these blocks factored together in most models. A confirmatory analysis, which constrained the MIRT models to a theoretical model constructed from expert solutions, produced a model requiring only …

Exploring The Structure Of Misconceptions In The Force Concept Inventory With Modified Module Analysis, James Wells, Rachel Henderson, John Stewart, Gay Stewart, Jie Yang, Adrienne Traxler

Faculty & Staff Scholarship

Module analysis for multiple-choice responses (MAMCR) was applied to a large sample of Force Concept Inventory (FCI) pretest and post-test responses (Npre ¼ 4509 and Npost ¼ 4716) to replicate the results of the original MAMCR study and to understand the origins of the gender differences reported in a previous study of this dataset. When the results of MAMCR could not be replicated, a modification of the method was introduced, modified module analysis (MMA). MMA was productive in understanding the structure of the incorrect answers in the FCI, identifying 9 groups of incorrect answers on the pretest and 11 groups …

Partitioning The Gender Gap In Physics Conceptual Inventories: Force Concept Inventory, Force And Motion Conceptual Evaluation, And Conceptual Survey Of Electricity And Magnetism, Rachel Henderson, John Stewart, Adrienne Traxler

Faculty & Staff Scholarship

Over the last decade, the “gender gap” in physics conceptual inventory scores has been extensively studied by the physics education research community. Researchers have identified many factors that influence the overall differences in post-test scores between men and women. More recently, it has been shown that the Force Concept Inventory (FCI) contains eight items that are substantially unfair; six are unfair to women, two are unfair to men. The Force and Motion Conceptual Evaluation (FMCE) and the Conceptual Survey of Electricity and Magnetism (CSEM), however, contain fewer unfair items. In this work, results from prior studies are used to further …

Interface Engineered Room‐Temperature Ferromagnetic Insulating State In Ultrathin Manganite Films, Weiwei Li, Bonan Zhu, Qian He, Albina Y. Borisevich, Chao Yun, Rui Wu, Ping Lu, Zhimin Qi, Qiang Wang, Aiping Chen, Haiyan Wang, Stuart A. Cavill, Kelvin H.L. Zhang, Judith L. Macmanus-Driscoll

Faculty & Staff Scholarship

emperatures near room temperature are critically needed for use in dissipationless quantum computation and spintronic devices. However, such materials are extremely rare. Here, a room‐temperature FMI is achieved in ultrathin La0.9Ba0.1MnO3 films grown on SrTiO3 substrates via an interface proximity effect. Detailed scanning transmission electron microscopy images clearly demonstrate that MnO6 octahedral rotations in La0.9Ba0.1MnO3 close to the interface are strongly suppressed. As determined from in situ X‐ray photoemission spectroscopy, O K‐edge X‐ray absorption spectroscopy, and density functional theory, the realization of the FMI state arises from a reduction of Mn eg bandwidth caused by the quenched MnO6 octahedral …

Reply To: “On The Understanding Of Current-Induced Spin Polarization Of Three-Dimensional Topological Insulators”, C. H. Li, O. M. J. Van ‘T Erve, S. Rajput, L. Li, B. T. Jonker

Faculty & Staff Scholarship

No abstract provided.

Electrical Detection Of Current Generated Spin In Topological Insulator Surface States: Role Of Interface Resistance, C. H. Li, O. M. J. Van ‘T Erve, C. Yan, L. Li., B. T. Jonker

Faculty & Staff Scholarship

Current generated spin polarization in topological insulator (TI) surface states due to spin-momentum locking has been detected recently using ferromagnet/tunnel barrier contacts, where the projection of the TI spin onto the magnetization of the ferromagnet is measured as a voltage. However, opposing signs of the spin voltage have been reported, which had been tentatively attributed to the coexistence of trivial two-dimensional electron gas states on the TI surface which may exhibit opposite currentinduced polarization than that of the TI Dirac surface states. Models based on electrochemical potential have been presented to determine the sign of the spin voltage expected for …

Multidimensional Item Response Theory And The Conceptual Survey Of Electricity And Magnetism, Cabot Zabriskie, John Stewart

Faculty & Staff Scholarship

This paper is part of the Focused Collection on Quantitative Methods in PER: A Critical Examination.] While many studies have examined the structure, validity, and reliability of the Force Concept Inventory, far less research has been performed on other conceptual instruments in widespread use in physics education research. This study performs a confirmatory analysis of the Conceptual Survey of Electricity and Magnetism (CSEM) guided by a theoretical model of expert understanding of electricity and magnetism. Multidimensional Item Response Theory (MIRT) with the discrimination matrix constrained to the theoretical model was used to investigate two large datasets (N1=2014 and N2=2657) from …

Synergy Of Physics-Based Reasoning And Machine Learning In Biomedical Applications: Towards Unlimited Deep Learning With Limited Data, Valeriy Gavrishchaka, Olga Senyukova, Mark Koepke

Faculty & Staff Scholarship

Technological advancements enable collecting vast data, i.e., Big Data, in science and industry including biomedical field. Increased computational power allows expedient analysis of collected data using statistical and machine-learning approaches. Historical data incompleteness problem and curse of dimensionality diminish practical value of pure data-driven approaches, especially in biomedicine. Advancements in deep learning (DL) frameworks based on deep neural networks (DNN) improved accuracy in image recognition, natural language processing, and other applications yet severe data limitations and/or absence of transfer-learning-relevant problems drastically reduce advantages of DNN-based DL. Our earlier works demonstrate that hierarchical data representation can be alternatively implemented without NN, …

Empirical Studies Related To Open Questions Regarding Geomagnetic Storms, Bruce Patrick Tepke

Graduate Theses, Dissertations, and Problem Reports

Earth’s magnetosphere is subject to disturbances, as evidenced by variations of the geomagnetic field in space and on the ground. It is generally understood that most such disturbances are controlled by variations in the solar wind, with interplanetary magnetic field orientations directed southward opposite to Earth’s dipole magnetic axis being most conducive to energy transfers into the magnetosphere, thus resulting in more disturbed intervals. However, the exact functional form for solar wind driving of the magnetosphere has been widely studied, with proposed functional forms varying from the simple half-wave electric rectifier to expressions with a much more complicated dependence upon …

Evaluation Of X-Ray Spectroscopic Techniques For Determining Temperature And Density In Plasmas, Theodore Scott Lane

Graduate Theses, Dissertations, and Problem Reports

Temperature and density measurements of plasmas are important for understanding various phenomena. For example, equations of state, most scaling arguments for Inertial Confinement Fusion and laboratory astrophysics all rely upon accurate knowledge of temperature and density. Spectroscopy is a non-invasive technique to measure these quantities. In this work we establish a new spectroscopic technique by using it to determine temperature. We also compare and contrast the capability of two codes, PrismSPECT and ATOMIC, to infer electron density from experimentally acquired spectra via Stark broadening.

We compare and contrast the capability of isoelectronic line ratios and inter-stage line ratios in an …

Application Of Global Search Methods To Materials Prediction And Design, Adam J. Payne

Graduate Theses, Dissertations, and Problem Reports

Due to increased availability and power of computational resources over the past few decades, prediction and design of novel materials using computational methods has become feasible. Simulation of material systems has become vital to the further realization of novel material systems. In order to ascertain physical properties, accurate determination and identification of stable crystalline structures is necessary. Additionally, further identification of novel properties, such as magnetic moments or orbital occupation, is necessary to further realize this goal. Global search methods provide a path to accurate prediction of these properties. In this dissertation, the Firefly algorithm and minima hopping methods are …

Depth Dependent Atomic Valence Determination In La0.7sr0.3mno3 Thin Films Using Synchrotron Techniques, Robbyn B. Trappen

Graduate Theses, Dissertations, and Problem Reports

The valence of atoms often has a strong effect on the properties of materials, such as magnetism, conductivity, and superconductivity. The atomic valence is often perturbed at the surface and/or interface and this deviation may play a strong role in many physical phenomena such as interfacial coupling and dead layers, both magnetic and electric. In this dissertation, I present a non-destructive approach of combining two X-ray absorption detection modes, electron yield and fluorescence, with very different probing depths in conjunction with theory to map out the layer-by-layer valence of a thin film.

The weighted average Mn atomic valence as measured …

The Structural Information Filtered Features Potential For Machine Learning Calculations Of Energies And Forces Of Atomic Systems., Jorge Arturo Hernandez Zeledon

Graduate Theses, Dissertations, and Problem Reports

In the last ten years, machine learning potentials have been successfully applied to the study of crystals, and molecules. However, more complex materials like clusters, macro-molecules, and glasses are out reach of current methods. The input of any machine learning system is a tensor of features (the most universal type are rank 1 tensors or vectors of features), the quality of any machine learning system is directly related to how well the feature space describes the original physical system. So far, the feature engineering process for machine learning potentials can not describe complex material. The current methods are highly inefficient …

Novel Computational Methods For Catalytic Applications, Gihan Uthpala Panapitiya

Graduate Theses, Dissertations, and Problem Reports

Thiolate protected nanoclusters gold nanoparticles are gaining interest of many researchers due to their promising applications in a variety of fields the development of synthesizing techniques capable of producing atomically precise nanoclusters with high purity. Au₂₅(SR)₁₈ is one of the widely studied nanoclsuters due its remarkable stability. In this first part of this study, we explore the structural, electronic and catalytic properties of bimetallic Au_25−xAg_x(SR)₁₈ (for x = 6, 7, 8). Due to the combinatorial enormity of the total number of possible alloyed isomers, we choose a randomly selected subset corresponding to …