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Missouri University of Science and Technology

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2018

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Articles 31 - 60 of 162

Full-Text Articles in Physical Sciences and Mathematics

A Distributed Semi-Supervised Platform For Dnase-Seq Data Analytics Using Deep Generative Convolutional Networks, Shayan Shams, Richard Platania, Joohyun Kim, Jian Zhang, Kisung Lee, Seungwon Yang, Seung Jong Park Aug 2018

A Distributed Semi-Supervised Platform For Dnase-Seq Data Analytics Using Deep Generative Convolutional Networks, Shayan Shams, Richard Platania, Joohyun Kim, Jian Zhang, Kisung Lee, Seungwon Yang, Seung Jong Park

Computer Science Faculty Research & Creative Works

A deep learning approach for analyzing DNase-seq datasets is presented, which has promising potentials for unraveling biological underpinnings on transcription regulation mechanisms. Further understanding of these mechanisms can lead to important advances in life sciences in general and drug, biomarker discovery, and cancer research in particular. Motivated by recent remarkable advances in the field of deep learning, we developed a platform, Deep Semi-Supervised DNase-seq Analytics (DSSDA). Primarily empowered by deep generative Convolutional Networks (ConvNets), the most notable aspect is the capability of semi-supervised learning, which is highly beneficial for common biological settings often plagued with a less sufficient number of …

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Gpu-Accelerated Large-Scale Genome Assembly, Sayan Goswami, Kisung Lee, Shayan Shams, Seung Jong Park Aug 2018

Gpu-Accelerated Large-Scale Genome Assembly, Sayan Goswami, Kisung Lee, Shayan Shams, Seung Jong Park

Computer Science Faculty Research & Creative Works

Spurred by a widening gap between hardware accelerators and traditional processors, numerous bioinformatics applications have harnessed the computing power of GPUS and reported substantial performance improvements compared to their CPU-based counterparts. However, most of these GPU-based applications only focus on the read alignment problem, while the field of de novo assembly still relies mostly on CPU-based solutions. This is primarily due to the nature of the assembly workload which is not only compute-intensive but also extremely data-intensive. Such workloads require large memories, making it difficult to adapt them to use GPUS with their limited memory capacities. To the best of …

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Algorithms Cs2500, Simone Silvestri, Ken Goss, Zhishan Guo, Ashikahmed Bhuiyan Aug 2018

Algorithms Cs2500, Simone Silvestri, Ken Goss, Zhishan Guo, Ashikahmed Bhuiyan

AOER Course Materials

No abstract provided.

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Dynamics Of Paramagnetic And Ferromagnetic Ellipsoidal Particles In Shear Flow Under A Uniform Magnetic Field, Christopher A. Sobecki, Jie Zhang, Yanzhi Zhang, Cheng Wang Aug 2018

Dynamics Of Paramagnetic And Ferromagnetic Ellipsoidal Particles In Shear Flow Under A Uniform Magnetic Field, Christopher A. Sobecki, Jie Zhang, Yanzhi Zhang, Cheng Wang

Mathematics and Statistics Faculty Research & Creative Works

We investigate the two-dimensional dynamic motion of magnetic particles of ellipsoidal shapes in shear flow under the influence of a uniform magnetic field. In the first part, we present a theoretical analysis of the rotational dynamics of the particles in simple shear flow. By considering paramagnetic and ferromagnetic particles, we study the effects of the direction and strength of the magnetic field on the particle rotation. The critical magnetic-field strength, at which particle rotation is impeded, is determined. In a weak-field regime (i.e., below the critical strength) where the particles execute complete rotations, the symmetry property of the rotational velocity …

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Scanning Tunneling Spectroscopy Investigations Of Superconducting-Doped Topological Insulators: Experimental Pitfalls And Results, Stefan Wilfert, Paolo Sessi, Zhiwei Wang, Henrik Schmidt, M. Carmen Martínez-Velarte, Seng Huat Lee, Yew San Hor, Alexander F. Otte, Yoichi Ando, Weida Wu, Matthias Bode Aug 2018

Scanning Tunneling Spectroscopy Investigations Of Superconducting-Doped Topological Insulators: Experimental Pitfalls And Results, Stefan Wilfert, Paolo Sessi, Zhiwei Wang, Henrik Schmidt, M. Carmen Martínez-Velarte, Seng Huat Lee, Yew San Hor, Alexander F. Otte, Yoichi Ando, Weida Wu, Matthias Bode

Physics Faculty Research & Creative Works

Recently, the doping of topological insulators has attracted significant interest as a potential route towards topological superconductivity. Because many experimental techniques lack sufficient surface sensitivity, however, definite proof of the coexistence of topological surface states and surface superconductivity is still outstanding. Here we report on highly surface sensitive scanning tunneling microscopy and spectroscopy experiments performed on Tl-doped Bi2Te3, a three-dimensional topological insulator which becomes superconducting in the bulk at TC=2.3 K. Landau level spectroscopy as well as quasiparticle interference mapping clearly demonstrated the presence of a topological surface state with a Dirac point energy …

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Extinction Transitions In Correlated External Noise, Alexander H. O. Wada, Matthew Small, Thomas Vojta Aug 2018

Extinction Transitions In Correlated External Noise, Alexander H. O. Wada, Matthew Small, Thomas Vojta

Physics Faculty Research & Creative Works

We analyze the influence of long-range correlated (colored) external noise on extinction phase transitions in growth and spreading processes. Uncorrelated environmental noise (i.e., temporal disorder) was recently shown to give rise to an unusual infinite-noise critical point [Europhys. Lett. 112, 30002 (2015)EULEEJ0295-507510.1209/0295-5075/112/30002]. It is characterized by enormous density fluctuations that increase without limit at criticality. As a result, a typical population decays much faster than the ensemble average, which is dominated by rare events. Using the logistic evolution equation as an example, we show here that positively correlated (red) environmental noise further enhances these effects. This means, the correlations accelerate …

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Quantum Critical Behavior Of A Three-Dimensional Superfluid-Mott Glass Transition, Jack Crewse, Cameron Lerch, Thomas Vojta Aug 2018

Quantum Critical Behavior Of A Three-Dimensional Superfluid-Mott Glass Transition, Jack Crewse, Cameron Lerch, Thomas Vojta

Physics Faculty Research & Creative Works

The superfluid to insulator quantum phase transition of a three-dimensional particle-hole symmetric system of disordered bosons is studied. To this end, a site-diluted quantum rotor Hamiltonian is mapped onto a classical (3+1)-dimensional XY model with columnar disorder and analyzed by means of large-scale Monte Carlo simulations. The superfluid-Mott insulator transition of the clean, undiluted system is in the four-dimensional XY universality class and shows mean-field critical behavior with logarithmic corrections. The clean correlation length exponent ν=1/2 violates the Harris criterion, indicating that disorder must be a relevant perturbation. For nonzero dilutions below the lattice percolation threshold of pc=0.688392, …

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The Role Of Multiple Electron Processes For Fast Ion H₂O Collisions, N. Bachi, G. S. Otero, S. Otranto, Ronald E. Olson Aug 2018

The Role Of Multiple Electron Processes For Fast Ion H₂O Collisions, N. Bachi, G. S. Otero, S. Otranto, Ronald E. Olson

Physics Faculty Research & Creative Works

In this work, collision processes between C6+, O8+ and Si13+ ions and H2O molecules that lead to target ionization are studied by means of the classical trajectory Monte Carlo method. We employ an 8-electron model in which the H2O electron densities and energies dynamically adapt during ionization processes to those corresponding to the H2Oq+ ions by assuming vertical transitions between the different molecular ionic states. Net total ionization cross sections and single differential cross sections in energy and angle are shown for 4 MeV/u projectiles and compared to available …

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Towards Distributed Cyberinfrastructure For Smart Cities Using Big Data And Deep Learning Technologies, Shayan Shams, Sayan Goswami, Kisung Lee, Seungwon Yang, Seung Jong Park Jul 2018

Towards Distributed Cyberinfrastructure For Smart Cities Using Big Data And Deep Learning Technologies, Shayan Shams, Sayan Goswami, Kisung Lee, Seungwon Yang, Seung Jong Park

Computer Science Faculty Research & Creative Works

Recent advances in big data and deep learning technologies have enabled researchers across many disciplines to gain new insight into large and complex data. For example, deep neural networks are being widely used to analyze various types of data including images, videos, texts, and time-series data. In another example, various disciplines such as sociology, social work, and criminology are analyzing crowd-sourced and online social network data using big data technologies to gain new insight from a plethora of data. Even though many different types of data are being generated and analyzed in various domains, the development of distributed city-level cyberinfrastructure …

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Tuning A Random-Field Mechanism In A Frustrated Magnet, Shashikant Singh Kunwar, Arnab Sen, Thomas Vojta, Rajesh Narayanan Jul 2018

Tuning A Random-Field Mechanism In A Frustrated Magnet, Shashikant Singh Kunwar, Arnab Sen, Thomas Vojta, Rajesh Narayanan

Physics Faculty Research & Creative Works

We study the influence of spinless impurities on a frustrated magnet featuring a spin-density wave (stripe) phase by means of Monte Carlo simulations. We demonstrate that the interplay between the impurities and an order parameter that breaks a real-space symmetry triggers the emergence of a random-field mechanism which destroys the stripe-ordered phase. Importantly, the strength of the emerging random fields can be tuned by the repulsion between the impurity atoms; they vanish for perfect anticorrelations between neighboring impurities. This provides a way of controlling the phase diagram of a many-particle system. In addition, we also investigate the effects of the …

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Automated Design Of Network Security Metrics, Aaron Scott Pope, Daniel R. Tauritz, Robert Morning, Alexander D. Kent Jul 2018

Automated Design Of Network Security Metrics, Aaron Scott Pope, Daniel R. Tauritz, Robert Morning, Alexander D. Kent

Computer Science Faculty Research & Creative Works

Many abstract security measurements are based on characteristics of a graph that represents the network. These are typically simple and quick to compute but are often of little practical use in making real-world predictions. Practical network security is often measured using simulation or real-world exercises. These approaches better represent realistic outcomes but can be costly and time-consuming. This work aims to combine the strengths of these two approaches, developing efficient heuristics that accurately predict attack success. Hyper-heuristic machine learning techniques, trained on network attack simulation training data, are used to produce novel graph-based security metrics. These low-cost metrics serve as …

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The Automated Design Of Probabilistic Selection Methods For Evolutionary Algorithms, Samuel N. Richter, Daniel R. Tauritz Jul 2018

The Automated Design Of Probabilistic Selection Methods For Evolutionary Algorithms, Samuel N. Richter, Daniel R. Tauritz

Computer Science Faculty Research & Creative Works

Selection functions enable Evolutionary Algorithms (EAs) to apply selection pressure to a population of individuals, by regulating the probability that an individual's genes survive, typically based on fitness. Various conventional fitness based selection methods exist, each providing a unique relationship between the fitnesses of individuals in a population and their chances of selection. However, the full space of selection algorithms is only limited by max algorithm size, and each possible selection algorithm is optimal for some EA configuration applied to a particular problem class. Therefore, improved performance may be expected by tuning an EA's selection algorithm to the problem at …

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Detonation Synthesis Of Alpha-Variant Silicon Carbide, Martin Langenderfer, Catherine E. Johnson, William Fahrenholtz, Vadym Mochalin Jul 2018

Detonation Synthesis Of Alpha-Variant Silicon Carbide, Martin Langenderfer, Catherine E. Johnson, William Fahrenholtz, Vadym Mochalin

Mining Engineering Faculty Research & Creative Works

A recent research study has been undertaken to develop facilities for conducting detonation synthesis of nanomaterials. This process involves a familiar technique that has been utilized for the industrial synthesis of nanodiamonds. Developments through this study have allowed for experimentation with the concept of modifying explosive compositions to induce synthesis of new nanomaterials. Initial experimentation has been conducted with the end goal being synthesis of alpha variant silicon carbide (α-SiC) in the nano-scale. The α-SiC that can be produced through detonation synthesis methods is critical to the ceramics industry because of a number of unique properties of the material. Conventional …

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Evolution Of Network Enumeration Strategies In Emulated Computer Networks, Sean Harris, Eric Michalak, Kevin Schoonover, Adam Gausmann, Hannah Reinbolt, Joshua Herman, Daniel R. Tauritz, Chris Rawlings, Aaron Scott Pope Jul 2018

Evolution Of Network Enumeration Strategies In Emulated Computer Networks, Sean Harris, Eric Michalak, Kevin Schoonover, Adam Gausmann, Hannah Reinbolt, Joshua Herman, Daniel R. Tauritz, Chris Rawlings, Aaron Scott Pope

Computer Science Faculty Research & Creative Works

Successful attacks on computer networks today do not often owe their victory to directly overcoming strong security measures set up by the defender. Rather, most attacks succeed because the number of possible vulnerabilities are too large for humans to fully protect without making a mistake. Regardless of the security elsewhere, a skilled attacker can exploit a single vulnerability in a defensive system and negate the benefits of those security measures. This paper presents an evolutionary framework for evolving attacker agents in a real, emulated network environment using genetic programming, as a foundation for coevolutionary systems which can automatically discover and …

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Flexible To Rigid Nanoporous Polyurethane-Acrylate (Puac) Type Materials For Structural And Thermal Insulation Applications, Nicholas Leventis, Chariklia Sotiriou-Leventis, Abhishek Bang Jun 2018

Flexible To Rigid Nanoporous Polyurethane-Acrylate (Puac) Type Materials For Structural And Thermal Insulation Applications, Nicholas Leventis, Chariklia Sotiriou-Leventis, Abhishek Bang

Chemistry Faculty Research & Creative Works

Novel urethane-acrylate (UAC) Star monomers and polyurethane-acrylate (PUAC) aerogel polymers derived therefrom are described herein, along with other novel, related monomers and polymers. Also described herein are processes for preparing the UAC Star monomers, the PUAC aerogel polymers, and the other related monomers and polymers. The PUAC and related polymers herein are useful in various applications including in structural and thermal insulation.

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Improving Performance Of Iterative Methods By Lossy Checkponting, Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, Franck Cappello Jun 2018

Improving Performance Of Iterative Methods By Lossy Checkponting, Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, Franck Cappello

Computer Science Faculty Research & Creative Works

Iterative methods are commonly used approaches to solve large, sparse linear systems, which are fundamental operations for many modern scientific simulations. When the large-scale iterative methods are running with a large number of ranks in parallel, they have to checkpoint the dynamic variables periodically in case of unavoidable fail-stop errors, requiring fast I/O systems and large storage space. To this end, significantly reducing the checkpointing overhead is critical to improving the overall performance of iterative methods. Our contribution is fourfold. (1) We propose a novel lossy checkpointing scheme that can significantly improve the checkpointing performance of iterative methods by leveraging …

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Evolution Of Structure And Superconductivity In Ba(Ni₁₋ₓcoₓ)₂As₂, Chris Eckberg, Limin Wang, Halyna Hodovanets, Hyunsoo Kim, Daniel J. Campbell, Peter Zavalij, Philip Piccoli, Johnpierre Paglione Jun 2018

Evolution Of Structure And Superconductivity In Ba(Ni₁₋ₓcoₓ)₂As₂, Chris Eckberg, Limin Wang, Halyna Hodovanets, Hyunsoo Kim, Daniel J. Campbell, Peter Zavalij, Philip Piccoli, Johnpierre Paglione

Physics Faculty Research & Creative Works

The effects of Co substitution on Ba(Ni1-xCox)2As2 (0 ≤ x ≤ 0.251) single crystals grown out of Pb flux are investigated via transport, magnetic, and thermodynamic measurements. BaNi2As2 exhibits a first-order tetragonal to triclinic structural phase transition at Ts = 137 K upon cooling, and enters a superconducting phase below Tc = 0.7 K. The structural phase transition is sensitive to cobalt content and is suppressed completely by x ≥ 0.133. The superconducting critical temperature, Tc, increases continuously with x, reaching a maximum of Tc …

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Identity-Adaptive Facial Expression Recognition Through Expression Regeneration Using Conditional Generative Adversarial Networks, Huiyuan Yang, Zheng Zhang, Lijun Yin Jun 2018

Identity-Adaptive Facial Expression Recognition Through Expression Regeneration Using Conditional Generative Adversarial Networks, Huiyuan Yang, Zheng Zhang, Lijun Yin

Computer Science Faculty Research & Creative Works

Subject variation is a challenging issue for facial expression recognition, especially when handling unseen subjects with small-scale labeled facial expression databases. Although transfer learning has been widely used to tackle the problem, the performance degrades on new data. In this paper, we present a novel approach (so-called IA-gen) to alleviate the issue of subject variations by regenerating expressions from any input facial images. First of all, we train conditional generative models to generate six prototypic facial expressions from any given query face image while keeping the identity related information unchanged. Generative Adversarial Networks are employed to train the conditional generative …

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Heterogeneous Activity Causes A Nonlinear Increase In The Group Energy Use Of Ant Workers Isolated From Queen And Brood, Nolan Ferral, Kyara Holloway, Mingzhong Li, Zhaozheng Yin, Chen Hou Jun 2018

Heterogeneous Activity Causes A Nonlinear Increase In The Group Energy Use Of Ant Workers Isolated From Queen And Brood, Nolan Ferral, Kyara Holloway, Mingzhong Li, Zhaozheng Yin, Chen Hou

Computer Science Faculty Research & Creative Works

Increasing evidence has shown that the energy use of ant colonies increases sublinearly with colony size so that large colonies consume less per capita energy than small colonies. It has been postulated that social environment (e.g., in the presence of queen and brood) is critical for the sublinear group energetics, and a few studies of ant workers isolated from queens and brood observed linear relationships between group energetics and size. In this paper, we hypothesize that the sublinear energetics arise from the heterogeneity of activity in ant groups, that is, large groups have relatively more inactive members than small groups. …

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Relativistic And Radiative Corrections To The Dynamic Stark Shift: Gauge Invariance And Transition Currents In The Velocity Gauge, Ulrich D. Jentschura, Chandra M. Adhikari Jun 2018

Relativistic And Radiative Corrections To The Dynamic Stark Shift: Gauge Invariance And Transition Currents In The Velocity Gauge, Ulrich D. Jentschura, Chandra M. Adhikari

Physics Faculty Research & Creative Works

We investigate the gauge invariance of the dynamic (ac) Stark shift under "hybrid" gauge transformations from the "length" (E·r ) to the "velocity" (A-·p ) gauge. By a "hybrid" gauge transformation, we understand a transformation in which the scalar and vector potentials are modified, but the wave function remains unaltered. The gauge invariance of the leading term is well known, while we here show that gauge invariance under perturbations holds only if one takes into account an additional correction to the transition current, which persists only in the velocity gauge. We find a general expression for this current, and apply …

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Overpumping Leads To California Groundwater Arsenic Threat, Ryan G. Smith, Rosemary Knight, Scott Fendorf Jun 2018

Overpumping Leads To California Groundwater Arsenic Threat, Ryan G. Smith, Rosemary Knight, Scott Fendorf

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Water resources are being challenged to meet domestic, agricultural, and industrial needs. To complement finite surface water supplies that are being stressed by changes in precipitation and increased demand, groundwater is increasingly being used. Sustaining groundwater use requires considering both water quantity and quality. A unique challenge for groundwater use, as compared with surface water, is the presence of naturally occurring contaminants within aquifer sediments, which can enter the water supply. Here we find that recent groundwater pumping, observed through land subsidence, results in an increase in aquifer arsenic concentrations in the San Joaquin Valley of California. By comparison, historic …

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Scalable, Hydrophobic And Highly-Stretchable Poly(Isocyanurate-Urethane) Aerogels, Sadeq Malakooti, Saman Rostami, Habel Gitogo Churu, Huiyang Luo, Jenna Clark, Fabiola Casarez, Owen Rettenmaier, Soheil Daryadel, Majid Minary-Jolandan, Chariklia Sotiriou-Leventis, Nicholas Leventis, Hongbing Lu Jun 2018

Scalable, Hydrophobic And Highly-Stretchable Poly(Isocyanurate-Urethane) Aerogels, Sadeq Malakooti, Saman Rostami, Habel Gitogo Churu, Huiyang Luo, Jenna Clark, Fabiola Casarez, Owen Rettenmaier, Soheil Daryadel, Majid Minary-Jolandan, Chariklia Sotiriou-Leventis, Nicholas Leventis, Hongbing Lu

Chemistry Faculty Research & Creative Works

Scalable, low-density and flexible aerogels offer a unique combination of excellent mechanical properties and scalable manufacturability. Herein, we report the fabrication of a family of low-density, ambient-dried and hydrophobic poly(isocyanurate-urethane) aerogels derived from a triisocyanate precursor. The bulk densities ranged from 0.28 to 0.37 g cm-3 with porosities above 70% v/v. The aerogels exhibit a highly stretchable behavior with a rapid increase in the Young's modulus with bulk density (slope of log-log plot > 6.0). In addition, the aerogels are very compressible (more than 80% compressive strain) with high shape recovery rate (more than 80% recovery in 30 s). Under …

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Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny Jun 2018

Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The common modeling of digital twins uses an information model to describe the physical machines. The integration of digital twins into productive cyber-physical cloud manufacturing (CPCM) systems imposes strong demands such as reducing overhead and saving resources. In this paper, we develop and investigate a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform. Our method helps reduce computing resources in the information processing center for efficient interactions between human users and physical machines. We introduce a knowledge resource center (KRC) built on a cloud server for information intensive applications. An information model …

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Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin Jun 2018

Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In a smart manufacturing system involving workers, recognition of the worker's activity can be used for quantification and evaluation of the worker's performance, as well as to provide onsite instructions with augmented reality. In this paper, we propose a method for activity recognition using Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals obtained from a Myo armband. The raw 10-channel IMU signals are stacked to form a signal image. This image is transformed into an activity image by applying Discrete Fourier Transformation (DFT) and then fed into a Convolutional Neural Network (CNN) for feature extraction, resulting in a high-level …

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Dynamic Effects In Electron Momentum Spectroscopy Of Sulfur Hexafluoride, Xing Wang, Shenyue Xu, Chuangang Ning, O. Al-Hagan, Pengfei Hu, Yongtao Zhao, Zhongfen Xu, Jingkang Deng, Enliang Wang, Xueguang Ren, Alexander Dorn, Don H. Madison Jun 2018

Dynamic Effects In Electron Momentum Spectroscopy Of Sulfur Hexafluoride, Xing Wang, Shenyue Xu, Chuangang Ning, O. Al-Hagan, Pengfei Hu, Yongtao Zhao, Zhongfen Xu, Jingkang Deng, Enliang Wang, Xueguang Ren, Alexander Dorn, Don H. Madison

Physics Faculty Research & Creative Works

Electron momentum spectroscopy (EMS) results are presented for the sulfur hexafluoride (SF6) molecule using a high-resolution binary (e, 2e) spectrometer at incident energies (Ei) of 600, 1200, and 2400 eV plus the binding energy. The valence orbital momentum profiles were measured with a binding energy resolution of 0.68 eV and angular resolutions of Δθ = ±0.6⁰, ΔΦ = ±0.85⁰. Whereas the two higher incident energies are in the range where normally EMS measurements do not exhibit an impact-energy dependence, the current experimental data display a dynamic dependence on the impact energies. The measured momentum profiles are compared with predictions from …

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Many-Body Expansion Dynamics Of A Bose-Fermi Mixture Confined In An Optical Lattice, P. Siegl, Simeon I. Mistakidis, P. Schmelcher May 2018

Many-Body Expansion Dynamics Of A Bose-Fermi Mixture Confined In An Optical Lattice, P. Siegl, Simeon I. Mistakidis, P. Schmelcher

Physics Faculty Research & Creative Works

We Unravel The Correlated Nonequilibrium Dynamics Of A Mass Balanced Bose-Fermi Mixture In A One-Dimensional Optical Lattice Upon Quenching An Imposed Harmonic Trap From Strong To Weak Confinement. Regarding The System's Ground State, The Competition Between The Inter- And Intraspecies Interaction Strength Gives Rise To The Immiscible And Miscible Phases Characterized By Negligible And Complete Overlap Of The Constituting Atomic Clouds, Respectively. The Resulting Dynamical Response Depends Strongly On The Initial Phase And Consists Of An Expansion Of Each Cloud And An Interwell Tunneling Dynamics. For Varying Quench Amplitude And Referring To A Fixed Phase, A Multitude Of Response Regimes …

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Salt-Assisted Ultrasonic Disaggregation Of Nanodiamond, Vadym Mochalin, Kostiantyn Turcheniuk, Caleb Trecazzi May 2018

Salt-Assisted Ultrasonic Disaggregation Of Nanodiamond, Vadym Mochalin, Kostiantyn Turcheniuk, Caleb Trecazzi

Chemistry Faculty Research & Creative Works

Methods for disaggregating nanodiamond clusters, for example, by using ultrasound to break apart nanodiamond aggregates in a sodium chloride aqueous slurry. Compositions, such as aqueous nanodiamond dispersions and dry particulate compositions that may be produced using these methods.

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Coas: The Line Of 3d Demarcation, Daniel J. Campbell, Limin Wang, Chris Eckberg, Dave Graf, Halyna Hodovanets, Johnpierre Paglione May 2018

Coas: The Line Of 3d Demarcation, Daniel J. Campbell, Limin Wang, Chris Eckberg, Dave Graf, Halyna Hodovanets, Johnpierre Paglione

Physics Faculty Research & Creative Works

Transition metal-pnictide compounds have received attention for their tendency to combine magnetism and unconventional superconductivity. Binary CoAs lies on the border of paramagnetism and the more complex behavior seen in isostructural CrAs, MnP, FeAs, and FeP. Here we report the properties of CoAs single crystals grown with two distinct techniques along with density functional theory calculations of its electronic structure and magnetic ground state. While all indications are that CoAs is paramagnetic, both experiment and theory suggest proximity to a ferromagnetic instability. Quantum oscillations are seen in torque measurements up to 31.5 T and support the calculated paramagnetic Fermiology.

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The Future Possibility Of Consumer-Grade Quantum Computers, Peter Dolan May 2018

The Future Possibility Of Consumer-Grade Quantum Computers, Peter Dolan

Missouri S&T’s Peer to Peer

Quantum computers are rapidly evolving and are on the edge of becoming useful for the first time. The theoretical limit of computational speed for quantum computers would put even small-scale quantum computers well ahead of any classical computer. With more researchers attempting to build their own, it has become a race to see who can create the first truly useful quantum computer. Once such computers become both useful and prevalent, massive advancements in many fields of science can be achieved, leading to a scientific revolution. Advances in quantum computing lead some researchers and consumers to question whether the technology can …

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The Viability Of Quantum Computing, Brennan Michael King May 2018

The Viability Of Quantum Computing, Brennan Michael King

Missouri S&T’s Peer to Peer

Quantum computing is an upcoming computational technology that could be the key to advancing the field and ushering in a new era of innovation. In this paper examines the viability of quantum computing extensively using only highly credible peer-reviewed articles from the last few years. These peer-reviewed articles will provide relevant facts and data from prominent researchers in the field of computer engineering. A growing problem in the field of electronics and computers is the concept of Moore’s law. Moore’s law refers to the doubling of transistors every two years in integrated circuits. Recent research has suggested that electronics may …

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