Physical Sciences and Mathematics Commons^™

University Of Arkansas, Chemistry And Biochemistry Department Graduate Student Publications, 2018- November 2023. 39p., Jeremy Smith, Lutishoor Salisbury

University Libraries Faculty Publications and Presentations

This report provides a compilation of the research publications by the Chemistry and Biochemistry (CHBC) Graduate students for the period: 2018-November 2023. It includes publications by the CHBC graduates and those where a CHBC faculty was the main advisor. It includes a summary of the research. The listing is organized according to type of publications within specific years.

University Of Arkansas, Chemistry And Biochemistry Department Research Publications, 2014- November 2023. 107p., Jeremy Smith, Lutishoor Salisbury

University Libraries Faculty Publications and Presentations

This report provides a compilation of the research publications by the Chemistry and Biochemistry faculty for the period: 2014 - November 2023. The information was gathered from major databases in science and technology including Web of Science, SciFinder, Reaxys, PubMed, IEEE Explore and Engineering Index. At least one author in each of the publications has the CHBC department as its affiliation. It includes a table summarizing the research. The listing is organized according to type of publications within specific years.

Wayne E. Sabbe Arkansas Soil Fertility Studies 2022, Nathan A. Slaton, Mike Daniels

Arkansas Agricultural Experiment Station Research Series

Rapid technological changes in crop management and production require that the research efforts be presented in an expeditious manner. The contributions of soil fertility and fertilizers are major production factors in all Arkansas crops. The studies described within will allow producers to compare their practices with the university’s research efforts. Additionally, soil-test data and fertilizer sales are presented to allow comparisons among years, crops, and other areas within Arkansas.

Constituent Loads And Trends In The Upper Illinois River Watershed: A Nonpoint Source Management Program Priority Watershed, Erin M. Grantz, Brian E. Haggard

Technical Reports

The Arkansas Department of Agriculture - Natural Resources Division (ANRD) has identified the Upper Illinois River Watershed (UIRW; 11110103), a hydrologic unit code (HUC) 8 watershed, located in Northwest Arkansas for prioritization by the Nonpoint Source (NPS) Management Program. URIW encompasses the Illinois River from its headwaters to the state line with Oklahoma and has been the subject of interstate disputes over water quality for decades. Nonpoint source pollution concerns in UIRW are excess nutrients from agriculture and sediment from changes in land use/land cover (LULC).

Local, state, and national groups, including the NPS Source Management Program, have invested in …

Constituent Loads And Trends In The Upper White River Basin: A Nonpoint Source Management Program Priority Watersheds, Erin M. Grantz, Brian E. Haggard

Technical Reports

The Arkansas Department of Agriculture – Natural Resources Division (ANRD) has identified the Upper White River Basin (UWRB; HUC 11010001) a hydrologic unit code (HUC) 8 watersheds, located in Northwest Arkansas, for prioritization by the Nonpoint Source (NPS) Management Program. UWRB includes Beaver Lake in its borders, the drinking water source for 1 in 6 Arkansans. Nonpoint source pollution concerns in these watersheds are excess nutrients from agriculture and sediment from changes in land use/land cover (LULC).

Local, state, and national groups, including the NPS Source Management Program, have invested in education, best management practices, and streambank restoration in the …

Supercontinuum Light Generation Via Non-Linear Effects In Hollow-Core Fiber, Skyler Gulati

Physics Student Works

The field of non-linear optics has gained traction in the last couple decades due to the variable generation of wavelengths which are less deterministic than within traditional optics. Using non-linear mediums, including hollow-core fibers (HCF), generation of wavelengths spanning into the vacuum ultraviolet (VUV) wavelength range is possible. These short wavelengths can be utilized within electron spectroscopy-based methods of material science like angle-resolved photoemission spectroscopy (ARPES). This technique most often uses specific photoemission lines of atoms in discharge lamps, however, with the frequency dispersion capabilities of HCF, broad band creation can allow for variable wavelength selection through filtering specific wavelengths …

Watershed Prioritization To Reduce Nutrient Export: A Framework For The State Of Arkansas Based On Ambient Water Quality Monitoring Data, Erin Grantz, Brian E. Haggard

Technical Reports

The annual formation of the Northern Gulf of Mexico hypoxic zone is driven by nutrient loading from the Mississippi-Atchafalaya River Basin (MARB). Member States of The Mississippi River/Gulf of Mexico Hypoxia Task have developed statewide strategies to identify priorities and opportunities for nutrient export reduction in the MARB. In 2014, the State of Arkansas joined the Task Force and initiated an Arkansas Nutrient Reduction Strategy (ANRS), which currently prioritizes ten Hydrologic Unit Code 8 (HUC-8) watersheds (ANRD, 2014). These priority watersheds were not selected based on measured in-stream nutrient concentrations or trends, which impedes quantitative assessment, goal setting, and linking …

Defining Critical Or Hydrologic Conditions As Sampled During The Joint Study, Brian E. Haggard, Erin Grantz, J. T. Scott

Technical Reports

The “Joint Study” was conducted to fulfill the obligations of the second “Statement of Joint Principles and Actions” agreed to by the states of Arkansas and Oklahoma. The “Joint Study” affirmed the magnitude of Oklahoma’s Scenic River total phosphorus (TP) criteria (i.e., 0.037 mg/L), but it added the new caveat of applying the criteria to “critical conditions.” The primary purpose of this paper was to define “critical conditions” based on the range in base flow proportions (BFP) of total streamflow on days that were sampled in the “Joint Study,” where BFP is base flow discharge divided by total stream flow …

Arkansas Corn And Grain Sorghum Research Studies 2021, Victor Ford, Jason Kelley, Nathan Mckinney Ii

Arkansas Agricultural Experiment Station Research Series

The 2021 edition of the Arkansas Corn and Grain Sorghum Research Studies Series includes research results on topics pertaining to corn and grain sorghum production, including weed, disease, and insect management; economics; sustainability; irrigation; post-harvest drying; soil fertility; mycotoxins; cover crop management; and research verification program results. Our objective is to capture and broadly distribute the results of research projects funded by the Arkansas Corn and Grain Sorghum Board. The intended audience includes producers and their advisors, current investigators, and future researchers. The Series serves as a citable archive of research results.

Active Learning With Cybersecurity, Carole Shook

TFSC Publications and Presentations

A global campus grant was obtained in Spring 2020 to develop modules for Cybersecurity. This presentation encompasses the use of Cyberciege and case studies that require active learning of students.

Wayne E. Sabbe Arkansas Soil Fertility Studies 2021, Nathan A. Slaton

Arkansas Agricultural Experiment Station Research Series

Rapid technological changes in crop management and production require that the research efforts be presented in an expeditious manner. The contributions of soil fertility and fertilizers are major production factors in all Arkansas crops. The studies described within will allow producers to compare their practices with the university’s research efforts. Additionally, soil-test data and fertilizer sales are presented to allow comparisons among years, crops, and other areas within Arkansas.

Arkansas Bulletin Of Water Research - Issue 2021-2022, Erin Grantz, Lillie Haddock, Brian E. Haggard

Arkansas Bulletin of Water Research

The Arkansas Bulletin of Water Research (Bulletin) is a publication of the Arkansas Water Resources Center (AWRC). We publish the Bulletin to communicate the major findings of research funded by the Water Resources Research Act Section 104(b) in Arkansas. This research is relevant to Arkansas water stakeholders, and the Bulletin provides an easily searchable and aesthetically engaging access option.

This is the fourth publication of the Bulletin. This issue contains final reports from research projects that were funded by the 104(b) program in fiscal years 2019 and 2020. The articles in this issue can be cited as an AWRC publication. …

Sediment Phosphorus Release At Lake Fayetteville, Summer 2020, Brian E. Haggard, Abbie L. Lasater, Morgan B. Dulin, Bradley J. Austin

Technical Reports

The purpose of this project was to evaluate the release of dissolved phosphorus (P) from bottom sediment at Lake Fayetteville, and the potential use of aluminum sulfate (Al2(SO4)3) to remediate the P stored and released by bottom sediments. Intact sediment cores (n=18) were taken at three locations, named inlet, mid and dam sites at Lake Fayetteville. The cores were incubated with 1 L of overlying water with light excluded and bubbled with air (half, aerobic treatment) and N2 (other half, anaerobic). Water samples were pulled and analyzed for soluble reactive P (SRP), and that water was replaced with filtered lake …

Lecture 05: The Convergence Of Big Data And Extreme Computing, David Keyes

Mathematical Sciences Spring Lecture Series

As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solvers that couple vast numbers of degrees of freedom, must span a widening gap between ambitious applications and austere architectures to support them. We present fifteen universals for researchers in scalable solvers: imperatives from computer architecture that scalable solvers must respect, strategies towards achieving them that are currently well established, and additional strategies currently being developed for an effective and efficient exascale software ecosystem. We consider recent generalizations of what it means to “solve” a computational problem, which suggest that we have often been “oversolving” them at the …

Lecture 09: Hierarchically Low Rank And Kronecker Methods, Rio Yokota

Mathematical Sciences Spring Lecture Series

Exploiting structures of matrices goes beyond identifying their non-zero patterns. In many cases, dense full-rank matrices have low-rank submatrices that can be exploited to construct fast approximate algorithms. In other cases, dense matrices can be decomposed into Kronecker factors that are much smaller than the original matrix. Sparsity is a consequence of the connectivity of the underlying geometry (mesh, graph, interaction list, etc.), whereas the rank-deficiency of submatrices is closely related to the distance within this underlying geometry. For high dimensional geometry encountered in data science applications, the curse of dimensionality poses a challenge for rank-structured approaches. On the other …

Lecture 08: Partial Eigen Decomposition Of Large Symmetric Matrices Via Thick-Restart Lanczos With Explicit External Deflation And Its Communication-Avoiding Variant, Zhaojun Bai

Mathematical Sciences Spring Lecture Series

There are continual and compelling needs for computing many eigenpairs of very large Hermitian matrix in physical simulations and data analysis. Though the Lanczos method is effective for computing a few eigenvalues, it can be expensive for computing a large number of eigenvalues. To improve the performance of the Lanczos method, in this talk, we will present a combination of explicit external deflation (EED) with an s-step variant of thick-restart Lanczos (s-step TRLan). The s-step Lanczos method can achieve an order of s reduction in data movement while the EED enables to compute eigenpairs in batches along with a number …

Lecture 04: Spatial Statistics Applications Of Hrl, Trl, And Mixed Precision, David Keyes

Mathematical Sciences Spring Lecture Series

As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solvers that couple vast numbers of degrees of freedom, must span a widening gap between ambitious applications and austere architectures to support them. We present fifteen universals for researchers in scalable solvers: imperatives from computer architecture that scalable solvers must respect, strategies towards achieving them that are currently well established, and additional strategies currently being developed for an effective and efficient exascale software ecosystem. We consider recent generalizations of what it means to “solve” a computational problem, which suggest that we have often been “oversolving” them at the …

Lecture 14: Randomized Algorithms For Least Squares Problems, Ilse C.F. Ipsen

Mathematical Sciences Spring Lecture Series

The emergence of massive data sets, over the past twenty or so years, has lead to the development of Randomized Numerical Linear Algebra. Randomized matrix algorithms perform random sketching and sampling of rows or columns, in order to reduce the problem dimension or compute low-rank approximations. We review randomized algorithms for the solution of least squares/regression problems, based on row sketching from the left, or column sketching from the right. These algorithms tend to be efficient and accurate on matrices that have many more rows than columns. We present probabilistic bounds for the amount of sampling required to achieve a …

Lecture 13: A Low-Rank Factorization Framework For Building Scalable Algebraic Solvers And Preconditioners, X. Sherry Li

Mathematical Sciences Spring Lecture Series

Factorization based preconditioning algorithms, most notably incomplete LU (ILU) factorization, have been shown to be robust and applicable to wide ranges of problems. However, traditional ILU algorithms are not amenable to scalable implementation. In recent years, we have seen a lot of investigations using low-rank compression techniques to build approximate factorizations.
A key to achieving lower complexity is the use of hierarchical matrix algebra, stemming from the H-matrix research. In addition, the multilevel algorithm paradigm provides a good vehicle for a scalable implementation. The goal of this lecture is to give an overview of the various hierarchical matrix formats, such …

Lecture 07: Nonlinear Preconditioning Methods And Applications, Xiao-Chuan Cai

Mathematical Sciences Spring Lecture Series

We consider solving system of nonlinear algebraic equations arising from the discretization of partial differential equations. Inexact Newton is a popular technique for such problems. When the nonlinearities in the system are well-balanced, Newton's method works well, but when a small number of nonlinear functions in the system are much more nonlinear than the others, Newton may converge slowly or even stagnate. In such a situation, we introduce some nonlinear preconditioners to balance the nonlinearities in the system. The preconditioners are often constructed using a combination of some domain decomposition methods and nonlinear elimination methods. For the nonlinearly preconditioned problem, …

Lecture 03: Hierarchically Low Rank Methods And Applications, David Keyes

Mathematical Sciences Spring Lecture Series

As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solvers that couple vast numbers of degrees of freedom, must span a widening gap between ambitious applications and austere architectures to support them. We present fifteen universals for researchers in scalable solvers: imperatives from computer architecture that scalable solvers must respect, strategies towards achieving them that are currently well established, and additional strategies currently being developed for an effective and efficient exascale software ecosystem. We consider recent generalizations of what it means to “solve” a computational problem, which suggest that we have often been “oversolving” them at the …

Lecture 12: Recent Advances In Time Integration Methods And How They Can Enable Exascale Simulations, Carol S. Woodward

Mathematical Sciences Spring Lecture Series

To prepare for exascale systems, scientific simulations are growing in physical realism and thus complexity. This increase often results in additional and changing time scales. Time integration methods are critical to efficient solution of these multiphysics systems. Yet, many large-scale applications have not fully embraced modern time integration methods nor efficient software implementations. Hence, achieving temporal accuracy with new and complex simulations has proved challenging. We will overview recent advances in time integration methods, including additive IMEX methods, multirate methods, and parallel-in-time approaches, expected to help realize the potential of exascale systems on multiphysics simulations. Efficient execution of these methods …

Lecture 02: Tile Low-Rank Methods And Applications (W/Review), David Keyes

Mathematical Sciences Spring Lecture Series

As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solvers that couple vast numbers of degrees of freedom, must span a widening gap between ambitious applications and austere architectures to support them. We present fifteen universals for researchers in scalable solvers: imperatives from computer architecture that scalable solvers must respect, strategies towards achieving them that are currently well established, and additional strategies currently being developed for an effective and efficient exascale software ecosystem. We consider recent generalizations of what it means to “solve” a computational problem, which suggest that we have often been “oversolving” them at the …

Lecture 11: The Road To Exascale And Legacy Software For Dense Linear Algebra, Jack Dongarra

Mathematical Sciences Spring Lecture Series

In this talk, we will look at the current state of high performance computing and look at the next stage of extreme computing. With extreme computing, there will be fundamental changes in the character of floating point arithmetic and data movement. In this talk, we will look at how extreme-scale computing has caused algorithm and software developers to change their way of thinking on implementing and program-specific applications.

Lecture 00: Opening Remarks: 46th Spring Lecture Series, Tulin Kaman

Mathematical Sciences Spring Lecture Series

Opening remarks for the 46th Annual Mathematical Sciences Spring Lecture Series at the University of Arkansas, Fayetteville.

Lecture 06: The Impact Of Computer Architectures On The Design Of Algebraic Multigrid Methods, Ulrike Yang

Mathematical Sciences Spring Lecture Series

Algebraic multigrid (AMG) is a popular iterative solver and preconditioner for large sparse linear systems. When designed well, it is algorithmically scalable, enabling it to solve increasingly larger systems efficiently. While it consists of various highly parallel building blocks, the original method also consisted of various highly sequential components. A large amount of research has been performed over several decades to design new components that perform well on high performance computers. As a matter of fact, AMG has shown to scale well to more than a million processes. However, with single-core speeds plateauing, future increases in computing performance need to …

Lecture 01: Scalable Solvers: Universals And Innovations, David Keyes

Mathematical Sciences Spring Lecture Series

As simulation and analytics enter the exascale era, numerical algorithms, particularly implicit solvers that couple vast numbers of degrees of freedom, must span a widening gap between ambitious applications and austere architectures to support them. We present fifteen universals for researchers in scalable solvers: imperatives from computer architecture that scalable solvers must respect, strategies towards achieving them that are currently well established, and additional strategies currently being developed for an effective and efficient exascale software ecosystem. We consider recent generalizations of what it means to “solve” a computational problem, which suggest that we have often been “oversolving” them at the …

Lecture 10: Preconditioned Iterative Methods For Linear Systems, Edmond Chow

Mathematical Sciences Spring Lecture Series

Iterative methods for the solution of linear systems of equations – such as stationary, semi-iterative, and Krylov subspace methods – are classical methods taught in numerical analysis courses, but adapting these methods to run efficiently at large-scale on high-performance computers is challenging and a constantly evolving topic. Preconditioners – necessary to aid the convergence of iterative methods – come in many forms, from algebraic to physics-based, are regularly being developed for linear systems from different classes of problems, and similarly are evolving with high-performance computers. This lecture will cover the background and some recent developments on iterative methods and preconditioning …

Water Quality Monitoring In The Upper Poteau River Watershed, Abbie Lasater, Brian E. Haggard

Technical Reports

The Upper Poteau River Watershed (UPRW) has been listed as a priority watershed in Arkansas since 1998 due to nutrient and sediment enrichment from point and nonpoint sources (NPS). According to the Arkansas NPS pollution management plan, the goals for the UPRW are to reduce pollutant levels that will restore all designates uses and target subwatersheds where implementation of management practices can have the greatest impact. Over the last several years, many 319(h) projects have been implemented and point sources have been reduced in order to improve water quality in the UPRW. The purpose of this study was to monitor …

Perceiving Mathematics And Art, Edmund Harriss

Mic Lectures

Mathematics and art provide powerful lenses to perceive and understand the world, part of an ancient tradition whether it starts in the South Pacific with tapa cloth and wave maps for navigation or in Iceland with knitting patterns and sunstones. Edmund Harriss, an artist and assistant clinical professor of mathematics in the Fulbright College of Arts and Sciences, explores these connections in his Honors College Mic lecture.