University of Arkansas

About: University of Arkansas is a education organization based out in Fayetteville, Arkansas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 17225 authors who have published 33329 publications receiving 941102 citations. The organization is also known as: Arkansas & UA.

The role of the solid electrolyte interphase layer in preventing Li dendrite growth in solid-state batteries

Abstract: Lithium (Li) metal anodes have regained intensive interest in recent years due to the ever-increasing demand for next-generation high energy battery technologies. Li metal, unfortunately, suffers from poor cycling stability and low efficiency as well as from the formation of dangerous Li dendrites, raising safety concerns. Utilizing solid-state electrolytes (SSEs) to prevent Li dendrite growth provides a promising approach to tackle the challenge. However, recent studies indicate that Li dendrites easily form at high current densities, which calls for full investigation of the fundamental mechanisms of Li dendrite formation within SSEs. Herein, the origin and evolution of Li dendrite growth through SSEs have been studied and compared by using Li6.1Ga0.3La3Zr2O12 (LLZO) and NASICON-type Li2O–Al2O3–P2O5–TiO2–GeO2 (LATP) pellets as the separators. We discover that a solid electrolyte interphase (SEI)-like interfacial layer between Li and SSE plays a critical role in alleviating the growth of dendritic Li, providing new insights into the interface between SSE and Li metal to enable future all solid-state batteries.

Phosphorus Mitigation to Control River Eutrophication: Murky Waters, Inconvenient Truths, and “Postnormal” Science

Abstract: This commentary examines an "inconvenient truth" that phosphorus (P)-based nutrient mitigation, long regarded as the key tool in eutrophication management, in many cases has not yet yielded the desired reductions in water quality and nuisance algal growth in rivers and their associated downstream ecosystems. We examine why the water quality and aquatic ecology have not recovered, in some case after two decades or more of reduced P inputs, including (i) legacies of past land-use management, (ii) decoupling of algal growth responses to river P loading in eutrophically impaired rivers; and (iii) recovery trajectories, which may be nonlinear and characterized by thresholds and alternative stable states. It is possible that baselines have shifted and that some disturbed river environments may never return to predisturbance conditions or may require P reductions below those that originally triggered ecological degradation. We discuss the practical implications of setting P-based nutrient criteria to protect and improve river water quality and ecology, drawing on a case study from the Red River Basin in the United States. We conclude that the challenges facing nutrient management and eutrophication control bear the hallmarks of "postnormal" science, where uncertainties are large, management intervention is urgently required, and decision stakes are high. We argue a case for a more holistic approach to eutrophication management that includes more sophisticated regime-based nutrient criteria and considers other nutrient and pollutant controls and river restoration (e.g., physical habitat and functional food web interactions) to promote more resilient water quality and ecosystem functioning along the land-freshwater continuum.

Nonlinear refraction and absorption: mechanisms and magnitudes

Abstract: We provide an in-depth treatment of the various mechanisms by which an incident light beam can produce an intensity- or flux-dependent change in the refractive index and absorption coefficient of different materials. Whenever possible, the mechanisms are initially traced to single-atom and -molecule effects in order to provide physical understanding. Representative values are given for the various mechanisms. Nine different mechanisms are discussed, starting with the Kerr effect due to atoms and/or molecules with discrete states, including organic materials such as molecules and conjugated polymers. Simplified two and/or three-level models provide useful information, and these are summarized. The nonlinear optics of semiconductors is reviewed for both bulk and quantum-confined semiconductors, focusing on the most common types II–VI and III–V. Also discussed in some detail are the different nonlinear mechanisms that occur in liquid crystals and photorefractive media. Additional nonlinear material systems and mechanisms such as glasses, molecular reorientation of single molecules, the electrostrictive effect, the nuclear effect (vibrational contributions), cascading, and the ever-present thermal effects are quantified, and representative tables of values are given.

Sacramento river flow reconstructed to a.d. 869 from tree rings1

Abstract: A time series of annual flow of the Sacramento River, California, is reconstructed to A.D. 869 from tree rings for a long-term perspective on hydrologic drought. Reconstructions derived by principal components regression of flow on time-varying subsets of tree-ring chronologies account for 64 to 81 percent of the flow variance in the 1906 to 1977 calibration period. A Monte Carlo analysis of reconstructed n-year running means indicates that the gaged record contains examples of drought extremes for averaging periods of perhaps = 6 to 10 years, but not for longer and shorter averaging periods. For example, the estimated probability approaches 1.0 that the flow in A.D. 1580 was lower than the lowest single-year gaged flow. The tree-ring record also suggests that persistently high or low flows over 50-year periods characterize some parts of the long-term flow history. The results should contribute to sensible water resources planning for the Sacramento Basin and to the methodology of incorporating tree-ring data in the assessment of the probability of hydrologic drought.

Dynamic linear models

Abstract: In this chapter we discuss the basic notions about state space models and their use in time series analysis. The dynamic linear model is presented as a special case of a general state space model, being linear and Gaussian. For dynamic linear models, estimation and forecasting can be obtained recursively by the well-known Kalman filter.