Showing papers by "Clarkson University published in 2019"

Sodium Metal Anodes: Emerging Solutions to Dendrite Growth

Abstract: This comprehensive Review focuses on the key challenges and recent progress regarding sodium-metal anodes employed in sodium-metal batteries (SMBs) The metal anode is the essential component of emerging energy storage systems such as sodium sulfur and sodium selenium, which are discussed as example full-cell applications We begin with a description of the differences in the chemical and physical properties of Na metal versus the oft-studied Li metal, and a corresponding discussion regarding the number of ways in which Na does not follow Li-inherited paradigms in its electrochemical behavior We detail the major challenges for Na-metal systems that at this time limit the feasibility of SMBs The core Na anode problems are the following interrelated degradation mechanisms: An unstable solid electrolyte interphase with most organic electrolytes, "mossy" and "lath-like" metal dendrite growth for liquid systems, poor Coulombic efficiency, and gas evolution Even solid-state Na batteries are not immune, with metal dendrites being reported The solutions may be subdivided into the following interrelated taxonomy: Improved electrolytes and electrolyte additives tailored for Na-metal anodes, interfacial engineering between the metal and the liquid or solid electrolyte, electrode architectures that both reduce the current density during plating-stripping and serve as effective hosts that shield the Na metal from excessive reactions, and alloy design to tune the bulk properties of the metal per se For instance, stable plating-stripping of Na is extremely difficult with conventional carbonate solvents but has been reported with ethers and glymes Solid-state electrolytes (SSEs) such as beta-alumina solid electrolyte (BASE), sodium superionic conductor (NASICON), and sodium thiophosphate (75Na2S·25P2S5) present highly exciting opportunities for SMBs that avoid the dangers of flammable liquids Even SSEs are not immune to dendrites, however, which grow through the defects in the bulk pellet, but may be controlled through interfacial energy modification We conclude with a discussion of the key research areas that we feel are the most fruitful for further pursuit In our opinion, greatly improved understanding and control of the SEI structure is the key to cycling stability A holistic approach involving complementary post-mortem, in situ, and operando analyses to elucidate full battery cell level structure-performance relations is advocated

Inferring causation from time series in Earth system sciences

Abstract: The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted correlation techniques. Here, we give an overview of causal inference frameworks and identify promising generic application cases common in Earth system sciences and beyond. We discuss challenges and initiate the benchmark platform causeme.net to close the gap between method users and developers.

Panoptic Studio: A Massively Multiview System for Social Interaction Capture

Abstract: We present an approach to capture the 3D motion of a group of people engaged in a social interaction. The core challenges in capturing social interactions are: (1) occlusion is functional and frequent; (2) subtle motion needs to be measured over a space large enough to host a social group; (3) human appearance and configuration variation is immense; and (4) attaching markers to the body may prime the nature of interactions. The Panoptic Studio is a system organized around the thesis that social interactions should be measured through the integration of perceptual analyses over a large variety of view points. We present a modularized system designed around this principle, consisting of integrated structural, hardware, and software innovations. The system takes, as input, 480 synchronized video streams of multiple people engaged in social activities, and produces, as output, the labeled time-varying 3D structure of anatomical landmarks on individuals in the space. Our algorithm is designed to fuse the “weak” perceptual processes in the large number of views by progressively generating skeletal proposals from low-level appearance cues, and a framework for temporal refinement is also presented by associating body parts to reconstructed dense 3D trajectory stream. Our system and method are the first in reconstructing full body motion of more than five people engaged in social interactions without using markers. We also empirically demonstrate the impact of the number of views in achieving this goal.

Sulfur‐Grafted Hollow Carbon Spheres for Potassium‐Ion Battery Anodes

Abstract: Sulfur-rich carbons are minimally explored for potassium-ion batteries (KIBs). Here, a large amount of S (38 wt%) is chemically incorporated into a carbon host, creating sulfur-grafted hollow carbon spheres (SHCS) for KIB anodes. The SHCS architecture provides a combination of nanoscale (≈40 nm) diffusion distances and CS chemical bonding to minimize cycling capacity decay and Coulombic efficiency (CE) loss. The SHCS exhibit a reversible capacity of 581 mAh g-1 (at 0.025 A g-1 ), which is the highest reversible capacity reported for any carbon-based KIB anode. Electrochemical analysis of S-free carbon spheres baseline demonstrates that both the carbon matrix and the sulfur species are highly electrochemically active. SHCS also show excellent rate capability, achieving 202, 160, and 110 mAh g-1 at 1.5, 3, and 5 A g-1 , respectively. The electrode maintains 93% of the capacity from the 5th to 1000th cycle at 3 A g-1 , with steady-state CE being near 100%. Raman analysis indicates reversible breakage of CS and SS bonds upon potassiation to 0.01 V versus K/K+ . The galvanostatic intermittent titration technique (GITT) analysis provides voltage-dependent K+ diffusion coefficients that range from 10-10 to 10-12 cm2 s-1 upon potassiation and depotassiation, with approximately five times higher coefficient for the former.

Breakdown Products from Perfluorinated Alkyl Substances (PFAS) Degradation in a Plasma-Based Water Treatment Process.

Abstract: Byproducts produced when treating perfluorooctanoic acid (PFOA) and perfluorooctanesulfonate (PFOS) in water using a plasma treatment process intentionally operated to treat these compounds slowly to allow for byproduct accumulation were quantified. Several linear chain perfluoroalkyl carboxylic acids (PFCAs) (C4 to C7) were identified as byproducts of both PFOA and PFOS treatment. PFOA, perfluorohexanesulfonate (PFHxS), and perfluorobutanesulfonate (PFBS) were also found to be byproducts from PFOS degradation. Significant concentrations of fluoride ions, inorganic carbon, and smaller organic acids (trifluoroacetic acid, acetic acid, and formic acid) were also identified. In addition to PFCAs, PFHxS, and PFBS, trace amounts of 43 PFOA-related and 35 PFOS-related byproducts were also identified using a screening and search-based algorithm. Minor concentrations of gas-phase byproducts were also identified (<2.5% of the F originally associated with the parent molecules) some of which are reported for the first time in perfluoroalkyl substance degradation experiments including cyclic perfluoroalkanes (C4F8, C5F10, C6F12, C7F14, and C8F16). The short chain PFCAs detected suggest the occurrence of a stepwise reduction of the parent perfluoroalkyl substances (PFAS) molecule, followed by oxidation of intermediates, perfluoroalkyl radicals, and perfluoro alcohols/ketones. Using a fluorine mass balance, 77% of the fluorine associated with the parent PFOA and 58% of the fluorine associated with the parent PFOS were identified. The bulk of the remaining fluorine was determined to be sorbed to reactor walls and tubing using sorption experiments in which plasma was not generated.

Machine Learning at the Network Edge: A Survey

Abstract: Resource-constrained IoT devices, such as sensors and actuators, have become ubiquitous in recent years. This has led to the generation of large quantities of data in real-time, which is an appealing target for AI systems. However, deploying machine learning models on such end-devices is nearly impossible. A typical solution involves offloading data to external computing systems (such as cloud servers) for further processing but this worsens latency, leads to increased communication costs, and adds to privacy concerns. To address this issue, efforts have been made to place additional computing devices at the edge of the network, i.e close to the IoT devices where the data is generated. Deploying machine learning systems on such edge computing devices alleviates the above issues by allowing computations to be performed close to the data sources. This survey describes major research efforts where machine learning systems have been deployed at the edge of computer networks, focusing on the operational aspects including compression techniques, tools, frameworks, and hardware used in successful applications of intelligent edge systems.

Physico-Chemical Processes for the Treatment of Per- And Polyfluoroalkyl Substances (PFAS): A review

Abstract: The recalcitrant behavior of per- and polyfluoroalkyl substances (PFAS) to most traditional water treatment processes is driving the development of new or modified treatment approaches for ...

Coordinated Optimal Network Reconfiguration and Voltage Regulator/DER Control for Unbalanced Distribution Systems

Abstract: Network reconfiguration has long been used by distribution system operators to achieve certain operation objectives such as reducing system losses or regulating bus voltages. In emerging distribution systems with a proliferation of distributed energy resources (DERs), co-optimizing network topology and DERs’ dispatches could further enhance such operational benefits. This paper focuses on the optimal network reconfiguration problem of distribution systems via an unbalanced ac optimal power flow framework, which rigorously addresses operation characters of unbalanced network, DERs, and voltage regulators (VRs). Two VR models with continuous and discrete tap ratios are studied and compared. The proposed co-optimization problem is formulated as a mixed-integer chordal relaxation-based semidefinite programming model with binary variables indicating line-switching statuses and tap positions. Several acceleration strategies by studying the structure of distribution networks are explored for reducing the number of binary variables and enhancing the computational performance. Case studies on modified IEEE 34-bus and 392-bus systems illustrate the effectiveness of the proposed approach.

Direct Structure-Performance Comparison of All-Carbon Potassium and Sodium Ion Capacitors.

Abstract: A hybrid ion capacitor (HIC) based on potassium ions (K+) is a new high-power intermediate energy device that may occupy a unique position on the Ragone chart space. Here, a direct performance comparison of a potassium ion capacitor (KIC) versus the better-known sodium ion capacitor is provided. Tests are performed with an asymmetric architecture based on bulk ion insertion, partially ordered, dense carbon anode (hard carbon, HC) opposing N- and O-rich ion adsorption, high surface area, cathode (activated carbon, AC). A classical symmetric "supercapacitor-like" configuration AC-AC is analyzed in parallel. For asymmetric K-based HC-AC devices, there are significant high-rate limitations associated with ion insertion into the anode, making it much inferior to Na-based HC-AC devices. A much larger charge-discharge hysteresis (overpotential), more than an order of magnitude higher impedance R SEI, and much worse cyclability are observed. However, K-based AC-AC devices obtained on-par energy, power, and cyclability with their Na counterpart. Therefore, while KICs are extremely scientifically interesting, more work is needed to tailor the structure of "Na-inherited" dense carbon anodes and electrolytes for satisfactory K ion insertion. Conversely, it should be possible to utilize many existing high surface area adsorption carbons for fast rate K application.

Multi-Objective Optimal Dispatch of Microgrid Under Uncertainties via Interval Optimization

Abstract: This paper presents a model of multi-objective optimal dispatch of microgrid (MODMG) under uncertainties via the interval optimization (IO) approach. In this model, multiple objectives are optimized simultaneously to meet economics, power quality, and security requirements of microgrid (MG) operations. Moreover, in order to adequately consider uncertain power outputs of wind turbines and photovoltaic cells in an MG, they are presented as interval variables. In turn, the MODMG model under uncertainties is formulated as a multi-objective optimization problem via the IO approach, which is then solved by the optimization algorithm of chaotic group search optimizer with multiple producers (CGSOMP). Simulation studies based on a modified IEEE 112-bus MG verify the effectiveness of the proposed optimal dispatch model and the CGSOMP algorithm.

A high-performance ultraviolet solar-blind photodetector based on a β-Ga2O3 Schottky photodiode

Abstract: UV ray detection near the earth surface has become urgent due to the serious effects of UV rays on human health, the environment and the biological evolution; therefore, the development of energy-saving UV photodetectors with high responsivity, specific detectivity, and sensitivity is urgently desired. Herein, we fabricated a lateral β-Ga2O3 Schottky photodiode on a sapphire substrate via magnetron sputtering using Ti and Ni as ohmic and Schottky contacts, respectively. The photodiode shows rectifying behaviors in the dark and under 254/365 nm UV light illuminations. As a photodetector, it exhibits the high photo-to-dark current ratio of 2.83 × 105 owing to its low dark current (1.32 × 10−11 A) and strong UV absorbance. The responsivity at 250 nm could reach up to 144.46 A W−1 at 10 V. The external quantum efficiency of 64 711% and the ideal specific detectivity of 7.29 × 1014 cm Hz1/2 W−1 (Jones) were also achieved. The rejection ratio (R250 nm/R400 nm) was as high as 4.8 × 103, suggesting high wavelength selectivity. The responsivity of 2301.78 A W−1 at 180 V proves the ability of this photodetector to operate at high voltages. In addition, it can operate with the responsivity of 0.73 mA W−1 and the specific detectivity of 3.35 × 1010 cm Hz1/2 W−1 (Jones) at zero bias. Overall, the lateral Ti/β-Ga2O3/Ni structured Schottky photodiode was verified as an excellent candidate for UV solar-blind detection with high performance and low energy consumption.

Numerical evaluation of the hysteretic behavior of concentrically braced frames and buckling restrained brace frame systems

Abstract: This paper presents a numerical investigation of buckling restrained brace (BRB) frames (BRBF) and a comparison with concentrically braced frames (CBF). A simplified core-spring finite element model was used to model BRB elements. Four types of CBF (X, V, inverted V, and two-story X) and four types of BRBF (diagonal, V, inverted V, and two-story X) were modeled in ABAQUS. A static nonlinear pushover analysis considering two cyclic loading protocols showed that the buckling restraint allows the BRB elements to undergo significant plasticity without forming plastic hinges , thereby dissipating a proportionally larger amount of energy and delaying yielding in the frame elements. Results indicated dramatic improvements in energy dissipation and ductility in BRBF models as compared to equivalent CBF models. Seismic response modification factors for BRBF models also showed greater values over CBF models. Time-history analysis evaluated the performance of CBF and BRBF under historical earthquake loadings and supported the same conclusions. The best performance was observed for V, inverted V, and two-story X BRBF configurations; the diagonal BRBF configuration performed better than equivalent CBF models, but did not perform nearly as well as the other BRBF models.

Hear Me Write: Does CEO Narcissism Affect Disclosure?

Abstract: Through earnings announcements, conference calls, and other press releases, corporate executives have an opportunity to frame the narrative of financial disclosures Numerous studies have shown that textual tone significantly influences stock returns, suggesting that through word choice, upper management may impact market reaction In this study, we examine the influence of CEO personality traits on corporate disclosures by analyzing the tone of earnings announcements for a sample of Fortune 500 CEOs over nearly two decades Our hypotheses are twofold: (1) that qualitative disclosures in firms with narcissistic leaders will be biased upward and (2) the bias will moderate as CEOs becomes older Our empirical results support these hypotheses and suggest that more narcissistic CEOs tend to reinforce their grandiose self-image by issuing more positive earnings announcements but this desire wanes with CEO age We also find that the stock market response to the tone of the earnings announcement is less pronounced for more narcissistic CEOs, suggesting the market takes into account the bias in narcissistic CEO announcements

The distribution of fitness effects among synonymous mutations in a gene under directional selection.

Abstract: The fitness effects of synonymous mutations, nucleotide changes that do not alter the encoded amino acid, have often been assumed to be neutral, but a growing body of evidence suggests otherwise. We used site-directed mutagenesis coupled with direct measures of competitive fitness to estimate the distribution of fitness effects among synonymous mutations for a gene under directional selection and capable of adapting via synonymous nucleotide changes. Synonymous mutations had highly variable fitness effects, both deleterious and beneficial, resembling those of nonsynonymous mutations in the same gene. This variation in fitness was underlain by changes in transcription linked to the creation of internal promoter sites. A positive correlation between fitness and the presence of synonymous substitutions across a phylogeny of related Pseudomonads suggests these mutations may be common in nature. Taken together, our results provide the most compelling evidence to date that synonymous mutations with non-neutral fitness effects may in fact be commonplace.

An information-theoretic, all-scales approach to comparing networks

Abstract: As network research becomes more sophisticated, it is more common than ever for researchers to find themselves not studying a single network but needing to analyze sets of networks. An important task when working with sets of networks is network comparison, developing a similarity or distance measure between networks so that meaningful comparisons can be drawn. The best means to accomplish this task remains an open area of research. Here we introduce a new measure to compare networks, the Network Portrait Divergence, that is mathematically principled, incorporates the topological characteristics of networks at all structural scales, and is general-purpose and applicable to all types of networks. An important feature of our measure that enables many of its useful properties is that it is based on a graph invariant, the network portrait. We test our measure on both synthetic graphs and real world networks taken from protein interaction data, neuroscience, and computational social science applications. The Network Portrait Divergence reveals important characteristics of multilayer and temporal networks extracted from data.

Direct Imaging of Isolated Single-Molecule Magnets in Metal-Organic Frameworks

Abstract: Practical applications involving the magnetic bistability of single-molecule magnets (SMMs) for next-generation computer technologies require nanostructuring, organization, and protection of nanoscale materials in two- or three-dimensional networks, to enable read-and-write processes. Owing to their porous nature and structural long-range order, metal-organic frameworks (MOFs) have been proposed as hosts to facilitate these efforts. Although probing the channels of MOF composites using indirect methods is well established, the use of direct methods to elucidate fundamental structural information is still lacking. Herein we report the direct imaging of SMMs encapsulated in a mesoporous MOF matrix using high-resolution transmission electron microscopy. These images deliver, for the first time, direct and unambiguous evidence to support the adsorption of molecular guests within the porous host. Bulk magnetic measurements further support the successful nanostructuring of SMMs. The preparation of the first magnetic composite thin films of this kind furthers the development of molecular spintronics.

Managing Bias in AI

Abstract: Recent awareness of the impacts of bias in AI algorithms raises the risk for companies to deploy such algorithms, especially because the algorithms may not be explainable in the same way that non-AI algorithms are. Even with careful review of the algorithms and data sets, it may not be possible to delete all unwanted bias, particularly because AI systems learn from historical data, which encodes historical biases. In this paper, we propose a set of processes that companies can use to mitigate and manage three general classes of bias: those related to mapping the business intent into the AI implementation, those that arise due to the distribution of samples used for training, and those that are present in individual input samples. While there may be no simple or complete solution to this issue, best practices can be used to reduce the effects of bias on algorithmic outcomes.

Emission Factors Derived from 13 Euro 6b Light-Duty Vehicles Based on Laboratory and On-Road Measurements

Abstract: Tailpipe emissions of a pool of 13 Euro 6b light-duty vehicles (eight diesel and five gasoline-powered) were measured over an extensive experimental campaign that included laboratory (chassis dynamometer), and on-road tests (using a portable emissions measurement system). The New European Driving Cycle (NEDC) and the Worldwide harmonised Light-duty vehicles Test Cycle (WLTC) were driven in the laboratory following standard and extended testing procedures (such as low temperatures, use of auxiliaries, modified speed trace). On-road tests were conducted in real traffic conditions, within and outside the boundary conditions of the regulated European Real-Driving Emissions (RDE) test. Nitrogen oxides (NOX), particle number (PN), carbon monoxide (CO), total hydrocarbons (HC), and carbon dioxide (CO2) emission factors were developed considering the whole cycles, their sub-cycles, and the first 300 s of each test to assess the cold start effect. Despite complying with the NEDC type approval NOX limit, diesel vehicles emitted, on average, over the WLTC and the RDE 2.1 and 6.7 times more than the standard limit, respectively. Diesel vehicles equipped with only a Lean NOX trap (LNT) averaged six and two times more emissions over the WLTC and the RDE, respectively, than diesel vehicles equipped with a selective catalytic reduction (SCR) catalyst. Gasoline vehicles with direct injection (GDI) emitted eight times more NOX than those with port fuel injection (PFI) on RDE tests. Large NOX emissions on the urban section were also recorded for GDIs (122 mg/km). Diesel particle filters were mounted on all diesel vehicles, resulting in low particle number emission (~1010 #/km) over all testing conditions including low temperature and high dynamicity. GDIs (~1012 #/km) and PFIs (~1011 #/km) had PN emissions that were, on average, two and one order of magnitude higher than for diesel vehicles, respectively, with significant contribution from the cold start. PFIs yielded high CO emission factors under high load operation reaching on average 2.2 g/km and 3.8 g/km on WLTC extra-high and RDE motorway, respectively. The average on-road CO2 emissions were ~33% and 41% higher than the declared CO2 emissions at type-approval for diesel and gasoline vehicles, respectively. The use of auxiliaries (AC and lights on) over the NEDC led to an increase of ~20% of CO2 emissions for both diesel and gasoline vehicles. Results for NOX, CO and CO2 were used to derive average on-road emission factors that are in good agreement with the emission factors proposed by the EMEP/EEA guidebook.

Quantifying primary and secondary humic-like substances in urban aerosol based on emission source characterization and a source-oriented air quality model

Abstract: . Humic-like substances (HULIS) are a mixture of high-molecular-weight, water-soluble organic compounds that are widely distributed in atmospheric aerosol. Their sources are rarely studied quantitatively. Biomass burning is generally accepted as a major primary source of ambient humic-like substances (HULIS) with additional secondary material formed in the atmosphere. However, the present study provides direct evidence that residential coal burning is also a significant source of ambient HULIS, especially in the heating season in northern China based on source measurements, ambient sampling and analysis, and apportionment with source-oriented CMAQ modeling. Emission tests show that residential coal combustion produces 5 % to 24 % of the emitted organic carbon (OC) as HULIS carbon (HULISc). Estimation of primary emissions of HULIS in Beijing indicated that residential biofuel and coal burning contribute about 70 % and 25 % of annual primary HULIS, respectively. Vehicle exhaust, industry, and power plant contributions are negligible. The average concentration of ambient HULIS in PM 2.5 was 7.5 µ g m −3 in urban Beijing and HULIS exhibited obvious seasonal variations with the highest concentrations in winter. HULISc accounts for 7.2 % of PM 2.5 mass, 24.5 % of OC, and 59.5 % of water-soluble organic carbon. HULIS are found to correlate well with K+ , Cl− , sulfate, and secondary organic aerosol, suggesting its sources include biomass burning, coal combustion, and secondary aerosol formation. Source apportionment based on CMAQ modeling shows residential biofuel and coal burning and secondary formation are important sources of ambient HULIS, contributing 47.1 %, 15.1 %, and 38.9 %, respectively.

Inhibition of Perchlorate Formation during the Electrochemical Oxidation of Perfluoroalkyl Acid in Groundwater

Abstract: Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonate (PFOS) are groundwater contaminants of emerging concern due to their toxicity and persistence. Currently, there are limited destructive tr...