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At least 775 records · Page 43

Methodology to predict annual yield losses and gains caused by solar module design and materials under field exposure

Solar cells and modules are usually optimized separately under standard test conditions (STC). However, the actual performance under field exposure depends on module design, installation and environmental conditions. This work therefore presents a methodology to predict the annual yield of crystalline silicon solar modules for varying module configurations and environments using a time step simulation approach. We define and quantify 12 effects that affect the annual module performance, starting with solar cells in air under STC to a complete module under realistic conditions. We consider the interaction of optical, thermal and electrical effects in the module and combine it with an angular, spectral and time resolved light source. The model enables understanding the impact of the module environment, such as regions with high wind speeds or high diffuse light, on the annual output of a particular module type. We validate our model with measured power and temperature data for crystalline silicon heterojunction solar cell modules and find an agreement of the annual yield within 0.7%. We quantify the annual gains and losses for this module and identify that major losses are caused by elevated operating temperatures (2.3%) and reflection losses at the front glass (2.6%). Critically, the coupling gains at the cell surface increase significantly by 1.5% when considering angular light irradiance compared to normal incidence. To conclude, we apply our Cell-to-Module-Yield method to a 72-cell mono-crystalline PERC module, where the main annual yield losses are caused by reflection at the front glass and ohmic losses in the connector ribbons.

14 SOLAR ENERGY↗

Trace explosives sampling for security applications (TESSA) study: Evaluation of procedures and methodology for contact sampling efficiency

We report the detection of trace amounts of explosive materials is critical to the security at mass transit centers (e.g., airports and railway stations). In a typical screening process, a trap is used to probe a surface of interest to collect and transfer particulate residue to a detector for analysis. The collection of residues from the surface being probed is widely viewed as the limiting step in this process. A multi-institutional study was performed to establish a methodology for the evaluation of sampling media collection efficiencies. Dry deposited residues of 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), C-4 (an RDX-based explosive), and pentaerythritol tetranitrate (PETN) were harvested from acrylonitrile butadiene styrene (ABS) plastic, ballistic nylon (NYL), and uncoated aluminum surfaces using muslin, Texwipe cotton, and stainless-steel mesh traps. Transfer and collection efficiencies of the sample media were calculated based on liquid chromatography-mass spectrometry analysis. Dry transfer efficiencies (DTE%) to all tested surfaces were greater than 75%, with transfer to ABS plastic being the lowest. Collection efficiency (CE%) varied significantly across the traps and the surfaces, yet some conclusions can be drawn; nylon had the lowest CE% for all cases (~10%), and the stainless steel mesh had the lowest CE% for the evaluated traps (~20%). Though the testing parameters have been standardized among the participants to establish a framework for an independent comparison of contact sampling media and surfaces, substantial variations in the DTE% and the CE% were observed, suggesting that other variables can affect contact sampling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A methodology for optimal MSW management, with an application in the waste transportation of Attica Region, Greece

Highlights: • A two-step (strategic and detailed optimal planning) methodology is used for solving complex MSW management problems. • A software package is outlined, which can be used for generating detailed optimal plans. • Sensitivity analysis compares alternative scenarios that address objections and/or wishes of local communities. • A case study shows the application of the above procedure in practice and demonstrates the results and benefits obtained. - Abstract: The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/or wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to: (a) serve 113 Municipalities and Communities that generate nearly 2 million t/y of comingled MSW with distinctly different waste collection patterns, (b) take into consideration several existing waste transfer stations (WTS) and optimize their use within the overall plan, (c) select the most appropriate sites among the potentially suitable (new and in use) ones, (d) generate the optimal profile of each WTS proposed, and (e) perform sensitivity analysis so as to define the impact of selected sets of constraints (limitations in the availability of sites and in the capacity of their installations) on the design and cost of the ensuing optimal waste transfer system. The results show that optimal planning offers significant economic savings to municipalities, while reducing at the same time the present levels of traffic, fuel consumptions and air emissions in the congested Athens basin.

42 ENGINEERING↗

Determining the biomass fraction of mixed waste fuels: A comparison of existing industry and {sup 14}C-based methodologies

Highlights: • Compares industry standard and {sup 14}C methods for determining bioenergy content of MSW. • Differences quantified through study at an operational energy from waste plant. • Manual sort and selective dissolution are unreliable measures of feedstock bioenergy. • {sup 14}C methods (esp. AMS) improve precision and reliability of bioenergy determination. • Implications for electricity generators and regulators for award of bio-incentives. - Abstract: {sup 14}C analysis of flue gas by accelerator mass spectrometry (AMS) and liquid scintillation counting (LSC) were used to determine the biomass fraction of mixed waste at an operational energy-from-waste (EfW) plant. Results were converted to bioenergy (% total) using mathematical algorithms and assessed against existing industry methodologies which involve manual sorting and selective dissolution (SD) of feedstock. Simultaneous determinations using flue gas showed excellent agreement: 44.8 ± 2.7% for AMS and 44.6 ± 12.3% for LSC. Comparable bioenergy results were obtained using a feedstock manual sort procedure (41.4%), whilst a procedure based on selective dissolution of representative waste material is reported as 75.5% (no errors quoted). {sup 14}C techniques present significant advantages in data acquisition, precision and reliability for both electricity generator and industry regulator.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimizing supercritical carbon dioxide in the inactivation of bacteria in clinical solid waste by using response surface methodology

Highlights: • Supercritical carbon dioxide sterilization of clinical solid waste. • Inactivation of bacteria in clinical solid waste using supercritical carbon dioxide. • Reduction of the hazardous exposure of clinical solid waste. • Optimization of the supercritical carbon dioxide experimental conditions. - Abstract: Clinical solid waste (CSW) poses a challenge to health care facilities because of the presence of pathogenic microorganisms, leading to concerns in the effective sterilization of the CSW for safe handling and elimination of infectious disease transmission. In the present study, supercritical carbon dioxide (SC-CO{sub 2}) was applied to inactivate gram-positive Staphylococcus aureus, Enterococcus faecalis, Bacillus subtilis, and gram-negative Escherichia coli in CSW. The effects of SC-CO{sub 2} sterilization parameters such as pressure, temperature, and time were investigated and optimized by response surface methodology (RSM). Results showed that the data were adequately fitted into the second-order polynomial model. The linear quadratic terms and interaction between pressure and temperature had significant effects on the inactivation of S. aureus, E. coli, E. faecalis, and B. subtilis in CSW. Optimum conditions for the complete inactivation of bacteria within the experimental range of the studied variables were 20 MPa, 60 °C, and 60 min. The SC-CO{sub 2}-treated bacterial cells, observed under a scanning electron microscope, showed morphological changes, including cell breakage and dislodged cell walls, which could have caused the inactivation. This espouses the inference that SC-CO{sub 2} exerts strong inactivating effects on the bacteria present in CSW, and has the potential to be used in CSW management for the safe handling and recycling-reuse of CSW materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Methodology for the development of empirical models relating 13C NMR spectral features to fuel properties

Effective formulation of new gasoline or diesel fuels for internal combustion engines would benefit from the development of reliable models for predicting key fuel properties based on a set of molecular descriptors obtained from a single measurement. This is particularly relevant in the case of renewable fuels, where the available fuel sample quantity may be limited. In this work, we present a statistically-based methodology for building empirical models to predict multiple properties from one-dimensional 13C nuclear magnetic resonance (NMR) spectra measured on around 200 microliters of a liquid fuel. NMR spectra contain information about the molecular composition of a sample and the carbon types and molecular substructures therein. Our approach uses this information to build sparse, interpretable models, where the predicted properties are linked to specific molecular features. The approach takes into consideration the constrained nature of the features making up the one-dimensional NMR spectrum, which, after standardization, represent a relative fuel composition. We point to the limitations in interpretability that arise when building this type of empirical predictive model and suggest how these limitations may be diminished. Among the many properties important for maximizing engine performance and minimizing emissions, we build models that predict derived cetane number and distillation temperatures as these are of particular interest because of their links to fuel economy, drivability, and engine-out emissions. Results suggest that the properties of interest may be impacted by only a few of the 27 13C NMR regions represented in the data, pointing to new directions for further testing in the development of improved fuels.

predictive models, biofuels., NMR Analysis↗

Optimization of the Electrochemical Extraction and Recovery of Metals from Electronic Waste Using Response Surface Methodology

The rapid growth of the electronic waste can be viewed both as an environmental threat and as an attractive source of minerals that can reduce the mining of natural resources, and stabilize the market of critical materials, such as rare earths. Here in this article surface response methodology was used to optimize a previously developed electrochemical recovery process for base metals from electronic waste using a mild oxidant (Fe 3+ ). Through this process an effective extraction of base metals can be achieved enriching the concentration of precious metals and significantly reducing environmental impacts and operational costs associated with the waste generation and chemical consumption. The optimization was performed using a bench-scale system specifically designed for this process. Operational parameters such as flow rate, applied current density and iron concentration were optimized to reduce the specific energy consumption of the electrochemical recovery process to 1.94 kWh per kg of metal recovered at a processing rate of 3.3 g of electronic waste per hour.

36 MATERIALS SCIENCE↗

Accurate Free Energies for Complex Condensed-Phase Reactions Using an Artificial Neural Network Corrected DFTB/MM Methodology

Semiempirical methods like density functional tight-binding (DFTB) allow extensive phase space sampling, making it possible to generate free energy surfaces of complex reactions in condensed-phase environments. Such a high efficiency often comes at the cost of reduced accuracy, which may be improved by developing a specific reaction parametrization (SRP) for the particular molecular system. Thiol–disulfide exchange is a nucleophilic substitution reaction that occurs in a large class of proteins. Its proper description requires a high-level ab initio method, while DFT-GAA and hybrid functionals were shown to be inadequate, and so is DFTB due to its DFT-GGA descent. We develop an SRP for thiol–disulfide exchange based on an artificial neural network (ANN) implementation in the DFTB+ software and compare its performance to that of a standard SRP approach applied to DFTB. Furthermore, as an application, we use both new DFTB-SRP as components of a QM/MM scheme to investigate thiol–disulfide exchange in two molecular complexes: a solvated model system and a blood protein. Demonstrating the strengths of the methodology, highly accurate free energy surfaces are generated at a low cost, as the augmentation of DFTB with an ANN only adds a small computational overhead.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Methodology for the Simulation of Molecular Motors at Different Scales

Millisecond-scale conformational transitions represent a seminal challenge for traditional molecular dynamics simulations, even with the help of high-end supercomputer architectures. Such events are particularly relevant to the study of molecular motors—proteins or abiological constructs that convert chemical energy into mechanical work. Here, we present a hybrid-simulation scheme combining an array of methods including elastic network models, transition path sampling, and advanced free-energy methods, possibly in conjunction with generalized-ensemble schemes to deliver a viable option for capturing the millisecond-scale motor steps of biological motors. The methodology is already implemented in large measure in popular molecular dynamics programs, and it can leverage the massively parallel capabilities of petascale computers. The applicability of the hybrid method is demonstrated with two examples, namely cyclodextrin-based motors and V-type ATPases.

Chemistry↗

XPS on Li-Battery-Related Compounds: Analysis of Inorganic SEI Phases and a Methodology for Charge Correction

Accurate identification of chemical phases associated with the electrode and solid-electrolyte interphase (SEI) is critical for understanding and controlling interfacial degradation mechanisms in lithium-containing battery systems. To study these critical battery materials and interfaces X-ray photoelectron spectroscopy (XPS) is a widely used technique that provides quantitative chemical insights. However, due to the fact that a majority of chemical phases relevant to battery interfaces are poor electronic conductors, phase identification that relies primarily on absolute XPS core-level binding-energies (BEs) can be problematic. Charging during XPS measurements leads to BE shifts that can be difficult to correct. These difficulties are often exacerbated by the coexistence of multiple Li-containing phases in the SEI with overlapping XPS core levels. To facilitate accurate phase identification of battery-relevant phases (and electronically insulating phases in general), we propose a straightforward approach for removing charging effects from XPS data sets. We apply this approach to XPS data sets acquired from six battery-relevant inorganic phases including lithium metal (Li0), lithium oxide (Li 2 O), lithium peroxide (Li 2 O 2 ), lithium hydroxide (LiOH), lithium carbonate (Li 2 CO 3 ), and lithium nitride (Li 3 N). Specifically, we demonstrate that BE separations between core levels present in a particular phase (e.g., BE separation between the O 1s and Li 1s core levels in Li 2 O) provide an additional constraint that can significantly improve reliability of phase identification. For phases like Li 2 O 2 and LiOH where the Li-to-O ratios and BE separations are nearly identical, X-ray excited valence-band spectra can provide additional clues that facilitate accurate phase identification. To accurately identity the phases in this study, we show that in situ growth of Li 2 O on Li 0 provides a means for determining absolute core-level positions, where all charging effects can be accurately removed. Finally, as an exemplary case we apply the charge-correction methodology to XPS data acquired from a symmetric cell based on a Li 2 S-P 2 S 5 solid electrolyte. This analysis demonstrates that accurately accounting for XPS BE shifts as a function of current-bias conditions can provide a direct probe of ionic conductivities associated with battery materials.

25 ENERGY STORAGE↗

Response Surface Methodology As a New Approach for Finding Optimal MALDI Matrix Spraying Parameters for Mass Spectrometry Imaging

Automated spraying devices have become ubiquitous in laboratories employing matrixassisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), in part because they permit control of a number of matrix application parameters that can easily be reproduced for intra- and interlaboratory studies. Determining the optimal parameters for MALDI matrix application, such as temperature, flow rate, spraying velocity, number of spraying cycles, and solvent composition for matrix application, is critical for obtaining high-quality MALDI-MSI data. However, there are no established approaches for optimizing these multiple parameters simultaneously. Instead optimization is performed iteratively (i.e., one parameter at a time), which is time consuming and can lead to overall non-optimal settings. In this report, we demonstrate the use a novel experimental design and the response surface methodology to optimize five parameters of MALDI matrix application using a robotic sprayer. Thirtytwo combinations of MALDI matrix spraying conditions were tested, which allowed us to elucidate relationships between each of the application parameters as determined by MALDI-MS (specifically, using a 15 Tesla Fourier transform ion cyclotron resonance mass spectrometer). As such, we were able to determine the optimal automated spraying parameters that minimized signal de-localization and enabled high MALDI sensitivity. We envision this optimization strategy can be utilized for other MALDI-MSI applications, tissue types, and matrix application approaches.

60 APPLIED LIFE SCIENCES↗

Developing Intensity-Duration-Frequency (IDF) Curves From Satellite-Based Precipitation: Methodology and Evaluation

Given the continuous advancement in the retrieval of precipitation from satellites, it is important to develop methods that incorporate satellite-based precipitation data sets in the design and planning of infrastructure. This is because in many regions around the world, in situ rainfall observations are sparse and have insufficient record length. A handful of studies examined the use of satellite-based precipitation to develop intensity-duration-frequency (IDF) curves; however, they have mostly focused on small spatial domains and relied on combining satellite-based with ground-based precipitation data sets. In this study, we explore this issue by providing a methodological framework with the potential to be applied in ungauged regions. This framework is based on accounting for the characteristics of satellite-based precipitation products, namely, adjustment of bias and transformation of areal to point rainfall. The latter method is based on previous studies on the reverse transformation (point to areal) commonly used to obtain catchment-scale IDF curves. The paper proceeds by applying this framework to develop IDF curves over the contiguous United States (CONUS); the data set used is Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR). IDFs are then evaluated against National Oceanic and Atmospheric Administration (NOAA) Atlas 14 to provide a quantitative estimate of their accuracy. Results of this work show that median errors are in the range of (17–22%), (6–12%), and (3–8%) for one-day, two-day and three-day IDFs, respectively, and return periods in the range (2–100) years. Furthermore, a considerable percentage of satellite-based IDFs lie within the confidence interval of NOAA Atlas 14.

54 ENVIRONMENTAL SCIENCES↗

Scalable and adaptable two-ligand co-solvent transfer methodology for gold bipyramids to organic solvents

Large and faceted nanoparticles, such as gold bipyramids, presently require synthesis using alkyl ammonium halide ligands in aqueous conditions to stabilize the structure, which impedes subsequent transfer and suspension of such nanoparticles in low polarity solvents despite success with few nanometer gold nanoparticles of shapes such as spheres. Phase transfer methodologies present a feasible avenue to maintain colloidal stability of suspensions and move high surface energy particles into organic solvent environments. Here, we present a method to yield stable suspensions of gold bipyramids in low-polarity solvents, including methanol, dimethylformamide, chloroform, and toluene, through the requisite combination of two capping agents and the presence of a co-solvent. By utilizing PEG-SH functionalization for stability, dodecanethiol (DDT) as the organic-soluble capping agent, and methanol to aid in the phase transfer, gold bipyramids with a wide-range of aspect ratios and sizes can be transferred between water and chloroform readily and maintain colloidal stability. Subsequent transfer to various organic and low-polarity solvents is then demonstrated for the first time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reduced dimension rovibrational variational calculations of the S{sub 1} state of C{sub 2}H{sub 2}. I. Methodology and implementation

The bending and torsional degrees of freedom in S{sub 1} acetylene, C{sub 2}H{sub 2}, are subject to strong vibrational resonances and rovibrational interactions, which create complex vibrational polyad structures even at low energy. As the internal energy approaches that of the barrier to cis-trans isomerization, these energy level patterns undergo further large-scale reorganization that cannot be satisfactorily treated by traditional models tied to local minima of the potential energy surface for nuclear motion. Experimental spectra in the region near the cis-trans transition state have revealed these complicated new patterns. In order to understand near-barrier spectroscopic observations and to predict the detailed effects of cis-trans isomerization on the rovibrational energy level structure, we have performed reduced dimension rovibrational variational calculations of the S{sub 1} state. In this paper, we present the methodological details, several of which require special care. Our calculation uses a high accuracy ab initio potential surface and a fully symmetrized extended complete nuclear permutation inversion group theoretical treatment of a multivalued internal coordinate system that is appropriate for large amplitude bending and torsional motions. We also discuss the details of the rovibrational basis functions and their symmetrization, as well as the use of a constrained reduced dimension rovibrational kinetic energy operator.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development and methodology of level 1 probability safety assessment at PUSPATI TRIGA Reactor

As a consequence of the accident at the Fukushima Dai-ichi Nuclear Power Plant in Japan, the safety aspects of the one and only research reactor (31 years old) in Malaysia need be reviewed. Based on this decision, Malaysian Nuclear Agency in collaboration with Atomic Energy Licensing Board and Universiti Kebangsaan Malaysia develop a Level-1 Probability Safety Assessment on this research reactor. This work is aimed to evaluate the potential risks of incidents in RTP and at the same time to identify internal and external hazard that may cause any extreme initiating events. This report documents the methodology in developing a Level 1 PSA performed for the RTP as a complementary approach to deterministic safety analysis both in neutronics and thermal hydraulics. This Level-1 PSA work has been performed according to the procedures suggested in relevant IAEA publications and at the same time numbers of procedures has been developed as part of an Integrated Management System programme implemented in Nuclear Malaysia.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A methodology to identify and quantify mobility-reducing defects in 4H-silicon carbide power metal-oxide-semiconductor field-effect transistors

In this paper, we present a methodology for the identification and quantification of defects responsible for low channel mobility in 4H-Silicon Carbide (SiC) power metal-oxide-semiconductor field-effect transistors (MOSFETs). To achieve this, we use an algorithm based on 2D-device simulations of a power MOSFET, density functional simulations, and measurement data. Using physical modeling of carrier mobility and interface traps, we reproduce the experimental I-V characteristics of a 4H-SiC doubly implanted MOSFET through drift-diffusion simulation. We extract the position of Fermi level and the occupied trap density as a function of applied bias and temperature. Using these inputs, our algorithm estimates the number of possible trap types, their energy levels, and concentrations at 4H-SiC/SiO{sub 2} interface. Subsequently, we use density functional theory (DFT)-based ab initio simulations to identify the atomic make-up of defects causing these trap levels. We study silicon vacancy and carbon di-interstitial defects in the SiC side of the interface. Our algorithm indicates that the D{sub it} spectrum near the conduction band edge (3.25 eV) is composed of three trap types located at 2.8–2.85 eV, 3.05 eV, and 3.1–3.2 eV, and also calculates their densities. Based on DFT simulations, this work attributes the trap levels very close to the conduction band edge to the C di-interstitial defect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Analysis of simulation methodology for calculation of the heat of transport for vacancy thermodiffusion

Computation of the heat of transport Q{sub a}{sup *} in monatomic crystalline solids is investigated using the methodology first developed by Gillan [J. Phys. C: Solid State Phys. 11, 4469 (1978)] and further developed by Grout and coworkers [Philos. Mag. Lett. 74, 217 (1996)], referred to as the Grout-Gillan method. In the case of pair potentials, the hopping of a vacancy results in a heat wave that persists for up to 10 ps, consistent with previous studies. This leads to generally positive values for Q{sub a}{sup *} which can be quite large and are strongly dependent on the specific details of the pair potential. By contrast, when the interactions are described using the embedded atom model, there is no evidence of a heat wave, and Q{sub a}{sup *} is found to be negative. This demonstrates that the dynamics of vacancy hopping depends strongly on the details of the empirical potential. However, the results obtained here are in strong disagreement with experiment. Arguments are presented which demonstrate that there is a fundamental error made in the Grout-Gillan method due to the fact that the ensemble of states only includes successful atom hops and hence does not represent an equilibrium ensemble. This places the interpretation of the quantity computed in the Grout-Gillan method as the heat of transport in doubt. It is demonstrated that trajectories which do not yield hopping events are nevertheless relevant to computation of the heat of transport Q{sub a}{sup *}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Influence of system size on the properties of a fluid adsorbed in a nanopore: Physical manifestations and methodological consequences

Hysteresis and discontinuities in the isotherms of a fluid adsorbed in a nanopore in general hamper the determination of equilibrium thermodynamic properties, even in computer simulations. A way around this has been to consider both a reservoir of small size and a pore of small extent in order to restrict the fluctuations of density and approach a classical van der Waals loop. We assess this suggestion by thoroughly studying through Monte Carlo simulations and density functional theory the influence of system size on the equilibrium configurations of the adsorbed fluid and on the resulting isotherms. We stress the importance of pore-symmetry-breaking states that even for modest pore sizes lead to discontinuous isotherms and we discuss the physical relevance of these states and the methodological consequences for computing thermodynamic quantities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗