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At least 199 records · Page 11

Methanol tolerance of atomically dispersed single metal site catalysts: mechanistic understanding and high-performance direct methanol fuel cells

Proton-exchange membrane fuel cells (PEMFCs) and direct methanol fuel cells (DMFCs) are promising power sources from portable electronic devices to vehicles. The high-cost issue of these low-temperature fuel cells can be primarily addressed by using platinum-group metal (PGM)-free oxygen reduction reaction (ORR) catalysts, in particular atomically dispersed metal–nitrogen–carbon (M–N–C, M = Fe, Co, Mn). Furthermore, a significant advantage of M–N–C catalysts is their superior methanol tolerance over Pt, which can mitigate the methanol cross-over effect and offer great potential of using a higher concentration of methanol in DMFCs. In this work, we investigated the ORR catalytic properties of M–N–C catalysts in methanol-containing acidic electrolytes via experiments and density functional theory (DFT) calculations. FeN 4 sites demonstrated the highest methanol tolerance ability when compared to metal-free pyridinic N, CoN 4 , and MnN 4 active sites. The methanol adsorption on MN 4 sites is even strengthened when electrode potentials are applied during the ORR. The negative influence of methanol adsorption becomes significant for methanol concentrations higher than 2.0 M. However, the methanol adsorption does not affect the 4e - ORR pathway or chemically destroy the FeN 4 sites. The understanding of the methanol-induced ORR activity loss guides the design of promising M–N–C cathode catalyst in DMFCs. Accordingly, we developed a dual-metal site Fe/Co–N–C catalyst through a combined chemical-doping and adsorption strategy. Instead of generating a possible synergistic effect, the introduced Co atoms in the first doping step act as “scissors” for Zn removal in metal–organic frameworks (MOFs), which is crucial for modifying the porosity of the catalyst and providing more defects for stabilizing the active FeN 4 sites generated in the second adsorption step. The Fe/Co–N–C catalyst significantly improved the ORR catalytic activity and delivered remarkably enhanced peak power densities (i.e., 502 and 135 mW cm -2 ) under H 2 –air and methanol–air conditions, respectively, representing the best performance for both types of fuel cells. Notably, the fundamental understanding of methanol tolerance, along with the encouraging DMFC performance, will open an avenue for the potential application of atomically dispersed M–N–C catalysts in other direct alcohol or ammonia fuel cells.

25 ENERGY STORAGE↗

Colloidal quantum dot based infrared detectors: extending to the mid-infrared and moving from the lab to the field

Quantum dots (QDs) that absorb in the mid-wave infrared (MWIR) regime (3–5 μm) have recently generated significant interest as possible detector materials for MWIR cameras, with promises to reduce materials and device fabrication costs and potentially increase device operating temperatures. However, these materials have been primarily explored in single pixel devices – not multi-pixel cameras – and their current performance lags behind that of commercially available MWIR cameras based on single crystalline materials. To realize the potential of QD MWIR photodetectors with imaging capabilities, improvements are needed in the quality of the MWIR-absorbing QD materials, ligands dictating inter-QD charge transport, ordering of QD films, device architectures, and scalability of these methods to larger areas. With three families of QDs being researched – lead-, silver-, and mercury-based chalcogenides – as well as a multitude of possible capping ligands and film deposition techniques, the experimental phase space for MWIR QDs is vast. Here, we provide a roadmap, considering the pros and cons of various film deposition and ligand exchange techniques, as well as reintroduce lessons learned over years of research on QD film formation. We also extracted and created a database of reported quantum dot photodetectors’ performance and fabrication methods and have developed an interactive data visualization dashboard for this database, which provides researchers in the field a quick snapshot of the existing state of the art. Finally, we outline figures of merit and information that should be presented in papers moving forward which would help to clarify the reported results, as well as offer ideas for future steps. We provide a database visualization of the QD photodetector literature at https://public.tableau.com/app/profile/tom.nakotte/viz/IRQDphotodetectors_16384709473480/Dashboard1#1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Recent advances in biomass pretreatment using biphasic solvent systems

The complexity and recalcitrance of lignocellulosic biomass seriously hinder its subsequent conversion to liquid fuels. To achieve high-value utilization of lignocellulosic biomass, the physical–chemical barrier should be overcome through appropriate pretreatment techniques to improve the accessibility of cellulose for efficient enzymatic hydrolysis. With the rapid emergence of novel pretreatment solvents, biphasic solvent pretreatments represent a nascent and green pretreatment method that has shown outstanding advantages and broad application prospects in the biorefinery of lignocellulosic substrates due to its ability to provide economically viable biomass upgrading, the separation process for products in the solvent phase, and the reutilization of solvents. Herein, different types of biphasic solvents (e.g., 2-methyltetrahydrofuran, methyl isobutyl ketone, 1-butanol, phenoxyethanol, ionic liquids, and deep eutectic solvents) were reviewed systematically, including the fundamental designs of biphasic solvents for biomass pretreatment, their effect on the fractionation of individual biomass components (e.g., carbohydrate and lignin) and the enzymatic hydrolysis performance, and the coproduction of furan and hydroxymethylfurfural. Finally, the main pros and cons of these different biphasic solvent systems are summarized, and the future development direction is also proposed. Finally, this review can provide a reference for designing and selecting effective biphasic pretreatment methods for various types of lignocellulosic biomass.

09 BIOMASS FUELS↗

Mechanics of Dynamic and Deformable DNA Nanostructures

In DNA nanotechnology, DNA molecules are designed, engineered, and assembled into arbitrary-shaped architectures with predesigned functions. Static DNA assemblies often have delicate designs with structural rigidity to overcome thermal fluctuations. Dynamic structures reconfigure in response to external cues, which have been explored to create functional nanodevices for environmental sensing and other applications. However, the precise control of reconfiguration dynamics has been a challenge due partly to flexible single-stranded DNA connections between moving parts. Deformable structures are special dynamic constructs with deformation on double-stranded parts and single-stranded hinges during transformation. These structures often have better control in programmed deformation. However, related deformability and mechanics including transformation mechanisms are not well understood or documented. In this review, we summarize the development of dynamic and deformable DNA nanostructures from a mechanical perspective. We present deformation mechanisms such as single-stranded DNA hinges with lock-and-release pairs, jack edges, helicity modulation, and external loading. Theoretical and computational models are discussed for understanding their associated deformations and mechanics. We elucidate the pros and cons of each model and recommend design processes based on the models. The design guidelines should be useful for those who have limited knowledge in mechanics as well as expert DNA designers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating Connected and Automated Vehicles in Co-Simulation Environment of Traffic Microsimulation and Vehicle Dynamics

Connected and automated vehicles (CAVs) have the potential to improve many aspects of the current transportation systems such as safety, mobility, and energy efficiency. In order to evaluate the benefits and impacts of a CAV, the CAV control algorithm is typically implemented on vehicles simulated in a traffic microsimulation environment. However, traffic microsimulation usually lacks detailed vehicle and powertrain dynamics, making it challenging to fully understand how a CAV control algorithm will perform and respond on an actual vehicle. Whether the same benefits measured in the simulation will also be observed in real-world remains an open question. One potential approach to fill in this gap is to conduct a co-simulation of traffic microsimulation with detailed vehicle and powertrain dynamics models, often developed in MATLAB Simulink. However, current microsimulation tools such as VISSIM and SUMO do not have a ready-to-use interface for co-simulation with vehicle dynamics and Simulink. Also, even if such an interface exists, it will be tool-specific, making it challenging to shift from one tool to another or test CAV controls in different tools. There are needs for tool-agnostic co-simulation as different microsimulation tools have their pros and cons, and researchers often need to use different tools based on the purposes of the simulation, project needs, and applications. In this work, Flexible Interface for X-in-the-loop Simulation (FIXS) is developed that can support the co-simulation of microsimulation, CAV control algorithm, and vehicle dynamics model in Simulink. Enabled by the FIXS, the benefit and performance of a CAV control algorithm can be better understood with the consideration of vehicle responses and dynamics. The connection to VISSIM and SUMO is handled internally by the interface, and users can easily switch tools by changing a configuration file. The co-simulation capability is demonstrated for a VISSIM eco-approach and departure CAV scenario and a SUMO cooperative merging scenario for both a passenger CAV and a class 8 heavy-duty connected and automated trucks.

Shao, Yunli↗

Optimization of laser-target parameters for the production of stable lithium beam

A laser ion source coupled with a radio frequency quadrupole linac accelerator is being proposed as a suitable system for the production of a low energy, high-current stable lithium beam. In order to maximize the lithium yield, plasmas generated by laser ablation of different materials based on lithium (Li, LiOH, and LiNbO3) have been characterized by using a Faraday cup and an electrostatic ion analyzer in the time of flight configuration. A wide range of laser power density has been investigated (109–1012 W/cm2) using two Nd:YAG lasers operating at different wavelengths (1064 nm and 532 nm), pulse durations (6 ns and 17 ns), and maximum energies (1400 mJ and 210 mJ). This paper outlines the pros and cons of the investigated materials by studying how the ion energy, yields, and charge state distributions are modified when the laser power density is changed. Considerable attention has been paid to the higher charge states of oxygen, which may occur with the same mass-to-charge ratio of Li3+. The analysis has evidenced that LiNbO3 represents a valid target since it allows minimizing the O6+/7Li3+ ratio down to 2.5% by using a laser power density of 1.8 × 1010 W/cm2. For such a condition, a Li3+ current of 1.4 mA/cm2 has been measured.

Cannavò, A. (ORCID:0000000309759630)↗

Stimulated Raman scattering mechanisms and scaling behavior in planar direct-drive experiments at the National Ignition Facility

Stimulated Raman scattering (SRS) has been investigated comprehensively in planar-geometry experiments at the National Ignition Facility at conditions relevant to the corona of inertial con finement fusion (ICF) ignition-scale direct-drive targets. These experiments at measured electron temperatures of 4 to 5 keV, simulated density scale lengths Ln of 400 to 700 um, and laser intensities at the quarter-critical density of up to 1.5 x 10 15 W/cm 2 have determined SRS thresholds and the scaling behavior of SRS for various beam geometries. Several SRS mechanisms, including saturated absolute SRS near the quarter-critical density and additional SRS, including near-backscatter or sidescatter at lower densities, have been identi fied. Correlation of time-dependent SRS at densities ~0.15 to 0.21 of the critical density with hot-electron signatures, as well as the magnitudes of these signatures across different experiments, is observed. Additional modeling work is needed to de nitively identify the density region in which hot electrons are generated, and will guide SRS and hot-electron preheat mitigation strategies for direct-drive-ignition designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Inferring thermal ion temperature and residual kinetic energy from nuclear measurements in inertial confinement fusion implosions

In inertial con finement fusion implosion experiments, the presence of residual anisotropic fluid motion within the stagnating hot spot leads to signifi cant variations in ion-temperature measurements using neutron time- of-flight detectors along different lines of sight. The minimum ion-temperature measurement is typically used as representative of the thermal temperature. In the presence of isotropic flows, however, even the minimum DT neutron-inferred ion temperature can be well above the plasma thermal temperature. Using both DD and DT neutron-inferred ion-temperature measurements, we show that it is possible to determine the contribution of isotropic flows and infer the DT burn-averaged thermal ion temperature. The contribution of large isotropic flows on driving the ratio of DD to DT neutron-inferred ion temperatures well below unity and approaching the lower bound of 0.8 is demonstrated in multimode simulations. The minimum DD neutron- inferred ion temperature is determined from the velocity variance analysis, accounting for the presence of isotropic flows. Being close to the DT burn-averaged thermal ion temperature, the inferred DD minimum ion temperatures demonstrate a strong correlation with the experimental yields in the OMEGA implosion database. An analytical expression is also derived to explain the effect of mode ℓ = 1 ion-temperature measurement asymmetry on yield degradations caused by the anisotropic flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reconstructing 3D asymmetries in laser-direct-drive implosions on OMEGA

Three-dimensional reconstruction algorithms have been developed which determine the hot-spot velocity, hot-spot apparent ion temperature distribution, and fuel areal density distribution present in laser-direct-drive inertial con finement fusion implosions on the OMEGA laser. These reconstructions rely on multiple independent measurements of the neutron energy spectrum emitted from the fusing plasma. Measurements of the neutron energy spectrum on OMEGA are made using a suite of quasi-orthogonal neutron time-of-flight detectors and a magnetic recoil spectrometer. These spectrometers are positioned strategically around the OMEGA target chamber to provide unique 3-D measurements of the conditions of the fusing hot spot and compressed fuel near peak compression. Here, the uncertainties involved in these 3-D reconstructions are discussed and are used to identify a new nTOF diagnostic line of sight which when built will reduce the uncertainty in the hot-spot apparent ion temperature distribution from 0.7 to < 0.4 keV.

47 OTHER INSTRUMENTATION↗

Current polarity effects on laboratory plasma jets

Plasma jets produced by a pulsed power machine were investigated using Thomson scattering and other diagnostics in order to make detailed comparisons to simulations. These jets were produced from a 15 μm thick disc of Al foil on a 1.2 MA, 100 ns rise time, pulsed power machine. Experiments were performed with both a radially inward and a radially outward current ow in the Al foil to investigate the effects of voltage polarity in the experiments and determine how extended magnetohydrodynamic (XMHD) effects, such as the Hall effect, change the formation of the jet. We recorded Thomson scattering spectra with a low enough laser energy to not perturb the plasma, while providing a high enough signal to noise ratio to resolve the scattered features. This enabled the measurement of the electron temperature in the jet region of the plasma, 15.5±4 eV for both current polarities. Jets with a radially outward current ow were heated more from inverse bremsstrahlung when 10 J of laser energy was used, implying that these jets are denser than the ones with a radially inward current. This higher density was con rmed by interferometry measurements. Experimental results were compared with XMHD computer simulations, which predicted electron temperatures 1.5 to 3 σ above those measured, and significantly higher density than experiments in both polarities. In this paper, possible sources of this discrepancy are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An efficient random-sampling method for calculating double occupancy of Gutzwiller wave function in single-band 1D and 2D lattices

In this paper, we report a random sampling method for computing the expectation value of physical quantities based on the Gutzwiler variational wave function. As the first application, we calculated the double occupancy, which is a critical quantity for under- standing the correlation effects in many-body systems, for single-band 1D and 2D lattices. We demonstrated that the random sampling scheme is more efficient than an existing Metropolis Monte-Carlo algorithm. For the 1D Hubbard model with only nearest-neighbor hopping, our results are almost identical to the exact analytic solution. We have also studied systems to which analytic solutions are not available, including the 1D lattices with next-nearest-neighbor hopping and 2D lattices. In addition, constraints on real-space con gurations can be easily implemented in the current scheme to further improve the Gutzwiller wave function. As an example, we calculated the double occupancy for 1D Hubbard model by applying the constraint that all double-occupied sites are paired with an empty site. With enhanced correlation between double-occupied and empty sites, the constraint results in much improved ground-state energy for 1D Hubbard model with strong on-site repulsion.

74 ATOMIC AND MOLECULAR PHYSICS↗

Demonstrating Computational Equivalence Between Continuous and Discrete Adjoint Methods by Calculating Time-Dependent Adjoint Solutions with Neutron Diffusion Models

The continuous adjoint method and the discrete adjoint method are two alternative approaches used to calculate adjoint solutions for adjoint systems. The continuous adjoint method derives adjoint equations analytically from continuous forward equations and then solves the adjoint equations either analytically or numerically in a discretized form whereas the discrete adjoint method calculates the adjoint solutions directly from the discretized forward equations. With regard to the methodology development and calculation procedure, distinct differences are well recognized between the two methods. For certain reasons, both methods are exclusively preferred and commonly used by different computational communities, but limited studies clarify the connections between the two adjoint methods from either of the communities. Herein, this paper demonstrates the computational equivalence between the continuous and discrete adjoint methods by investigating time-dependent adjoint solutions to the two-group neutron diffusion model in nuclear reactor analysis problems using both methods. Adjoint solutions can be used to estimate system parameters for reactor safety analysis. Appropriate final state conditions for the adjoint systems are specified in both of the methods, and the conditions are clarified with proper physical explanations. With the help of an event-based case study on neutron diffusion models, the accuracy of the time-dependent adjoint fluxes obtained from both methods is verified, and the pros and cons of both adjoint methods are examined. More importantly, the computational equivalence of both methods is demonstrated when they are applied to multigroup neutron diffusion systems. The advantage of calculating time-dependent adjoint fluxes by directly solving time-dependent adjoint systems rather than taking steady-state approximations as in common practice is also demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

On-policy learning-based deep reinforcement learning assessment for building control efficiency and stability

Artificial intelligence technologies have emerged as a game changer not only in specific applications such as image recognition and machine translation but also in many scientific domains. In particular, as deep reinforcement learning (DRL) has shown great success in complex control problems, DRL-based control has been considered as a potential solution to efficiently control and manage building systems. However, broad assessment of DRL-based building control is still required to characterize their pros and cons in comparison with conventional building control methods (e.g., rule-based feedback controls). In this paper, we assessed DRL-based controls with on-policy learning-based algorithms and continuous control actions for cooling control of large office buildings in the summer season to minimize whole-building energy use and occupant discomfort. We compared DRL-based control methods with two baseline control methods: (1) a pre-determined schedule with supply temperature and static pressure setpoints, and (2) advanced reset method that adjusts setpoints based on heuristic rules, i.e., ASHRAE Guideline 36. We also tested the DRL algorithms to evaluate their performances in multiple climate locations. We found that DRL-based control methods outperformed the baseline control methods in terms of energy savings while maintaining a thermal comfort. DRL reduced energy use between ~4%–22% on average compared to the baseline methods, depending on climate location. We also evaluated DRL-based control in terms of control stability and showed that DRL-based methods should address the span of hardware lifetimes in practical operations.

control stability↗

El valor de los metadatos para las estaciones de recuperación de recursos del agua

Spanish: Los metadatos hacen referencia a información descriptiva (como ubicación del sensor, unidad de medida, rango de medida, fecha de calibración, fecha de limpieza, si ocurrió algún evento como episodio de lluvia/fallo operativo/vertido tóxico . . .) que es esencial para convertir los grandes volúmenes de datos que se recogen actualmente en las instalaciones de tratamiento de agua y que están sin procesar en información y recursos útiles. Con el avance de la digitalización en el sector del agua, es fundamental evitar los cementerios de datos y, por otro lado, utilizar los datos almacenados para resolver problemas actuales y futuros. Este artículo se centra en el papel crucial que tienen los metadatos para responder a desafíos futuros y posiblemente impredecibles. El objetivo de este documento es presentar el ‘reto de los metadatos’ y destacar la necesidad de tener en cuenta los metadatos cuando se recoge información como parte de las buenas prácticas de digitalización. English: Metadata refers to descriptive information (such as sensor location, measurement unit, measurement range, calibration date, cleaning date, if any event occurred such as rain event/operating failure/toxic spill, . . .) essential to convert large volumes of raw data that are currently collected at water treatment facilities into useful information and resources. With the advance of digitalization in the water sector, it is fundamental to avoid data graveyards and, on the other hand, using collected data to address current and future problems. This paper focuses on the crucial role that metadata has in responding to future and possibly unpredictable challenges. The aim of this document is to present the ‘metadata challenge’ and to highlight the need to consider metadata when collecting information as part of good digitalization practices.

54 ENVIRONMENTAL SCIENCES↗

Review of nonflow estimation methods and uncertainties in relativistic heavy-ion collisions

Abstract Collective anisotropic flow, where particles are correlated over the entire event, is a prominent phenomenon in relativistic heavy-ion collisions and is sensitive to the properties of the matter created in those collisions. It is often measured by two- and multi-particle correlations and is therefore contaminated by nonflow, those genuine few-body correlations unrelated to the global event-wise correlations. Many methods have been devised to estimate nonflow contamination with various degrees of successes and difficulties. Here, we review those methods pedagogically, discussing the pros and cons of each method, and give examples of ballpark estimate of nonflow contamination and associated uncertainties in relativistic heavy-ion collisions. We hope such a review of the various nonflow estimation methods in a single place would prove helpful to future researches.

Feng, Yicheng (ORCID:0000000169010870)↗

Characterizing the gene–environment interaction underlying natural morphological variation in Neurospora crassa conidiophores using high-throughput phenomics and transcriptomics

Abstract Neurospora crassa propagates through dissemination of conidia, which develop through specialized structures called conidiophores. Recent work has identified striking variation in conidiophore morphology, using a wild population collection from Louisiana, United States of America to classify 3 distinct phenotypes: Wild-Type, Wrap, and Bulky. Little is known about the impact of these phenotypes on sporulation or germination later in the N. crassa life cycle, or about the genetic variation that underlies them. In this study, we show that conidiophore morphology likely affects colonization capacity of wild N. crassa isolates through both sporulation distance and germination on different carbon sources. We generated and crossed homokaryotic strains belonging to each phenotypic group to more robustly fit a model for and estimate heritability of the complex trait, conidiophore architecture. Our fitted model suggests at least 3 genes and 2 epistatic interactions contribute to conidiophore phenotype, which has an estimated heritability of 0.47. To uncover genes contributing to these phenotypes, we performed RNA-sequencing on mycelia and conidiophores of strains representing each of the 3 phenotypes. Our results show that the Bulky strain had a distinct transcriptional profile from that of Wild-Type and Wrap, exhibiting differential expression patterns in clock-controlled genes (ccgs), the conidiation-specific gene con-6, and genes implicated in metabolism and communication. Combined, these results present novel ecological impacts of and differential gene expression underlying natural conidiophore morphological variation, a complex trait that has not yet been thoroughly explored.

59 BASIC BIOLOGICAL SCIENCES↗

Parameterizations of electron scattering form factors for elastic scattering and electroexcitation of nuclear states in 27 Al and 40 Ca

Here, we report on empirical parameterizations of longitudinal ($\mathscr{R}$ L ) and transverse ($\mathscr{R}$ T ) nuclear elec- tromagnetic form factors for elastic scattering and the excitations of nuclear states in 27 Al and 40 Ca. The parameterizations are needed for the calculations of radiative corrections in measurements of electron scattering cross sections on 27 Al and 40 Ca in the quasi-elastic, resonance and inelastic con- tinuum regions, provide the contribution of nuclear excitations in investigations of the Coulomb Sum Rule, and test theoretical model predictions for excitation of nuclear states in electron and neutrino interactions on nuclear targets at low energies.

elastic scattering reactions↗

Full versus quasiparticle self-consistency in vertex-corrected GW approaches

Here, using seven semiconductors/insulators with band gaps covering the range from 1 eV to 10 eV we systematically explore the performance of two different variants of self-consistency associated with famous Hedin's system of equations: the full self-consistency and the so called quasi-particle approximation to it. The pros and cons of these two variants of self-consistency are sufficiently well documented in literature for the simplest GW approximation to the Hedin's equations. Our study, therefore, aims primarily at the level of theory beyond GW approximation, i.e. at the level of theory which includes vertex corrections. Whereas quasi-particle self-consistency has certain advantages at GW level (well known fact), the situation becomes quite different when vertex corrections are included. In the variant with full self-consistency, vertex corrections (both for polarizability and for self energy) systematically reduce the calculated band gaps making them closer to the experimental values. In the variant with quasi-particle self-consistency, however, an inclusion of the same diagrams has considerably larger effect and calculated band gaps become severely underestimated. Different effect of vertex corrections in two variants of self-consistency can be related to the Z-factor cancellation which plays positive role in quasi-particle self-consistency at GW level of theory but appears to be destructive for the quasi-particle approximation when higher order diagrams are included. Second result of our study is that we were able to reproduce the results obtained with the Questaal code using our FlapwMBPT code when the same variant of self-consistency (quasi-particle) and the same level of vertex corrections (for polarizability only, static approximation for screened interaction, and Tamm-Dancoff approximation for the Bethe-Salpeter equation) are used.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗