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At least 163 records · Page 9

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

We present a benchmarking study of active learning (AL) schemes for designing planar multilayer nanophotonic metamaterials, where the design tasks are formulated as binary optimization problems. Different surrogate models, including factorization machine (FM), Gaussian process regression (GPR), and convolutional neural network (CNN), combined with different optimization methods, including exhaustive enumeration, discrete particle swarm optimization (DPSO), quantum annealing (QA), hybrid QA, and simulated annealing are studied. The benchmark cases investigated range from small problems with short binary lengths (N = 25) to large problems with N up to 100, focusing on the design of two classes of photonic structures, including antireflective coatings for the long-wavelength infrared region and transparent radiative coolers. For small problems, CNN coupled with DPSO in AL achieves the best performance. As N increases, FM with QA outperforms GPR and CNN. For FM-based AL, hybrid QA yields the best optimization results, particularly in high-dimensional cases (N = 100). These results demonstrate that the optimization method can significantly affect in AL performance as N increases, and that QA-based optimization can provide practical routes for mitigating the optimization bottleneck in high-dimensional problems.

Jung, Serang [Kyung Hee University, Korea]↗

Scope and Limitations of Fmoc Chemistry SPPS-Based Approaches to the Total Synthesis of Insulin Lispro via Ester Insulin

We have systematically explored three approaches based on 9-fluorenylmethoxycarbonyl (Fmoc) chemistry solid phase peptide synthesis (SPPS) for the total chemical synthesis of the key depsipeptide intermediate for the efficient total chemical synthesis of insulin. The approaches used were: stepwise Fmoc chemistry SPPS; the “hybrid method”, in which maximally protected peptide segments made by Fmoc chemistry SPPS are condensed in solution; and, native chemical ligation using peptide-thioester segments generated by Fmoc chemistry SPPS. A key building block in all three approaches was a Glu[O-β-(Thr)] ester-linked dipeptide equipped with a set of orthogonal protecting groups compatible with Fmoc chemistry SPPS. We report the most effective method for the preparation of the 51 residue ester-linked polypeptide chain of ester insulin was the use of unprotected peptide-thioester segments, prepared from peptide-hydrazides synthesized by Fmoc chemistry SPPS, and condensed by native chemical ligation. High-resolution X-ray crystallography confirmed the disulfide pairings and three-dimensional structure of synthetic insulin lispro prepared from ester insulin lispro by this route. Further optimization of these pilot studies could yield an efficient total chemical synthesis of insulin lispro (Humalog) based on peptide synthesis by Fmoc chemistry SPPS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards developing multiscale-multiphysics models and their surrogates for digital twins of metal additive manufacturing

Artificial intelligence (AI) embedded within digital models of manufacturing processes can be used to improve process productivity and product quality significantly. The application of such advanced capabilities particularly to highly digitalized processes such as metal additive manufacturing (AM) is likely to make those processes commercially more attractive. AI capabilities will reside within Digital Twins (DTs) which are living virtual replicas of the physical processes. DTs will be empowered to operate autonomously in a diagnostic control capacity to supervise processes and can be interrogated by the practitioner to inform the optimal processing route for any given product. The utility of the information gained from the DTs would depend on the quality of the digital models and, more importantly, their faster-solving surrogates which dwell within DTs for consultation during rapid decision-making. In this article, we point out the exceptional value of DTs in AM and focus on the need to create high-fidelity multiscale-multiphysics models for AM processes to feed the AI capabilities. We identify technical hurdles for their development, including those arising from the multiscale and multiphysics characteristics of the models, the difficulties in linking models of the subprocesses across scales and physics, and the scarcity of experimental data. We discuss the need for creating surrogate models using machine learning approaches for real-time problem-solving. We further identify non-technical barriers, such as the need for standardization and difficulties in collaborating across different types of institutions. We offer potential solutions for all these challenges, after reflecting on and researching discussions held at an international symposium on the subject in 2019. Here, we argue that a collaborative approach can not only help accelerate their development compared with disparate efforts, but also enhance the quality of the models by allowing modular development and linkages that account for interactions between the various sub-processes in AM. A high-level roadmap is suggested for starting such a collaboration.

36 MATERIALS SCIENCE↗

Emerging platforms for co-utilization of one-carbon substrates by photosynthetic organisms

One-carbon substrates have generated increasing attention as long-term sustainable feedstocks for biobased production of fuels and chemicals. However, their physicochemical properties present significant biological and operational challenges for commercial bioprocesses including kinetically slower substrate activation, high energetic cost of assimilation, low mass transfer, substrate toxicity, and low productivity titers. Several different routes including optimization of native pathways, synthetic pathways, and hybrid methods are being explored to overcome these challenges. Integration of emerging biological solutions with process improvements is enabling faster bioprocess development for cost-effective conversion of one-carbon substrates into fuels and chemicals.

59 BASIC BIOLOGICAL SCIENCES↗

Analysis and prediction of reaction kinetics using the degree of rate control

“Degree of rate control” (DRC) analysis provides a quantitative approach for analysing the kinetics of multi-step reaction mechanisms that has been widely applied to both heterogeneous and homogeneous catalysis research, as well as electrocatalysis. The DRC of any given transition state or intermediate is defined as a partial derivative such that it approximately equals the fractional increase in net rate to the product of interest per differential decrease in its standard-state free energy for that species (÷RT), holding constant the standard-state free energies of all other transition states and intermediates. Even very complex mechanisms usually have only a few species with non-zero DRCs and are thus the species whose interactions with the catalyst most strongly affect the net rate. These key DRC values thus offer a simple and intuitive route to optimize catalyst materials, especially with the assistance of computational methods like density functional theory (DFT). These high-DRC species are also the species whose energetics must be most accurately measured or calculated to achieve an accurate kinetic model for any reaction mechanism. In simple cases with a single “rate-determining step”, the DRC for its transition state (TS) is + 1. Catalyst-bound intermediates, on the other hand, often have negative DRCs equal to a small integer times their fractional occupancy of catalyst sites. The apparent activation energy equals a weighted average of the standard-state enthalpies (relative to reactants) of all the species (intermediates, transition states and products) in the reaction mechanism, each weighted by its DRC (+RT). It has been shown that the apparent transfer coefficient in electrocatalysis, an inverted form of the Tafel slope, is a weighted average of the number of electrons transferred to generate each intermediate or product species in the mechanism, weighted again by the DRC. Quantitative analysis of kinetic isotope effects (KIEs, or the ratio of net rates for different reactant isotopes) in complex mechanisms has shown that the logarithm of the KIE equals the weighted average over all species in the mechanism of the difference between the two isotopes in their standard-state free energies (÷RT), again weighted by the DRC. The reaction orders with respect to fluid-phase concentrations of reactants, products and intermediates have also been proven to be directly related to DRCs. Thus, there are numerous experimental observables which equate to short linear combinations of DRCs, so that combinations of experimental measurements might provide access to DRC values. Since its invention for transition states in 1994 and its generalization to include intermediates in 2009, the DRC has thus far mainly been calculated for microkinetic models based either entirely on DFT or on DFT with the key energies (i.e., those for high-DRC species) being fine-tuned to match experiments. The relationships summarized in this work provide new opportunities for using experiments earlier in the development and optimization of microkinetic models that require input from computational catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Magnetic order and crystal structure study of YNi{sub 4}Si-type NdNi{sub 4}Si

Magnetic measurements and neutron powder diffraction investigation of the magnetic structure of the orthorhombic YNi{sub 4}Si-type (space group Cmmm) NdNi{sub 4}Si compound are presented. The magnetocaloric effect of NdNi{sub 4}Si is calculated in terms of the isothermal magnetic entropy change and it reaches the maximum value of –3.3 J/kg K for a field change of 50 kOe near T{sub C}=12 K. Below ∼12 K, NdNi{sub 4}Si exhibits a commensurate b-axis collinear ferromagnetic ordering with the Cmm′m magnetic space group in a zero magnetic field. At 1.5 K, the neodymium atoms have the magnetic moment of 2.37(5) μ{sub B}. The orthorhombic crystal structure and its thermal evolution are discussed in comparison with the CaCu{sub 5}-type compound. - Graphical abstract: The NdNi{sub 4}Si supplement the series of the orthorhombic derivative of the CaCu{sub 5}-type, namely the YNi{sub 4}Si-type, RNi{sub 4}Si compounds (R=Y, La, Ce, Sm, Gd–Ho). Below ∼12 K in a zero applied magnetic field, NdNi{sub 4}Si exhibits a commensurate b-axis collinear ferromagnetic ordering with the Cmm′m magnetic space group. Compared to the CaCu{sub 5}-type NdNi{sub 4}Si compound, the YNi{sub 4}Si-type counterpart has the relatively high ferromagnetic ordering temperature (9.2 K vs. 12 K), the small magnetocaloric effect (–7.3 J/kg K vs. –3.3 J/kg K for ∆H=50 kOe), and the large magnetic anisotropy at low temperatures. In contrast with CaCu{sub 5}-type NdNi{sub 4}Si, YNi{sub 4}Si-type NdNi{sub 4}Si shows distinct hysteresis loop at 2 K.We suggest that orthorhombic distortion may be used as a prospective route for optimization of permanent magnetic properties in the family of CaCu{sub 5}-type rare earth materials. - Highlights: • Below ∼12 K the YNi{sub 4}Si-type NdNi{sub 4}Si shows a ferromagnetic ordering. • MCE of NdNi{sub 4}Si reaches value of –3.3 J/kg K in 0–50 kOe near Curie point. • NdNi{sub 4}Si exhibits b-axis ferromagnetic order with the Cmm′m magnetic space group. • Contrary to CaCu{sub 5}-type, YNi{sub 4}Si-type NdNi{sub 4}Si shows hysteresis loop at 2 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Processing-dependent chemical ordering in Cu 3 Au characterized via non-destructive Bragg coherent diffraction imaging

Of current importance for alloy design is controlling chemical ordering through processing routes to optimize an alloy's mechanical properties for a desired application. However, characterization of chemical ordering remains an ongoing challenge, particularly when nondestructive characterization is needed. Here, in this study, Bragg coherent diffraction imaging is used to reconstruct morphology and lattice displacement in model Cu 3 Au nanocrystals that have undergone different heat treatments to produce variation in chemical ordering. The magnitudes and distributions of the scattering amplitudes (proportional to electron density) and lattice strains within these crystals are then analyzed to correlate them to the expected amount of chemical ordering present. Nanocrystals with increased amounts of ordering are found to generally have less extreme strains present and reduced strain distribution widths. In addition, statistical correlations are found between the spatial arrangement of scattering amplitude and lattice strains.

Warren, Nathaniel [Pennsylvania State Univ., Unive↗

High-Performance Pd 3 Pb Intermetallic Catalyst for Electrochemical Oxygen Reduction

Extensive efforts to develop highly active and strongly durable electrocatalyst for oxygen reduction are motivated by a need for metal–air batteries and fuel cells. In this work, we report a very promising catalyst prototype of structurally ordered Pd-based alloys, Pd 3 Pb intermetallic compound. Such structurally ordered Pd 3 Pb/C exhibits a significant increase in mass activity. More importantly, compared to the conventional Pt/C catalysts, ordered Pd 3 Pb/C is highly durable and exhibits a much longer cycle life and higher cell efficiency in Zn-air batteries. Interestingly, ordered Pd 3 Pb/C possesses very high methanol tolerance during electrochemical oxygen reduction, which make it an excellent methanol-tolerant cathode catalyst for alkaline polymer electrolyte membrane fuel cells. Here, we offer a promising route to optimize the synthesis of ordered Pd-based intermetallic catalysts for fuel cells and metal-air batteries.

25 ENERGY STORAGE↗

Photoinduced anisotropic lattice dynamic response and domain formation in thermoelectric SnSe

Identifying and understanding the mechanisms behind strong phonon–phonon scattering in condensed matter systems is critical to maximizing the efficiency of thermoelectric devices. To date, the leading method to address this has been to meticulously survey the full phonon dispersion of the material in order to isolate modes with anomalously large linewidth and temperature-dependence. Here we combine quantitative MeV ultrafast electron diffraction (UED) analysis with Monte Carlo based dynamic diffraction simulation and first-principles calculations to directly unveil the soft, anharmonic lattice distortions of model thermoelectric material SnSe. A small single-crystal sample is photoexcited with ultrafast optical pulses and the soft, anharmonic lattice distortions are isolated using MeV-UED as those associated with long relaxation time and large displacements. We reveal that these modes have interlayer shear strain character, induced mainly by c -axis atomic displacements, resulting in domain formation in the transient state. These findings provide an innovative approach to identify mechanisms for ultralow and anisotropic thermal conductivity and a promising route to optimizing thermoelectric devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Role of precursor chemistry in the direct fluorination to form titanium based conversion anodes for lithium ion batteries

In this study, a new synthetic route for the formation of titanium oxydifluoride (TiOF 2 ) through the process of direct fluorination via a fluidized bed reactor system and the associated electrochemical properties of the powders formed from this approach are reported. The flexibility of this synthetic route was demonstrated using precursor powders of titanium dioxide (TiO 2 ) nanoparticles, as well as a reduced TiO x N y . An advantage of this synthetic method is the ability to directly control the extent of fluorination as a function of reaction temperature and time. The reversible capacity of TiOF 2 anodes was found to depend greatly upon the precursor employed. The TiOF 2 synthesized from TiO 2 and TiO x N y showed reversible capacities of 300 mAh g -1 and 440 mAh g -1 , respectively, over 100 cycles. The higher reversible capacity of the TiOF 2 powders derived from TiO x N y likely relate to the partial reduction of the Ti in the fluorinated electrode material, highlighting a route to optimize the properties of conversion electrode materials.

25 ENERGY STORAGE↗

The importance of phase equilibrium for doping efficiency: iodine doped PbTe

Semiconductor engineering relies heavily on doping efficiency and dopability. Low doping efficiency may cause low mobility and failure to reach target carrier concentrations or even the desired carrier type. Semiconducting thermoelectric materials perform best with degenerate carrier concentrations, meaning high performance in new materials might not be realized experimentally without a route to optimal doping. Doping in the classic PbTe thermoelectric system has been largely successful but reported doping efficiencies can vary, raising concerns about reproducibility. Here, we stress the importance of phase equilibria considerations during synthesis to avoid undesired intrinsic defects leading to sub-optimal doping. By saturation annealing at 973 K, we decidedly fix the composition in single crystal iodine-doped PbTe samples to be Pb-rich or Te-rich without introducing impurity phases. We show that, regardless of iodine concentration, degenerate n-type carrier concentrations with ideal doping efficiency require Pb-rich compositions. Electrons in Te-rich samples are heavily compensated by charged intrinsic Pb vacancy defects. From Hall effect measurements and a simple defect model supported by modern defect calculations, we map out the 973 K ternary Pb–Te–I phase diagram to explicitly link carrier concentration and composition. Furthermore, we discuss unintentional composition changes due to loss of volatile Te during synthesis and measurements. The methods and concepts applied here may guide doping studies on other lead chalcogenide systems as well as any doped, complex semiconductor.

36 MATERIALS SCIENCE↗

Multicharacterization approach for studying InAl(Ga)N/Al(Ga)N/GaN heterostructures for high electron mobility transistors

We report on our multi–pronged approach to understand the structural and electrical properties of an InAl(Ga)N(33nm barrier)/Al(Ga)N(1nm interlayer)/GaN(3μm)/ AlN(100nm)/Al{sub 2}O{sub 3} high electron mobility transistor (HEMT) heterostructure grown by metal organic vapor phase epitaxy (MOVPE). In particular we reveal and discuss the role of unintentional Ga incorporation in the barrier and also in the interlayer. The observation of unintentional Ga incorporation by using energy dispersive X–ray spectroscopy analysis in a scanning transmission electron microscope is supported with results obtained for samples with a range of AlN interlayer thicknesses grown under both the showerhead as well as the horizontal type MOVPE reactors. Poisson–Schrödinger simulations show that for high Ga incorporation in the Al(Ga)N interlayer, an additional triangular well with very small depth may be exhibited in parallel to the main 2–DEG channel. The presence of this additional channel may cause parasitic conduction and severe issues in device characteristics and processing. Producing a HEMT structure with InAlGaN as the barrier and AlGaN as the interlayer with appropriate alloy composition may be a possible route to optimization, as it might be difficult to avoid Ga incorporation while continuously depositing the layers using the MOVPE growth method. Our present work shows the necessity of a multicharacterization approach to correlate structural and electrical properties to understand device structures and their performance.

36 MATERIALS SCIENCE↗

Synthesis and characterization of brownmillerite SrFeO{sub 2.5} in nanostructured form

Synthesis of bulk polycrystalline and nanocrystalline oxygen-deficient SrFeO{sub 2.5} compounds, with potential applications as oxygen membranes, has been explored by chemical route to optimize an easy and reproducible method for high yield. The structure of the samples was investigated by X-ray powder diffraction followed by structural refinement. Both bulk and nanocrystalline SrFeO{sub 2.5} crystallize in Imma space group. X-ray powder diffraction pattern corresponds to the brownmillerite structure in which the Fe cations exist in an octahedral or tetrahedral configuration in alternate layers along the b axis. Brunauer−Emmett−Teller (BET) surface area is found to be 0.40m{sup 2}/g and 14 m{sup 2}/g for bulk and nanocrystalline SrFeO{sub 2.5} respectively. The morphology of these materials was also investigated by scanning electron microscopy and transmission electron microscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Mechanism of shape symmetry breaking in surfactant-mediated crystal growth

We present a dynamical model of crystal growth, in which it is possible to reliably achieve asymmetric products, beginning from symmetric initial conditions and growing within an isotropic environment. The asymmetric growth is the result of a positive feedback mechanism that amplifies the effect of thermal fluctuations in the coverage of surfactants on the growing crystalline facets. Within our simple model, we are able to understand the kinetic and thermodynamic factors involved in both the onset of symmetry breaking and the persistence of anisotropic growth. We demonstrate that the mechanism is general by studying models with increasing complexity. We argue that this mechanism of symmetry breaking underpins observations of colloidal, seed-mediated syntheses of single crystalline metal nanorods capped with strongly interacting surfactants. The parameters within our model are related to experimental observables such as the concentration, hydrophobicity, and binding strength of the surfactants, which suggests a potential route to optimize the yield of asymmetric products in colloidal nanoparticle syntheses.

Oaks-Leaf, Sam↗

Joint Fleet Sizing and Charging System Planning for Autonomous Electric Vehicles

This paper studies the joint fleet sizing and charging system planning problem for a company operating a fleet of autonomous electric vehicles (AEVs) for passenger and goods transportation. Most of the relevant published papers focus on intracity scenarios and adopt heuristic approaches, e.g., agent based simulation, which do not guarantee optimality. In contrast, we propose a mixed integer linear programming model for intercity scenarios. This model incorporates comprehensive considerations of 1) limited AEV driving range; 2) optimal AEV routing and relocating operations; 3) time-varying origin-destination transport demands; and 4) differentiated operation cost structure of passenger and goods transportation. The proposed model can be computational expensive when the scale of the transportation network is large. We then exploit the structure of this program to expedite its solution. Numerical experiments are conducted to validate the proposed method. Our experimental results show that AEVs in passenger and goods transportation have remarkable planning and operation differences. We also demonstrate that intelligent routing and relocating operations, charging system and vehicle parameters, e.g., charging power, battery capacity, driving speed etc., can significantly affect the economic efficiency and the planning results of an AEV fleet.

33 ADVANCED PROPULSION SYSTEMS↗