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At least 91 records · Page 5

Impact of Individual Structural Defects in GaAs Solar Cells: A Correlative and In Operando Investigation of Signatures, Structures, and Effects

Defects usually degrade device performance. Thus, many techniques and effort are devoted to studying semiconductor defects. However, it is rarely known: i) how individual defects affect device performance; ii) how the impact depends on the device operating conditions; iii) how the impact varies from one defect to another; and iv) how these variations are correlated to the microscopic-scale defect structure. To address these crucial questions, an array of correlative and spatially resolved techniques, including electroluminescence, photoluminescence, Raman, I–V characteristics, and high-resolution electron microscopy, are used to characterize dislocation defects in GaAs solar cells. Significantly, the study is carried out in a series mode and in operando. This approach provides quantitative and definitive correlation between the atomistic structure of defects and their explicit effects on device performance, thus giving unprecedented insight into defect physics.

dislocation defects↗

The Effect of Structural Inhomogeneities and Gas-Forming Impurities on the Functional Properties of High Purity Rare-Earth Metals

Rare-earth metals (REM) gadolinium and dysprosium, and also the Gd–H and Dy–H systems in which magnetic order–order and order–disorder phase transitions are accompanied by significant magnetocaloric effect, have been studied. The materials have been prepared in various structural states. It is stated that there is a substantial difference of their functional properties in the dependence on the features of the structural state and also on the existence of a gas-forming impurity. It has been proved experimentally and theoretically that the Curie temperatures of Gd samples with grain sizes of ~200 nm increases as a result of hydrogenation, while the magnetic phase transition temperatures of Dy are almost unchanged Inhomogeneities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantitative Structure–Property Relationship (QSPR) Analysis of ZrO 2 -Containing Soda-Lime Borosilicate Glasses

Quantitative structure–property relationship (QSPR) analysis is a promising approach to correlate structural features with properties of glass materials that lack long-range order and usually have complex structures. By using carefully chosen descriptors based on structural models generated from molecular dynamics (MD) simulations, correlations with properties and insights on glass behaviors can be obtained. Zirconia can significantly alter glass properties including chemical durability, even in a small amount, and hence plays an important role in vitrification of nuclear waste where long-term chemical durability is desired. In this study, borosilicate glasses with the composition of xZrO 2 –(61 – x)SiO 2 –17B 2 O 3 –18Na 2 O–4CaO with x = 0, 1, 2, 4, 6, and 8 were simulated using classical MD simulations with the recently developed composition-dependent potentials. Short-range (e.g., bond distance and coordination numbers) and medium-range (e.g., Qn distribution, network connectivity, and ring-size distribution) structural features altered by ZrO 2 were obtained and analyzed. The use of a descriptor (Fnet descriptor) that combines short-range structural characteristics, from MD simulations, and the cation-oxygen single bond strength was found to provide excellent linear correlations with the density and initial dissolution rate of these glasses. Furthermore, the results show that by combining MD simulations and QSPR analysis the composition and structural effect on the properties of complex multicomponent glasses can be elucidated, thus suggesting that this is a promising approach for future glass research and new composition design.

36 MATERIALS SCIENCE↗

Machine learning for deep elastic strain engineering of semiconductor electronic band structure and effective mass

Abstract The controlled introduction of elastic strains is an appealing strategy for modulating the physical properties of semiconductor materials. With the recent discovery of large elastic deformation in nanoscale specimens as diverse as silicon and diamond, employing this strategy to improve device performance necessitates first-principles computations of the fundamental electronic band structure and target figures-of-merit, through the design of an optimal straining pathway. Such simulations, however, call for approaches that combine deep learning algorithms and physics of deformation with band structure calculations to custom-design electronic and optical properties. Motivated by this challenge, we present here details of a machine learning framework involving convolutional neural networks to represent the topology and curvature of band structures in k -space. These calculations enable us to identify ways in which the physical properties can be altered through “deep” elastic strain engineering up to a large fraction of the ideal strain. Algorithms capable of active learning and informed by the underlying physics were presented here for predicting the bandgap and the band structure. By training a surrogate model with ab initio computational data, our method can identify the most efficient strain energy pathway to realize physical property changes. The power of this method is further demonstrated with results from the prediction of strain states that influence the effective electron mass. We illustrate the applications of the method with specific results for diamonds, although the general deep learning technique presented here is potentially useful for optimizing the physical properties of a wide variety of semiconductor materials.

Tsymbalov, Evgenii↗

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.

97 MATHEMATICS AND COMPUTING↗

Effect of structural disordering on magnetic and magneto-optical properties of F e 3 Si

The electronic, magnetic, transport, and magneto-optical properties of the D0 3 and amorphous Fe 3 Si are investigated by using the first-principles calculations. A strong correlation between local magnetization and atomic arrangement is established. Here, the amorphization significantly alters the spin polarization and the magneto-optical Kerr rotation spectrum but has a little influence on anomalous Hall conductivity. Analyses in band structures and interband matrix elements provide clear insights for the understanding of these results.

36 MATERIALS SCIENCE↗

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗

Investigation of the effect of structural defects from hydride precipitation on superconducting properties of high purity SRF cavity Nb using magneto-optical and electron imaging methods

Abstract Nb is an elemental superconductor with a critical temperature of 9.3 K and is widely used to fabricate superconducting radiofrequency (SRF) cavities for particle accelerators. However, microstructural defects in Nb, such as grain boundaries (GBs) and dislocations, can act as pinning centers for magnetic flux that can degrade SRF cavity performance. Hydrogen contamination is also detrimental to SRF cavity performance due to the formation of normal conducting hydrides during cool down. In this study, disc shaped Nb bi-crystals extracted from high-purity large-grain Nb slices were investigated to study the effects of GBs, hydrogen, and dislocations on superconducting properties. Grain orientation and GB misorientation were measured using Laue x-ray diffraction and electron backscattered diffraction (EBSD) analyses. Cryogenic magneto-optical imaging was used to directly observe magnetic flux penetration below T c = 9.3 K. Damage caused by low temperature precipitation of hydrides and their dissolution upon reheating after cryogenic cycles was examined using electron channeling contrast imaging, and EBSD. The relationships between hydride formation, dislocation content, GBs, cryo-cooling, heat treatment (HT), and flux penetration indicate that both GB character and hydrogen content affect magnetic flux penetration. Such flux penetration could be facilitated by dislocation structures and low angle GBs resulting from hydride precipitation and HT.

36 MATERIALS SCIENCE↗

Machine Learning Prediction of H Adsorption Energies on Ag Alloys

Adsorption energies on surfaces are excellent descriptors of their chemical properties, including their catalytic performance. This has prompted a significant amount of work towards efficiently predicting adsorption energies without performing expensive quantum chemical calculations, based on semi-empirical or data scientific models. Here, we develop machine learning models to predict H adsorption energies on stepped Ag surface alloys using a database of energies obtained from first-principles electronic structure calculations based on density functional theory. Starting with a simple model and iteratively refining the features extracted from the calculations, we determine the key characteristics of successful models, and reduce the number of features required for accurate prediction of the adsorption energy. We find that nonlinear models are essential for accurate predictions. Moreover, detailed comparison of model predictions and calculations reveal a counterintuitive "selfpassivation" induced by some alloying elements, as well as unexpected discontinuous electronic structure effects. These findings are rationalized using tight-binding model hamiltonians and by analyzing the electronic density of states. Lastly, we show that we can estimate the reliability of a particular prediction, mitigating the effects of errors in the small fraction of cases where these errors are significant.

36 MATERIALS SCIENCE↗

Hydrodynamics of countercurrent flows in a structured packed column: effects of initial wetting and dynamic contact angle

The structured packed column has gained considerable attention as a prospective technology to mitigate carbon dioxide emissions from thermal power plants. The computational flow investigation of such systems is a multiscale problem, and local hydrodynamics plays a key role in overall column efficiency. Accordingly, multiphase flow studies in the representative elementary unit (REU) of a packed column can offer insights into the local flow behavior such as flow pattern, interfacial area, etc. The interfacial area plays a key role in the overall interphase mass transfer and thereby in separation efficiency. The predicted effective area matches well with corresponding ones in experiments for Mellapak 250.Y packings. The contact angle (i.e., solid substrate behavior) is one of the critical factors that dictates wettings, and thereby the interfacial area. The dynamic contact angle (DCA) was considered in order to explore the effects of contact angle hysteresis on the interfacial area. DCA has more pronounced impact on the interfacial area for a solvent possessing a higher value of surface tension and equilibrium contact angle. The interfacial area shows temporal undulation and does not achieve a pseudo steady state due to the capillary force. In contrary, the interfacial area gets a net value for a solvent having low surface tension value. Further, specification of the static contact angle at the solid substrate shows the least value of the interfacial area. We also extensively studied the effect of the initial sheet condition (dry vs wet) on the interfacial area. The initially wetted sheets show slightly higher value of the interfacial area as compared to the initially dry sheets at a fixed flow rate for a solvent having high surface tension value. Wetting hysteresis decreases with increasing liquid loads. On the other hand, wetting hysteresis does not occur for a solvent having value of low surface tension and equilibrium contact angle.

structured packings, dynamic contact angle, interf↗

Mononuclear to Polynuclear U(IV) Structural Units: Effects of Reaction Conditions on U-Furoate Phase Formation

In this work, Uranium(IV) complexation by 2-furoic acid was examined to better understand the effects of ligand identity and reaction conditions on species formation and stability. Five compounds were isolated: [UCl 2 (2-FA) 2 (H 2 O) 2 ] n (1), [U 4 Cl 10 O 2 (THF) 6 (2-FA) 2 ]•2(THF) (2), [U 6 O 4 (OH) 4 (H 2 O) 3 (2-FA) 12 ]•7(THF)•(H 2 O) (3), [U 6 O 4 (OH) 4 (H 2 O) 2 (2-FA) 12 ]•8.76(H 2 O) (4), and [U 38 Cl 42 O 54 (OH) 2 (H 2 O) 20 ]•m(H 2 O)•n(THF) (5). The structures were determined by single crystal X-ray diffraction and further characterized by Raman, IR, and optical absorption spectroscopy. The thermal stability and magnetic behavior of the compounds were also examined. Variations in the synthetic conditions led to notable differences in the structural units observed in the solid state. At low H 2 O/THF ratios, a tetranuclear oxo bridged [U 4 O 2 ] core was isolated. Aging of this solution resulted in the formation a U 38 oxo cluster capped by chloro and water ligands. However, at increasing water concentrations only hexanuclear units were observed. In all cases, at temperatures of 100-120 °C, UO 2 nanoparticles formed.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Masses and β-Decay Spectroscopy of Neutron-Rich Odd-Odd 160,162 Eu Nuclei: Evidence for a Subshell Gap with Large Deformation at N = 98

The structure of deformed neutron-rich nuclei in the rare-earth region is of significant interest for both the astrophysics and nuclear structure fields. At present, a complete explanation for the observed peak in the elemental abundances at A ~ 160 eludes astrophysicists, and models depend on accurate quantities, such as masses, lifetimes, and branching ratios of deformed neutron-rich nuclei in this region. Unusual nuclear structure effects are also observed, such as the unexpectedly low energies of the first 2 + levels in some even-even nuclei at N = 98. In order to address these issues, mass and β-decay spectroscopy measurements of the 160 Eu 97 and 162 Eu 99 nuclei were performed at the Californium Rare Isotope Breeder Upgrade radioactive beam facility at Argonne National Laboratory. Here, evidence for a gap in the single-particle neutron energies at N = 98 and for large deformation (β 2 ~ 0.3) is discussed in relation to the unusual phenomena observed at this neutron number.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Microwave-Hydrothermal Synthesis of Y{sub 3}Fe{sub 5}O{sub 12} Nanoparticles: Sintering Temperature Effect on Structural, Magnetic and Dielectric Properties

Herein, we report a facile microwave-assisted hydrothermal method for the preparation of yttrium iron garnet (YIG, Y{sub 3}Fe{sub 5}O{sub 12})nanocrystals and realized the synergy between its structural and magnetic properties. The as-prepared powder thermal stability was characterized in detail by using thermogravimetric-differential thermal analysis (TG-DTA). The synthesized powder was microwave sintered at six different temperatures ranging from 973 to 1373 K for 60 min and characterized using X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM). Magnetic properties were investigated by vibrating-sample magnetometer (VSM) and ferromagnetic resonance (FMR) studies. The frequency variation of dielectric and magnetic properties was measured in the frequency range of 100 kHz–1.8 GHz. The observed magnetic and dielectric parameters such as saturation magnetization, coercivity, permeability, linewidth, dielectric constant and magnetodielectric losses are strongly affected by sintering temperature. The saturation magnetization and coercivity of YIG were found in the range 14.4–28.0 emu/g and 35–87 Oe, respectively. Furthermore, the FMR linewidth decreases from 844 to 204 Oe. This analysis undoubtedly demonstrates that the synthesis method and sintering temperature have the prominent effect on the electrical and magnetic properties of YIG and would be very useful for the garnet-based microwave device applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Gallium‐Doping Effects on Structure, Lithium‐Conduction, and Thermochemical Stability of Li 7‐3 x Ga x La 3 Zr 2 O 12 Garnet‐Type Electrolytes

Abstract One of the most promising electrolytes for all‐solid‐state lithium batteries is Li 7 La 3 Zr 2 O 12 . Previously, their thermodynamic stability, Li‐ion conductivity, and structural features induced by Ga‐doping have not been empirically determined or correlated. Here, their interplay was examined for Li 7−3 x Ga x La 3 Zr 2 O 12 with target x Ga=0, 0.25, 0.50, 0.75, and 1.00 atoms per formula unit (apfu). Formation enthalpies, obtained with calorimetry and found to be exothermic at all compositions, linearly decreased in stability with increased x Ga. At dilute x Ga substitution, the formation enthalpy curve shifted stepwise endothermically, and the conductivity increased to a maximum, coinciding with 0.529 Ga apfu. This correlated with percolation threshold analysis (0.558 Ga apfu). Further substitution (0.787 Ga apfu) produced a large decrease in the stability and conductivity due to a large increase in point defects and blocked Li‐migration pathways. At x Ga=1.140 apfu, a small exothermic shift was related to defect cluster organization extending the Li hopping distance and decreased Li‐ion conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of structure and volcanic stratigraphy on groundwater and surface water flow: Hat Creek basin, California, USA

Abstract Hydrogeologic systems in the southern Cascade Range in California (USA) develop in volcanic rocks where morphology, stratigraphy, extensional structures, and attendant basin geometry play a central role in groundwater flow paths, groundwater/surface-water interactions, and spring discharge locations. High-volume springs (greater than 3 m 3 /s) flow from basin-filling (<800 ka) volcanic rocks in the Hat Creek and Fall River tributaries and contribute approximately half of the average annual flow of the Pit River, the largest tributary to Shasta Lake. A hydrogeologic conceptual framework is constructed for the Hat Creek basin combining new geologic mapping, water-well lithologic logs, a database of active faults, LiDAR mapping of faults and volcanic landforms, streamflow measurements and airborne thermal infrared remote sensing of stream temperature. These data are used to integrate the geologic structure and the volcanic and volcaniclastic stratigraphy to create a three-dimensional interpretation of the hydrogeology in the basin. Two large streamflow gains from focused groundwater discharge near Big Spring and north of Sugarloaf Peak result from geologic barriers that restrict lateral groundwater flow and force water into Hat Creek. The inferred groundwater-flow barriers divide the aquifer system into at least three leaky compartments. The two downstream compartments lose streamflow in the upstream reaches (immediately downstream of the groundwater-flow barriers) and gain in downstream reaches with the greatest inflows immediately upstream of the barriers.

Geology↗

Thermal Annealing Effect on Structure and Properties of Tungsten Surface Irradiated with High Fluence and Low Energy Alpha-Particles

The paper presents research into the surface morphology, helium cluster formation and mechanical properties of high-purity tungsten after the high fluence and low-energy helium ion implantation and subsequent annealing. Investigations are based on scanning electron and atomic force microscopy observations and thermal desorption measurements. Because of the local stresses appearing within the energy loss straggling of helium ions, atoms migrate at distances significantly increasing the ion projective range, and create mobile coalescence of helium atoms and immobile helium-vacancy clusters. The latter form helium bubbles in the energy loss straggling which cause the surface blistering. Local stresses induced by helium coalescence and helium-vacancy clusters beyond the energy loss straggling result in the material strengthening or hardness increase. Subsequent 600°С annealing provides the size growth of blisters on the metal surface irradiated with helium ions and high helium desorption due to the migration of mobile coalescence of helium atoms. With the increasing annealing temperature from 600 to 1000°С, the layer corresponding to the projective range of helium ions fully fractures due to the interstitial helium atoms releasing from immobile helium-vacancy clusters. After 1000°С annealing, the tungsten hardness returns to its initial value.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗