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At least 55 records · Page 3

Temperature effects in spin-dependent Hall currents in an ideal skyrmion gas

The quest of novel reliable and fast performing logic and memory elements in classical and quantum computing requires discoveries of new effects in novel quantum materials. Skyrmions are such magnetic textures where electron scattering can essentially change the shape and location of the skyrmion, which can be used as a memory element being more efficient than domain walls as memory device in classical computing. Because the skyrmion motion is sensitive even to very small currents, we study electron scattering by skyrmions in an ideal skyrmion gas in ferromagnetic environment. In such systems, the direct and Hall currents become spin-dependent. For applications it is important to consider a Hall effect in the whole range of temperatures under the assumption of the skyrmion existence. In this study we find the nonmonotonic temperature dependence of the direct spin-up conductivity, i. e., the conductivity for the current directed along the applied electric field due to the electrons with the spin parallel to the ferromagnetic moment. Such a behavior contradicts the traditional understanding where the temperature only increases the value of the conductivity. The spin-down Hall conductivity is found to be even more dramatic exhibiting the conductivity sign change (i.e., the change in the current direction) with temperature for small skyrmion sizes. The found effects strongly depend on Fermi energy. The most pronounced dependencies take place if the Fermi energy is slightly below and above the bottom of the upper (spin-down) energy band of an ideal 2D electron gas. In addition, we also find that the direct and Hall resistivities, ρ xx and ρ xy , are independent of the exchange integral J for 2J > ε F .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Data of High-Temperature Dynamic LCM Testing Setup

Data from high temperature dynamic sealing tests for various fracture widths, at various temperatures (degrees F), with 5 wt.% bentonite-based mud containing various material fiber contents, at 100 to 400 psi differential pressure. Data from pressure test and evaluation of the dynamic lost circulation materials (LCM) testing unit to reflect the condition of open and sealed fracture using fracture width of 1000 microns at 120 degrees F. Links to two papers based on the data - "Loss circulation prevention in geothermal drilling by shape memory polymer" which was published in Geothermics 89 (2021) 101943) as well as "Evaluating sealability of blended smart polymer and fiber additive for geothermal drilling with the effect of fracture opening size", published in the Journal of Petroleum Science and Engineering 206 (2021) 108998.

15 GEOTHERMAL ENERGY↗

A PIPS + SrI 2 (Eu) detector for atmospheric radioxenon monitoring

The PIPS–SrI 2 (Eu) is a prototype atmospheric radioxenon detection system designed at Oregon State University in support of international efforts towards monitoring clandestine nuclear weapon testing activities. This detector aims to address some shortcomings found in currently deployed beta–gamma atmospheric radioxenon detection systems, such as lackluster energy resolution and memory effect, by employing modern detection materials and readout. The system uses a PIPSBox, a silicon-based gas cell, for electron detection, and a pair of ultrabright, D-shaped SrI 2 (Eu) scintillators coupled to silicon photomultipliers for photon detection. A custom eight-channel digital pulse processor equipped with a field programmable gate-array (FPGA) identifies electron–photon coincidences between the volumes in near real-time. Gas samples of the four radioxenon isotopes of interest were independently measured with the PIPS–SrI 2 (Eu) detection system to determine energy resolution and efficiency. Application of FPGA-based coincidence discrimination in near real-time reduced the ambient background count rate by 95.85 ± 0.04%. Using parameters from the Xenon International gas processing unit and assuming a blank sample and zero memory effect the minimum detectable concentrations (MDCs) for the isotopes were calculated to be 0.12 ± 0.03, 0.27 ± 0.05, 0.15 ± 0.02, and 1.00 ± 0.08 mBq/m 3 air for 131m Xe, 133 Xe, 133m Xe, and 135 Xe, respectively. These MDC estimates compare well with other radioxenon detection systems employed in the International Monitoring System (IMS) and indicate that the PIPS–SrI 2 (Eu) is in compliance with the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO) sensitivity requirement of ≤ 1 mBq/m 3 for 133 Xe.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Effect of hatch spacing and laser power on microstructure, texture, and thermomechanical properties of laser powder bed fusion (L-PBF) additively manufactured NiTi

This study systematically evaluates the effects of laser powder bed fusion additive manufacturing (L-PBF-AM) parameters (hatch spacing and laser power) on the thermomechanical behavior and microstructure of Ni 50.8 Ti 49.2 shape memory alloy. The samples were fabricated with hatch spacings from 40 to 240 µm and laser powers of 50 and 100 W at a constant scanning speed of 125 mm/s, resulting in parts with volumetric energy density levels from 55 to 666 J/mm 3 and two sets of linear energy densities of 0.4 and 0.8 J/mm. The results showed a reduced melt pool size and discontinuity of scan tracks with decreased laser power. Additionally, the porosity level was increased with larger hatch spacing and lower laser power. More notably, the transformation temperatures increased, and the critical stress, recoverable strain, and functional stability of samples improved with lower hatch spacing, where the recovery ratio of up to 90% was observed, regardless of the employed laser power. This study also discussed the relationship between the fabrication process and texture formation in the L-PBF-AM process. In conclusion, the advantage of L-PBF-AM was revealed in tailoring the microstructure from highly textured samples in [1 1 1] or [0 0 1] direction when hatch spacing lower than laser beam focused was employed, to the appearance of equiaxed solidification front with island grains and random orientations.

36 MATERIALS SCIENCE↗

DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology

Abstract. Vegetation phenology plays a key role in controlling the seasonality of ecosystem processes that modulate carbon, water and energy fluxes between the biosphere and atmosphere. Accurate modelling of vegetation phenology in the interplay of Earth's surface and the atmosphere is thus crucial to understand how the coupled system will respond to and shape climatic changes. Phenology is controlled by meteorological conditions at different timescales: on the one hand, changes in key meteorological variables (temperature, water, radiation) can have immediate effects on the vegetation development; on the other hand, phenological changes can be driven by past environmental conditions, known as memory effects. However, the processes governing meteorological memory effects on phenology are not completely understood, resulting in their limited performance of vegetation phenology represented in land surface models. A deep learning model, specifically a long short-term memory network (LSTM), has the potential to capture and model the meteorological memory effects on vegetation phenology. Here, we apply the LSTM to model the vegetation phenology using meteorological drivers and high-temporal-resolution canopy greenness observations through digital repeat photography by the PhenoCam network. We compare a multiple linear regression model, a no-memory-effect LSTM model and a full-memory-effect LSTM model to predict the whole seasonal greenness trajectory and the corresponding phenological transition dates across 50 sites and 317 site years during 2009–2018, covering deciduous broadleaf forests, evergreen needleleaf forests and grasslands. Results show that the deep learning model outperforms the multiple linear regression model, and the full-memory-effect LSTM model performs better than the no-memory-effect model for all three plant function types (median R2 of 0.878, 0.957 and 0.955 for broadleaf forests, evergreen needleleaf forests and grasslands). We also find that the full-memory-effect LSTM model is capable of predicting the seasonal dynamic variations of canopy greenness and reproducing trends in shifting phenological transition dates. We also performed a sensitivity analysis of the full-memory-effect LSTM model to assess its plausibility, revealing its coherence with established knowledge of vegetation phenology sensitivity to meteorological conditions, particularly changes in temperature. Our study highlights that (1) multi-variate meteorological memory effects play a crucial role in vegetation phenology, and (2) deep learning opens up new avenues for improving the representation of vegetation phenological processes in land surface models via a hybrid modelling approach.

Geology↗

A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

Abstract The design of materials and identification of optimal processing parameters constitute a complex and challenging task, necessitating efficient utilization of available data. Bayesian Optimization (BO) has gained popularity in materials design due to its ability to work with minimal data. However, many BO-based frameworks predominantly rely on statistical information, in the form of input-output data, and assume black-box objective functions. In practice, designers often possess knowledge of the underlying physical laws governing a material system, rendering the objective function not entirely black-box, as some information is partially observable. In this study, we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making process. We demonstrate that this method significantly improves decision-making efficiency and enables more data-efficient BO. The applicability of this approach is showcased through the design of NiTi shape memory alloys, where the optimal processing parameters are identified to maximize the transformation temperature.

Chemistry↗

Role of point defects in stress-induced martensite transformations in NiTi shape memory alloys: A molecular dynamics study

Shape-memory properties of equiatomic NiTi rely on the thermal- or stress-induced reversible martensitic phase transformation between the $\textit{B}$2 and $\textit{B}$19' phases. Irradiation defects suppress thermal-induced transformations, but their effects on stress-induced transformations are poorly understood. In this work, we use molecular dynamics to investigate the effect of vacancies, vacancy clusters, interstitials, and antisite defects on stress-induced transformations. All defects suppress the transformation, but vacancy clusters do so to the greatest extent, while antisite defects do so to the least extent. The responsible mechanisms are grain boundary pinning and chemical disordering.

36 MATERIALS SCIENCE↗

Evaluating sealability of blended smart polymer and fiber additive for geothermal drilling with the effect of fracture opening size

Geothermal formations often contain extensive fracture networks. These fracture networks contribute to the significant loss of drilling fluids during geothermal drilling. Multiple loss circulation materials (LCM) such as fiber, granules, and pills have been proposed to tackle this problem but with only limited success. Recent advances in materials science have led to the development of thermoset shape memory polymers (SMP) to address the lost circulation problem. In this paper, we evaluate a thermoset SMP performance in sealing near wellbore fractures of different sizes in geothermal wells. The SMP performance was assessed using granite disks and cylindrical granite cores having fracture sizes of 1000 μm and 3000 μm. A static filtration test was performed using cedar fiber, CaCO 3 , and SMP. Results showed cedar fiber performed better than the CaCO 3 ., reducing fluid loss by 89% and improving sealing pressure by 200 psi. A novel dynamic testing unit that allows for high-temperature testing under flowing conditions was used in this study. The analysis showed that 3% by weight SMP and fiber blends could bridge and plug the 1000 μm fracture. For a larger fracture of 3000 μm width, there was a need to increase the weight concentration of the SMP to 6% to plug the fracture opening effectively. We showed the influence of key parameters such as the type of LCM, concentration, and particle size distribution in optimizing the performance of drilling fluid loss treatment.

02 PETROLEUM↗

Filled Elastomers: Mechanistic and Physics-Driven Modeling and Applications as Smart Materials

Elastomers are made of chain-like molecules to form networks that can sustain large deformation. Rubbers are thermosetting elastomers that are obtained from irreversible curing reactions. Curing reactions create permanent bonds between the molecular chains. On the other hand, thermoplastic elastomers do not need curing reactions. Incorporation of appropriated filler particles, as has been practiced for decades, can significantly enhance mechanical properties of elastomers. However, there are fundamental questions about polymer matrix composites (PMCs) that still elude complete understanding. This is because the macroscopic properties of PMCs depend not only on the overall volume fraction (ϕ) of the filler particles, but also on their spatial distribution (i.e., primary, secondary, and tertiary structure). This work aims at reviewing how the mechanical properties of PMCs are related to the microstructure of filler particles and to the interaction between filler particles and polymer matrices. Overall, soft rubbery matrices dictate the elasticity/hyperelasticity of the PMCs while the reinforcement involves polymer–particle interactions that can significantly influence the mechanical properties of the polymer matrix interface. For ϕ values higher than a threshold, percolation of the filler particles can lead to significant reinforcement. While viscoelastic behavior may be attributed to the soft rubbery component, inelastic behaviors like the Mullins and Payne effects are highly correlated to the microstructures of the polymer matrix and the filler particles, as well as that of the polymer–particle interface. Additionally, the incorporation of specific filler particles within intelligently designed polymer systems has been shown to yield a variety of functional and responsive materials, commonly termed smart materials. We review three types of smart PMCs, i.e., magnetoelastic (M-), shape-memory (SM-), and self-healing (SH-) PMCs, and discuss the constitutive models for these smart materials.

36 MATERIALS SCIENCE↗

Nanocrystalline strain glass TiNiPt and its superelastic behavior

TiNi-based shape-memory alloys are known to exhibit a strain glass state under certain conditions, generally in the presence of high-density defects such as excess solute atoms or alloying elements, dislocations, and nanoprecipitates. In this paper, we report a strain glass transition in a nanocrystalline Ti 50 Ni 35 Pt 15 alloy. The nanocrystalline strain glass state is achieved by a combined effect of high-density grain boundaries and high concentration doping of Pt atoms in the B2 matrix. The nanocrystalline Ti 50 Ni 35 Pt 15 strain glass alloy showed a large near-complete progressive superelasticity with a recovery strain of about 6% and a low apparent Young's modulus of about 30 GPa in a wide temperature range of over 200 °C. In situ synchrotron x-ray diffraction measurement showed that the strain glass B2 [B2(SG)] phase experienced B2(SG)→R→B19 transformation upon loading and B19→B2(SG) upon unloading. The findings of this study provide insight for the development of nanocrystalline strain glass shape-memory alloys.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Magnetism and structure of Fe- and Co-substituted Mn 2 NiSn

Mn-containing Heuslers are important magnetic shape-memory alloys for fast and precise actuators in manufacturing, robotics, surgery, and other applications. Among the key requirements are a high magnetization and favorable thermal properties, especially a high Curie temperature. In this work, the effect of Fe and Co substitution on the structure and magnetism of Mn 2 NiSn alloys is investigated. The Heusler alloys have been produced by melt spinning and characterized by X-ray diffraction, magnetometry, and electron-transport measurements. It was found that Co substitution for Mn enhances the Curie temperature of Mn 2 NiSn and both Co and Fe substitution improve its magnetization. Further, these improvements are accompanied by reduced thermal and magnetic hysteresis losses and by interesting structural changes, namely improved chemical order and site occupancies characteristic of quaternary (Y-ordered) Heuslers.

36 MATERIALS SCIENCE↗

Spin Solar Cell Phenomenon on a Single-Molecule Magnet (SMM) Impacted CoFeB-Based Magnetic Tunnel Junctions

The single-molecule magnet (SMM) is demonstrated here to transform conventional magnetic tunnel junctions (MTJs), a memory device used in present-day computers, into solar cells. For the first time, we demonstrated an electronic spin-dependent solar cell effect on an SMM-transformed MTJ under illumination from unpolarized white light. We patterned cross-junction-shaped devices to form a CoFeB/MgO/CoFeB-based MTJ. The MgO barrier thickness at the intersection between the two exposed junction edges was less than the SMM extent, which enabled the SMM molecules to serve as channels to conduct spin-dependent transport. The SMM channels yielded a region of long-range magnetic ordering around these engineered molecular junctions. Our SMM possessed a hexanuclear [Mn 6 (μ 3 -O) 2 (H 2 N-sao) 6 (6-atha) 2 (EtOH) 6 ] [H 2 N-saoH = salicylamidoxime, 6-atha = 6-acetylthiohexanoate] complex and thioesters end groups to form bonds with metal films. SMM-doped MTJs were shown to exhibit a solar cell effect and yielded ≈80 mV open-circuit voltage and ≈10 mA/cm 2 saturation current density under illumination from one sun equivalent radiation dose. A room-temperature Kelvin Probe AFM (KPAFM) study provided direct evidence that the SMM transformed the electronic properties of the MTJ’s electrodes over a lateral area in excess of several thousand times larger in extent than the area spanned by the molecular junctions themselves. As a result, the decisive factor in observing this spin-photovoltaic effect is the formation of SMM spin channels between the two different ferromagnetic electrodes, which in turn is able to catalyze the long-range transformation in each electrode around the junction area.

14 SOLAR ENERGY↗

Additively Manufacturing Nitinol Shape Memory Alloys for Advanced Actuator Designs

The objective of this research was to understand the role of feedstock production in the phase transformation behavior of additively manufactured Ni-Ti alloys for advanced actuator design. Industrial adoption of additively manufactured Ni-Ti alloys depends on the ability to produce repeatable phase transformation behavior, quantified here by the austenite to martensite transformation on heating. Small variations in the alloy composition may have a significant effect on the temperature at which this transformation occurs. This project showed that the powder characteristics play an important role in determining this behavior. Increases in the surface area per unit volume of the powder, either as a function of size distribution or morphology, have the effect of reducing the Ti content in the alloy through the formation of Ti-rich oxides on the powder surface, which has the effect of depressing the transformation temperature. Preferential Ni vaporization during additive manufacturing can partially offset this effect. To achieve repeatable results, it is important to understand the effect of powder oxidation, and to control the powder characteristics.

36 MATERIALS SCIENCE↗

LPBF Processability of NiTiHf Alloys: Systematic Modeling and Single-Track Studies

Research into the processability of NiTiHf high-temperature shape memory alloys (HTSMAs) via laser powder bed fusion (LPBF) is limited; nevertheless, these alloys show promise for applications in extreme environments. This study aims to address this limitation by investigating the printability of four NiTiHf alloys with varying Hf content (1, 2, 15, and 20 at. %) to assess their suitability for LPBF applications. Solidification cracking is one of the main limiting factors in LPBF processes, which occurs during the final stage of solidification. To investigate the effect of alloy composition on printability, this study focuses on this defect via a combination of computational modeling and experimental validation. To this end, solidification cracking susceptibility is calculated as Kou’s index and Scheil–Gulliver model, implemented in Thermo-Calc/2022a software. An innovative powder-free experimental method through laser remelting was conducted on bare NiTiHf ingots to validate the parameter impacts of the LPBF process. The result is the processability window with no cracking likelihood under diverse LPBF conditions, including laser power and scan speed. This comprehensive investigation enhances our understanding of the processability challenges and opportunities for NiTiHf HTSMAs in advanced engineering applications.

36 MATERIALS SCIENCE↗

Unconventional short-range structural fluctuations in cuprate superconductors

Abstract The interplay between structural and electronic degrees of freedom in complex materials is the subject of extensive debate in physics and materials science. Particularly interesting questions pertain to the nature and extent of pre-transitional short-range order in diverse systems ranging from shape-memory alloys to unconventional superconductors, and how this microstructure affects macroscopic properties. Here we use neutron and X-ray diffuse scattering to uncover universal structural fluctuations in La 2-x Sr x CuO 4 and Tl 2 Ba 2 CuO 6+δ , two cuprate superconductors with distinct point disorder effects and with optimal superconducting transition temperatures that differ by more than a factor of two. The fluctuations are present in wide doping and temperature ranges, including compositions that maintain high average structural symmetry, and they exhibit unusual, yet simple scaling behaviour. The scaling regime is robust and universal, similar to the well-known critical fluctuations close to second-order phase transitions, but with a distinctly different physical origin. We relate this behaviour to pre-transitional phenomena in a broad class of systems with structural and magnetic transitions, and propose an explanation based on rare structural fluctuations caused by intrinsic nanoscale inhomogeneity. We also uncover parallels with superconducting fluctuations, which indicates that the underlying inhomogeneity plays an important role in cuprate physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The root-zone soil moisture spectrum in a mediterranean ecosystem

Storage of water within soil pores of the root zone introduce memory effects in the dynamics of soil moisture that are considerably longer than the integral timescale of many atmospheric processes. Thus, hydro-climatic states can be “sustained” through land-surface heat and water vapor fluxes primarily because they can “feed off” on this long-term soil moisture memory. Root-zone soil moisture memory is only but one feature characterizing the spectrum of soil moisture dynamics, which is analyzed here using a combination of long-term measurements and models. In particular, the spectrum of root-zone soil moisture content in a Mediterranean ecosystem is examined using 14-years of half-hourly measurements. A distinguishing hydro-climatic feature in such ecosystems is that sources (mainly rainfall) and sinks (mainly evapotranspiration) of soil moisture are roughly out of phase with each other. For over 4 decades of time scales and 7 decades of energy, the canonical shape of the measured soil moisture spectrum is shown to be approximately Lorentzian determined by the soil moisture variance and its memory but with two exceptions: the occurrences of a peak at diurnal-to-daily time scales and a weaker peak at near annual time scales. Model calculations and spectral analysis demonstrate that diurnal and seasonal variations in hydroclimate forcing responsible for variability in evapotranspiration had minor impact on the normalized shape of the soil moisture spectrum. However, their impact was captured by adjustments in the temporal variance. These findings indicate that precipitation and not evapotranspiration variability dominates the multi-scaling properties of soil moisture variability consistent with prior climate model simulations. Furthermore, the soil moisture memory inferred by the annual peak of soil moisture (340 d) is consistent with climate model simulations, while the memory evaluated from the loss function of a linearized mass balance approach leads to a smaller value (50 d), highlighting the effect of weak non-stationarity on soil moisture variability.

54 ENVIRONMENTAL SCIENCES↗

Boundary conditions manipulation of polar vortex domains in BiFeO 3 membranes via phase-field simulations

Polar vortex domains have recently become an emergent research field due to the abundant physical phenomena and potential applications in high-density memories. Here, we explore the mechanisms of creating polar vortex domains in the BiFeO3 (BFO) membranes subjected to different boundary conditions using phase-field simulations. A major difference is that the vortex in membrane can be stabilized even under short-circuit electrical boundary conditions compared to vortex in other systems, such as thin film or superlattice. We found that (a) the formation of polar vortex domains at the membrane interior under bending is mainly driven by the reduction of elastic energy under short-circuit boundary condition, and the vortex chirality (namely, clockwise and counterclockwise) could be identified by n-shape and u-shape bending; (b) in the unbent open-circuit BFO membrane case, exotic trapezoid-shaped vortex nanodomains form at the terminations of 109 degrees domain walls (DWs) and partially charged 71 degrees DWs, which is driven by the local depolarization field and the interplay among electrostatic, elastic, and gradient and Landau energies. We also examine Kittel's law by establishing the dependence of vortex periods on the membrane thickness. Furthermore, these results give further understanding of the effect of boundary conditions on the formation of polar vortex domains, guiding experimental designs of vortex-based high-density memories.

36 MATERIALS SCIENCE↗

Experimental study on rheological and settling properties of shape memory polymer for fracture sealing in geothermal formations

This article studies the rheology and annular flow of a smart lost circulation material (LCM) at 160 °C, using a high-temperature flow loop. The smart LCM is a shape memory polymer (SMP) that activates at high temperatures, and its particle size increases to seal fractures in geothermal formations. SMP was mixed with the base fluid in two different concentrations, 1.0 and 3.0 wt%, to study rheology, wellbore hydraulics, activation process, and settling behavior under different testing conditions. The results of this study showed that the SMP could be activated at high temperatures. An increase of 80–100% in the particle size was observed at 160 °C. The mud samples showed a high shear-thinning behavior at the two concentrations with a Power-law flow index (n) ranging between 0.025 and 0.101. No additional frictional pressure losses were observed when SMP was added to the base fluid. SMP particles showed an excellent suspension at 1.0 wt% while, at 3.0 wt%, a bed was formed at a low flow rate and without pipe rotation. Increasing the drill pipe rotational speed or flow rate effectively removed the bed and homogeneously dispersed the SMP particles, ensuring a better sealing efficiency. SMP particle dispersion in inclined wells was better than in horizontal wells. Moreover, the findings of this study help optimize the lost circulation treatment by considering a wide range of operating parameters that can further be extended to different systems and geometries.

02 PETROLEUM↗