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Defects and Defect Engineering of Two-Dimensional Transition Metal Dichalcogenide (2D TMDC) Materials

As layered materials, transition metal dichalcogenides (TMDCs) are promising two-dimensional (2D) materials. Interestingly, the characteristics of these materials are transformed from bulk to monolayer. The atomically thin TMDC materials can be a good alternative to group III–V and graphene because of their emerging tunable electrical, optical, and magnetic properties. Although 2D monolayers from natural TMDC materials exhibit the purest form, they have intrinsic defects that limit their application. However, the synthesis of TMDC materials using the existing fabrication tools and techniques is also not immune to defects. Additionally, it is difficult to synthesize wafer-scale TMDC materials for a multitude of factors influencing grain growth mechanisms. While defect engineering techniques may reduce the percentage of defects, the available methods have constraints for healing defects at the desired level. Thus, this holistic review of 2D TMDC materials encapsulates the fundamental structure of TMDC materials, including different types of defects, named zero-dimensional (0D), one-dimensional (1D), and two-dimensional (2D). Moreover, the existing defect engineering methods that relate to both formation of and reduction in defects have been discussed. Finally, an attempt has been made to correlate the impact of defects and the properties of these TMDC materials.

2D materials↗

Nearly hyperuniform, nonhyperuniform, and antihyperuniform density fluctuations in two-dimensional transition metal dichalcogenides with defects

Hyperuniform many-body systems in d-dimensional Euclidean space R d are characterized by completely suppressed (normalized) infinite-wavelength density fluctuations, and appear to be endowed with novel exotic physical properties. Recently, hyperuniform systems of disordered varieties have been observed in the context of various atomic-scale two-dimensional (2D) materials. Here, we analyze the effects of localized defects on the density fluctuations across length scales and on the hyperuniformity property of experimental samples of two-dimensional transition metal dichalcogenides. In particular, we extract atomic coordinates from time series annular dark field-scanning transmission electron microscopy (ADF-STEM) imaging data of 2D tungsten chalcogenides with the 2H structure (Te-doped 2H-WSe 2 ) showing continuous development and evolution of electron-beam induced defects, and construct the corresponding chemical-bonding informed coordination networks between the atoms. We then compute a variety of pair statistics and bond-orientational statistics to characterize the samples. At low defect concentrations, the corresponding materials are nearly hyperuniform, characterized by significantly suppressed scattering at the zero wave-number limit (omitting forward/ballistic scattering). As more defects are introduced, the (approximate) hyperuniformity of the materials is gradually destroyed, and the system becomes non-hyperuniform even when the material still contains a significant amount of crystalline regions. At high defect concentrations, the structures become antihyperuniform with diverging (normalized) large-scale density fluctuations, mimicking those typically observed at the thermal critical points associated with phase transitions. Overall, the defected materials possess varying degrees of orientation order, and there is apparently no intermediate hexatic phase emerging. To understand the observed nearly hyperuniform density fluctuations in the slightly defected materials, we construct a minimalist structural model and demonstrate that the experimental samples can be essentially viewed as perturbed honeycomb crystals with small correlated displacements and double chalcogen vacancies. Moreover, the small correlated displacements alone can significantly degrade hyperuniformity of the perfect honeycomb structure. Therefore, even a small amount of vacancies, when coupled with correlated displacements, can completely destroy hyperuniformity of the system.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Elucidation of Ce/Zr ratio effects on the physical properties and catalytic performance of CuO x /Ce y Zr 1− y O 2 catalysts

Although cerium oxide (CeO 2 ) is widely used as a catalyst support, its limited defect sites and surface oxygen vacancy/mobility should be improved. The incorporation of zirconium (Zr) in the cerium (Ce) lattice is shown to increase the number of oxygen vacancies and improve catalytic activity. Using a fixed surface density (SD) of copper (∼2.3 Cu atoms per nm 2 ) as a surface species, the role of the support (Ce y Zr 1−y O 2 (y = 1.0, 0.9, 0.6, 0.5, and 0.0)) and defect site effects in the CO oxidation reaction was investigated. Spectroscopic (e.g., Raman, XRD, XPS) and microscopic (e.g., SEM-EDX, HR-TEM) characterization techniques were applied to evaluate the defect sites, crystallite size, lattice parameters, chemical composition, oxidation states of elements and microstructure of the catalysts. Here, the CO oxidation reaction with varied CO : O 2 ratios (1 : 5, 1 : 1, and 1 : 0.5 (stoichiometric)) was used as a model reaction to describe the relationship between the structure and the catalytic performance of each catalyst. Based on the characterization results of Ce y Zr 1−y O 2 materials, the addition of Zr causes physical and chemical changes to the overall material. The inclusion of Zr into the structure of CeO 2 decreased the overall lattice parameter of the catalyst and increased the number of defect sites. The prepared catalysts were able to reach complete CO conversion (∼100%) at low temperature conditions (<200 °C), each showing varied reaction activity. The difference in CO oxidation activity was then analyzed and related to the structure, wherein Cu loading, surface oxygen vacancies, reduction–oxidation ability, CuO x –support interaction and oxygen mobility in the catalyst were the crucial descriptors.

36 MATERIALS SCIENCE↗

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗

Searching for axion-like particles through CMB birefringence from string-wall networks

Axion-like particles (ALPs) can form a network of cosmic strings and domain walls that survives after recombination and leads to anisotropic birefringence of the cosmic microwave background (CMB). In addition to studying cosmic strings, we clarify and emphasize how the formation of ALP-field domain walls impacts the cosmic birefringence signal; these observations provide a unique way of probing ALPs with masses in the range 3H 0 ≲ m a ≲ 3H cmb . Using measurements of CMB birefringence from several telescopes, we find no evidence for axion-defect-induced anisotropic birefringence of the CMB. We extract constraints on the model parameters that include the ALP mass ma, ALP-photon coupling Script A ∝ g aγγ f a , the domain wall number N dw , and parameters characterizing the abundance and size of defects in the string-wall network. Considering also recent evidence for isotropic CMB birefringence, we find it difficult to accommodate this with the non-detection of anisotropic birefringence under the assumption that the signal is generated by an ALP defect network.

79 ASTRONOMY AND ASTROPHYSICS↗

Identification and characterization of deep nitrogen acceptors in β-Ga 2 O 3 using defect spectroscopies

The ability to achieve highly resistive beta-phase gallium oxide (β-Ga 2 O 3 ) layers and substrates is critical for β-Ga 2 O 3 high voltage and RF devices. To date, the most common approach involves doping with iron (Fe), which generates a moderately deep acceptor-like defect state located at E C -0.8 eV in the β-Ga 2 O 3 bandgap. Recently, there has been growing interest in alternative acceptors, such as magnesium (Mg) and nitrogen (N), due to their predicted deeper energy levels, which could avoid inadvertent charge modulation during device operation. In this work, a systematic study that makes direct correlations between the introduction of N using ion implantation and the observation of a newly observed deep level at E C -2.9 eV detected by deep-level optical spectroscopy (DLOS) is presented. The concentration of this state displayed a monotonic dependence with N concentration over a range of implant conditions, as confirmed by secondary ion mass spectrometry (SIMS). With a near 1:1 match in absolute N and E C -2.9 eV trap concentrations from SIMS and DLOS, respectively, which also matched the measured removal of free electrons from capacitance-voltage studies, this indicates that N contributes a very efficiently incorporated compensating defect. Density functional theory calculations confirm the assignment of this state to be an N (0/-1) acceptor with a configuration of N occupying the oxygen site III [N O(III) ]. The near ideal efficiency for this state to compensate free electrons and its location toward the midgap region of the β-Ga 2 O 3 bandgap demonstrates the potential of N doping as a promising approach for producing semi-insulating β-Ga 2 O 3 .

36 MATERIALS SCIENCE↗

A cryogenic white light absorption spectroscopy setup with in situ gamma irradiation and thermo-optical annealing for optical fiber radiation-induced attenuation characterization

Silica optical fiber sensors offer a fast, distributed measurement solution in various cryogenic and radiation environments, such as magnets for fusion power. Under these conditions, light-absorbing point defects limit lifetime via radiation-induced attenuation (RIA). To support RIA kinetics prediction, we present an in situ, broadband absorption spectroscopy setup combining gamma irradiation with liquid nitrogen cooling. The apparatus enables continuous monitoring of narrowband RIA levels and the use of secondary optical annealing light sources, alongside broadband spectrum measurements to characterize RIA defects through spectrum decomposition. Initial results confirm the inevitable photobleaching effect of the probe light source, which must be accounted for. In addition, we report RIA kinetics during cycles of gamma irradiation at 77 K and isochronal thermal annealing steps from liquid nitrogen to room temperature, showcasing the setup’s ability to replicate real fiber operation scenarios. These instruments form an ideal platform to further study the kinetics of RIA coupled with thermal and optical annealing.

Absorption spectroscopy↗

Band gap and electronic structure of defects in the ternary nitride BP 3 N 6 : experiment and theory

Recent advances in methods to access nitride systems by a high-pressure high-temperature approach have made possible the one-step synthesis of mixed ternary non-metal nitrides. As a prerequisite to use in a practical device, it is important to understand important bulk electronic properties, such as the band gap, as well as characterizing the presence and effect of defects that are present. In this work, the novel ternary nitride BP 3 N 6 is studied using techniques sensitive to the partial electronic density of states, specifically X-ray absorption spectroscopy and X-ray emission spectroscopy. Complementary full-potential all-electron density functional theory (DFT) calculations allow important bulk electronic parameters, such as the band gap, to be elucidated. The band gap of BP 3 N 6 has been determined to be 3.9 ± 0.2 eV and 4.1 ± 0.4 eV at the B K- and N K-edges, respectively. This is close to a theoretical value of 4.3 eV predicted by the PBEsol exchange–correlation functional and considerably less than a value of 5.8 eV predicted by the modified Becke–Johnson exchange–correlation functional. X-Ray excited optical luminescence (XEOL) measurements are performed to interrogate the presence of point defects in this system. Together with DFT calculations, these measurements reveal the presence of nitrogen vacancies which lead to multiple mid-gap trap states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗

Quantifying dislocation-type defects in post irradiation examination via transfer learning

The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

36 MATERIALS SCIENCE↗

Critical differences in 3D atomic structure of individual ligand-protected nanocrystals in solution

Precise three-dimensional (3D) atomic structure determination of individual nanocrystals is a prerequisite for understanding and predicting their physical properties. Nanocrystals from the same synthesis batch display what are often presumed to be small but possibly important differences in size, lattice distortions, and defects, which can only be understood by structural characterization with high spatial 3D resolution. We solved the structures of individual colloidal platinum nanocrystals by developing atomic-resolution 3D liquid-cell electron microscopy to reveal critical intrinsic heterogeneity of ligand-protected platinum nanocrystals in solution, including structural degeneracies, lattice parameter deviations, internal defects, and strain. These differences in structure lead to substantial contributions to free energies, consequential enough that they must be considered in any discussion of fundamental nanocrystal properties or applications.

Kim, Byung Hyo↗

Extended defects in GaAs/GaAs 1-x Sb x /GaAs (001) heterostructures

The atomic-scale structure of extended defects in GaAs/GaAs 1-x Sb x /GaAs (001) heterostructures has been characterized using aberration-corrected scanning transmission electron microscopy. The defect located at the tensile-strained GaAs(cap)/GaAs 0.34 Sb 0.66 interface had no edge component in the projection plane and is identified as either a dissociated screw dislocation or a partial dislocation dipole. The associated intrinsic stacking fault is bounded by two 30° Shockley partial dislocations of opposite sign. Another defect, located at the compressively-strained GaAs 0.91 Sb 0.09 /GaAs(substrate) interface, is identified as a dissociated 90° dislocation. The associated intrinsic stacking fault is bounded by a 30° Shockley partial dislocation and a partial dislocation with a Burgers vector of either or , where a is the lattice constant. Unpaired atomic columns observed at the cores of the 30° Shockley partial dislocations indicate that both defects belong primarily to the glide set.

36 MATERIALS SCIENCE↗

High Entropy Alloys: Irradiation

High entropy alloys (HEAs) have been considered as structural materials for nuclear applications due to their promising mechanical properties and radiation resistance. For this purpose, irradiation-induced defect evolution and microstructure change have been characterized to evaluate the irradiation performance of different HEAs. This article reviews recent advances in understanding the irradiation response of HEAs, including the effect of disordered states on the defect energy landscape and defect evolution, irradiation-induced microstructure changes, void swelling, phase stability, mechanical properties under irradiation, as well as the He irradiation effects.

Zhao, Shijun↗

Archive of AGR-5/6/7 Particle Radiographs for Identification of Particles with Defective IPyC

As a part of fuel quality control characterization, 2D radiographs of large numbers of particles produced by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program’s AGR-5/6/7 irradiation were acquired. These radiographs were used for the identification of particles with excessive uranium dispersion from the kernel into the surrounding buffer layer caused by chlorine infiltration through a defective inner pyrolytic carbon (IPyC) layer during silicon carbide (SiC) deposition. Additional features of interest associated with fabrication anomalies were also catalogued. Raw radiography images, along with the noted defective IPyC defects found by analysis at Oak Ridge National Laboratory are reported herein.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

TEM Approaches for Microstructure-Informed Prediction of Mechanical Properties in Structural Alloys

Predicting the mechanical performance of structural alloys from their evolving microstructure remains a major challenge in materials science, particularly for nuclear structural materials, where irradiation-induced defects span multiple types and length scales and interact through complex mechanisms. The dispersed barrier hardening (DBH) [1] and Friedel–Kroupa–Hirsch (FKH) [2,3] models have been widely used to evaluate the hardening contributions of individual obstacles and to estimate tensile strength from quantified microstructures; however, when multiple size-dependent obstacles coexist and evolve, predicting temperature-dependent tensile strength becomes significantly more complex, and a fully consistent hardening model is still lacking. Transmission electron microscopy (TEM) plays a central role in refining hardening models and enabling predictive assessments of tensile strength evolution by providing quantitative characterization of dislocations, irradiation-induced defects (e.g., dislocation loops and cavities), precipitates, and grain structure (Fig. 1.). These experimentally measured defect densities are incorporated into physically based hardening models with size- and shape- dependent obstacle strengths [4], using root-sum-square superposition for obstacles of comparable strength and linear superposition for dissimilar ones [5]. In addition, recent advances in TEM [6-8], including high-resolution imaging, 4D-STEM strain mapping, EDS/EELS elemental analysis, and flash-polishing-based TEM specimen preparation and extraction-replica methods (Fig. 2), further improve the accuracy of microstructural quantification. By comparison with prior studies as well as our own results, we show that when TEM-derived microstructural information is carefully integrated with physically grounded hardening models, yield strength (or irradiation-induced hardening) measured at room temperature can be predicted with good quantitative agreement across multiple alloy classes. In-situ TEM combined with high-temperature mechanical testing represents an important next step for refining hardening models by directly probing dislocation–obstacle interactions across varying irradiation doses and temperatures [9]. Because the barrier strength factor (α) depends on both temperature and obstacle size, it should not be treated as a constant fitting parameter; rather, it must be explicitly evaluated to achieve physically meaningful predictions of mechanical behaviour at operating temperatures. This presentation therefore discusses why all strengthening contributions (e.g., Peierls stress, solid-solution strengthening, voids, bubbles, dislocation loops, dislocation lines, and grain boundaries) must be considered collectively, why appropriate superposition methods are essential when obstacles possess different barrier strength factors, how hardness measurements can be meaningfully related to tensile properties, and how TEM-derived microstructural information can be systematically incorporated into hardening models. More broadly, it outlines a pathway toward microstructure-informed prediction of mechanical properties and supports the goal of establishing science-based tools for evaluating structural materials in extreme environments [10].

Lin, Yan-Ru [ORNL] (ORCID:0000000339991473)↗

Origin of proton irradiation-induced deep acceptors in Al 0.70 Ga 0.30 N

Deep level defect introduction and carrier removal were characterized using steady-state photocapacitance (SSPC), deep level transient spectroscopy (DLTS) and lighted capacitance–voltage for proton irradiated n-type Al 0.70 Ga 0.30 N Schottky diodes grown by metal-organic vapor phase epitaxy on AlN-on-sapphire templates. SSPC observed deep levels in the as-grown diode with zero-phonon transition energies of 2.20, 2.65, 3.10, 3.40, and 4.65 eV relative to the conduction band minimum (E c ), and an additional deep level emerged at 1.20 eV with irradiation. Lighted capacitance–voltage measurements quantified the deep level concentration (N t ) of states detected by SSPC, and it was observed that N t increased with proton fluence only for the 1.2 and 4.65 eV levels. Carrier removal was much larger than the increase in N t of the 1.2 and 4.65 eV deep levels, suggesting that radiation-induced deep level compensators existed beyond what was detected with SSPC. DLTS detected additional, proton-induced deep acceptors at E c —0.55, 0.82, and 1.16 eV, the latter of which is likely the same 1.20 eV deep state observed by SSPC. The concentration of the E c —0.82 eV defect state was large enough to reconcile carrier removal with total deep level introduction. Comparing the E c —0.82 and 1.16 eV deep acceptor levels to previous experimental and theoretical reports suggests that their atomistic origins could be the nitrogen vacancy (V N ) and oxygen substituting on the nitrogen sub-lattice (O N ), respectively. This defect behavior contrasts starkly with GaN, where V N and O N are shallow donors, and demonstrates that the electronic properties of defects can evolve drastically within the AlGaN alloy system ranging from wide bandgap GaN to ultra-wide bandgap AlN.

Armstrong, Andrew Michael [Sandia National Laborat↗

Structure of V-defects in long wavelength GaN-based light emitting diodes

The V-defect is a naturally occurring inverted hexagonal pyramid structure that has been studied in GaN and InGaN growth since the 1990s. Strategic use of V-defects in pre-quantum well superlattices or equivalent preparation layers has enabled record breaking efficiencies for green, yellow, and red InGaN light emitting diodes (LEDs) utilizing lateral injection of holes through the semi-polar sidewalls of the V-defects. In this article, we use advanced characterization techniques such as scattering contrast transmission electron microscopy, high angle annular dark field scanning transmission electron microscopy, x-ray fluorescence maps, and atom probe tomography to study the active region compositions, V-defect formation, and V-defect structure in green and red LEDs grown on (0001) patterned sapphire and (111) Si substrates. We identify two distinct types of V-defects. The “large” V-defects are those that form in the pre-well superlattice and promote hole injection, usually nucleating on mixed (Burgers vector b = ±a±c⁠) character threading dislocations. In addition, “small” V-defects often form in the multi-quantum well region and are believed to be deleterious to high-efficiency LEDs by providing non-radiative pathways. The small V-defects are often associated with basal plane stacking faults or stacking fault boxes. Furthermore, we show through scattering contrast transmission electron microscopy that during V-defect filling, the threading dislocation, which runs up the center of the V-defect, will “bend” onto one of the six {10$\overline{1}$1} semi-polar planes. In conclusion, this result is essential to understanding non-radiative recombination in V-defect engineered LEDs.

42 ENGINEERING↗

Non-Equilibrium Effects in Quantum Magnets

While most often the state of a material will tend toward an equilibrium determined by its environment, there are many cases of scientific and technological interest where materials are manipulated to be or are found in non-equilibrium configurations. For example, data can be stored in hard drives by deliberately altering the magnetic orientation in a material to store information in non-equilibrium pattern. In this project, the main goals were studies of non-equilibrium properties of quantum magnets using neutron scattering as the primary experimental method. Neutron scattering allows characterization of magnetic correlation lengths sensitive to the presence of defects. It can also be used to distinguish equilibrium from non-equilibrium states via energy transfer rates. Typical bulk state magnetization relaxation times are too short to perform many neutron scattering measurements of interest. To enable the study of non-equilibrium conditions, materials with longer magnetic relaxation times were targeted. CoNb 2 O 6 was used in two experiments related to non-equilibrium physics. In the first, evidence for defects created via the Kibble-Zurek mechanism (KZM) was sought by quenching across a magnetic field-dependent phase transition. Somewhat unexpectedly, clear evidence for KZM-induced defects was absent. Additional measurements of CoNb 2 O 6 were made to better characterize its crystal field and other properties to provide a better theoretical understanding to enable more effective non-equilibrium physics measurements. In another project, LiHo 0.45 Y 0.55 F 4 was used to compare a quantum annealing protocol to a thermal annealing one since magnetic fields can be used to control the thermal fluctuations in LiHo 0.45 Y 0.55 F 4 . In addition, a new pulsed magnet power supply and new techniques were developed suitable for neutron scattering experimental environments to enable faster magnetic field changes for producing non-equilibrium conditions. The power supply developed for this project has wider technological applications in addition to faster magnetic field ramps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗