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At least 1,495 records · Page 83

Superconductivity in a topological lattice model with strong repulsion

The highly tunable nature of synthetic quantum materials-both in the solid-state and cold atom contexts-invites examining which microscopic ingredients aid in the realization of correlated phases of matter such as superconductors. Recent experimental advances in moiré materials suggest that unifying the features of the Fermi-Hubbard model and quantum Hall systems creates a fertile ground for the emergence of such phases. Here, we introduce the "double Hofstadter"model, a minimal 2D lattice model that incorporates exactly these features: Time-reversal symmetry, band topology, and strong repulsive interactions. By using infinite cylinder density matrix renormalization group methods (cylinder iDMRG), we investigate the ground state phase diagram of this model. We find that it hosts an interaction-induced quantum spin Hall insulator and demonstrate that weakly hole-doping this state gives rise to a superconductor at a finite circumference, with indications that this behavior persists on larger cylinders. Further, at the aforementioned circumference, the superconducting phase is surprisingly robust to perturbations including additional repulsive interactions in the pairing channel. By developing a technique to probe the superconducting gap function in iDMRG, we phenomenologically characterize the superconductor. Namely, we demonstrate that it is formed from the weak pairing of holes atop the quantum spin Hall insulator. Furthermore, we determine the pairing symmetry of the superconductor, finding it to be p-wave-reminiscent of the unconventional superconductivity reported in experiments on twisted bilayer graphene (TBG). Motivated by this, we elucidate structural similarities and differences between our model and those of TBG in its chiral limit. Finally, to provide a more direct experimental realization, we detail an implementation of our Hamiltonian in a system of cold fermionic alkaline-earth atoms in an optical lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Properties and Potential of Two (ni,pt)ti Alloys for Use as High-temperature Actuator Materials

The microstructure, transformation temperatures, basic tensile properties, shape memory behavior, and work output for two (Ni,Ti)Pt high-temperature shape memory alloys have been characterized. One was a Ni30Pt20Ti50 alloy (referred to as 20Pt) with transformation temperatures above 230 C and the other was a Ni20Pt30Ti50 alloy (30Pt) with transformation temperatures about 530 C. Both materials displayed shape memory behavior and were capable of 100% (no-load) strain recovery for strain levels up to their fracture limit (3-4%) when deformed at room temperature. For the 20Pt alloy, the tensile strength, modulus, and ductility dramatically increased when the material was tested just about the austenite finish (A(sub f)) temperature. For the 30Pt alloy, a similar change in yield behavior at temperatures above the A(sub f) was not observed. In this case the strength of the austentite phase was at best comparable and generally much weaker than the martensite phase. A ductility minimum was also observed just below the A(sub s) temperature in this alloy. As a result of these differences in tensile behavior, the two alloys performed completely different when thermally cycled under constant load. The 20Pt alloy behaved similar to conventional binary NiTi alloys with work output due to the martensite-to-austenite transformation initially increasing with applied stress. The maximum work output measured in the 20Pt alloy was nearly 9 J/cu cm and was limited by the tensile ductility of the material. In contrast, the martensite-to-austenite transformation in the 30Pt alloy was not capable of performing work against any bias load. The reason for this behavior was traced back to its basic mechanical properties, where the yield strength of the austenite phase was similar to or lower than that of the martensite phase, depending on temperature. Hence, the recovery or transformation strain for the 30Pt alloy under load was essentially zero, resulting in zero work output.

Noebe, Ronald↗

Charges on a suspended silicon nitride membrane under a high-energy electron beam

Thin silicon nitride (SiN x ) membranes are widely used in gas and liquid phase transmission electron microscopy (TEM) and as phase plates to enhance imaging contrast. SiN x contains trap sites for both positive and negative charges, which can be manipulated by high-energy electron irradiation, external potential biasing, or light exposure. Charge accumulation on the membrane can significantly affect in situ TEM processes, including chemical and electrochemical reactions, nanoparticle dynamics, and catalytic activity, or introduce unwanted phase shifts when used as a phase plate. Here, in this study, charge accumulation on suspended SiN x membranes was investigated using off-axis electron holography combined with model-free charge analysis, supported by custom finite element analysis (FEA) simulations. An average residual positive charge density of approximately 2.8 × 10 −4 C m −2 was measured. Localized and stable regions of both positive and negative charges were identified on the membrane. The global positive and localized positive/negative charges give rise to strong electric fields and electroosmotic slip velocities at the membrane surface, which are sufficient to induce non-Brownian particle behavior and directional fluid flow, offering a physical explanation for previously observed anomalies in particle dynamics, nucleation, and growth during gas and liquid phase TEM experiments. These results provide a benchmark for understanding charge behavior at SiNx interfaces in gas and liquid phase TEM. Furthermore, the FEA simulations establish a framework for future investigations into charge distribution, electrostatic potentials, and electrical double layers at solid–liquid interfaces, particularly in complex geometries and chemically dynamic environments.

Suspended silicon↗

Entanglement transitions from restricted Boltzmann machines

The search for novel entangled phases of matter has lead to the recent discovery of a new class of “en- tanglement transitions,” exemplified by random tensor networks and monitored quantum circuits. Most known examples can be understood as some classical ordering transitions in an underlying statistical mechanics model, where entanglement maps onto the free-energy cost of inserting a domain wall. In this paper we study the possibility of entanglement transitions driven by physics beyond such statistical mechanics mappings. Motivated by recent applications of neural-network-inspired variational Ansätze, we investigate under what conditions on the variational parameters these Ansätze can capture an entanglement transition. We study the entanglement scaling of short-range restricted Boltzmann machine (RBM) quantum states with random phases. For uncorrelated random phases, we analytically demonstrate the absence of an entanglement transition and reveal subtle finite-size effects in finite-size numerical simulations. Introducing phases with correlations decaying as 1/r α in real space, we observe three regions with a different scaling of entanglement entropy depending on the exponent α. We study the nature of the transition between these regions, finding numerical evidence for critical behavior. Furthermore, our work establishes the presence of long-range correlated phases in RBM-based wave functions as a required ingredient for entanglement transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Magnetic structure and properties of the compositionally complex perovskite (Y 0.2 La 0.2 Pr 0.2 Nd 0.2 Tb 0.2 )MnO 3

Large configurational disorder in compositionally complex ceramics can lead to unique functional properties that deviate from traditional rules of alloy mixing. In recent years, compositionally complex oxides (CCOs) have shown intriguing magnetic behavior including long-range order, enhanced magnetic exchange couplings, and mixed phase magnetic structures. This work focuses on how large local spin disorder affects magnetic ordering in a CCO. Specifically, we investigated the A-site alloyed perovskite, (Y 0.2 La 0.2 Pr 0.2 Nd 0.2 Tb 0.2 )MnO 3 , or (5A)MnO 3 , using a combination of bulk magnetometry, synchrotron X-ray diffraction, and temperature-dependent neutron diffraction. The five A-site ions have an average spin and ionic radius nearly equal to that of Nd 3+ ions, which minimizes structural distortions and allows for an understanding of the local spin disorder effects through a direct comparison with NdMnO 3 . Our magnetometry data show that (5A)MnO 3 exhibits two distinct phase transitions associated with the A-site and B-site sublattices, as seen in NdMnO 3 , as well as the presence of domain pinning and exchange bias at low temperature, suggesting a mixed phase magnetic ground state, as seen in other magnetic CCOs. Neutron powder diffraction shows clear long-range antiferromagnetic ordering below 67 K and refines to a Pn'ma' magnetic structure at low temperature, in excellent agreement with the well-studied behavior of NdMnO 3 . The two most notable differences in (5A)MnO 3 magnetism apparent from our data are a slight suppression of the B-site ordering temperature, which is explained by a smaller Mn–O–Mn bond angle in (5A)MnO 3 than NdMnO 3 , and the presence of a magnetic susceptibility transition above the B-site ordering, which could indicate the formation of a cluster glass but requires further study. Finally, this work demonstrates a general method of isolated investigation of size and spin disorder in CCOs and motivates future work using local structure probes to better understand the effects of nanoscale clustering and local spin disorder in magnetic CCOs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Visualizing strange metallic correlations in the two-dimensional Fermi-Hubbard model with artificial intelligence

Strongly correlated phases of matter are often described in terms of straightforward electronic patterns. This has so far been the basis for studying the Fermi-Hubbard model realized with ultracold atoms. Here, we show that artificial intelligence (AI) can provide an unbiased alternative to this paradigm for phases with subtle, or even unknown, patterns. Long- and short-range spin correlations spontaneously emerge in filters of a convolutional neural network trained on snapshots of single atomic species. In the less well-understood strange metallic phase of the model, we find that a more complex network trained on snapshots of local moments produces an effective order parameter for the non-Fermi-liquid behavior. We report our technique can be employed to characterize correlations unique to other phases with no obvious order parameters or signatures in projective measurements, and has implications for science discovery through AI beyond strongly correlated systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Martensitic transformation in superlattices of two non-transforming metals

A number of studies have shown that the coherent integration of a second non-transforming phase in martensitic materials results in unprecedented thermo-mechanical properties. We demonstrate the possibility of martensitic transformation by epitaxially combining two non-transforming materials, Mg (hexagonal closed packed) and MgLi (body centered cubic). Density functional theory calculations predict that MgLi/Mg superlattices undergo a transformation crystallographically equivalent to MgSc alloys and can be expected to result in finite temperature shape memory behavior. We predict the zero-temperature energy of the martensite phase to be 9.3 meV/atom lower than austenite for a 50–50 at. % MgLi/Mg nanolaminate, which is expected to result in a martensitic transformation temperature of approximately 150 K. This energy difference can be tuned between 4.9 and 18.1 meV/atom by varying the fraction of the pure Mg phase in the superlattice, potentially enabling the transformation from cryogenic to room and higher temperatures. While Li diffusion might limit the applications of the systems proposed, this work opens the door to a new approach to create martensitic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Effect of Metal Composition on Fe-Ni Partition Behavior between Olivine and FeNi-Metal, FeNi-Carbide, FeNi-Sulfide at Elevated Pressure

Metal-olivine Fe-Ni exchange distribution coefficients were determined at 1500 C over the pressure range of 1 to 9 GPa for solid and liquid alloy compositions. The metal alloy composition was varied with respect to the Fe/Ni ratio and the amount of dissolved carbon and sulfur. The Fe/Ni ratio of the metal phase exercises an important control on the abundance of Ni in the olivine. The Ni abundance in the olivine decreases as the Fe/Ni ratio of the coexisting metal increases. The presence of carbon (up to approx. 3.5 wt.%) and sulfur (up to approx. 7.5 wt.%) in solution in the liquid Fe-Ni-metal phase has a minor effect on the partitioning of Fe and Ni between metal and olivine phases. No pressure dependence of the Fe-Ni-metal-olivine exchange behavior in carbon- and sulfur-free and carbon- and sulfur-containing systems was found within the investigated pressure range. To match the Ni abundance in terrestrial mantle olivine, assuming an equilibrium metal-olivine distribution, a sub-chondritic Fe/Ni-metal ratio that is a factor of 17 to 27 lower than the Fe/Ni ratios in estimated Earth core compositions would be required, implying higher Fe concentrations in the core forming metal phase. A simple metal-olivine equilibrium distribution does not seem to be feasible to explain the Ni abundances in the Earth's mantle. An equilibrium between metal and olivine does not exercise a control on the problem of Ni overabundance in the Earth's mantle. The experimental results do not contradict the presence of a magma ocean at the time of terrestrial core formation, if olivine was present in only minor amounts at the time of metal segregation.

Holzheid, Astrid↗

LDRD 22A1059-068FP Tailoring the Properties of Multi-Phase Materials Through the Use of Correlative Microscopy and Machine Learning - Poster

High strength alloys with good ductility, hardness, and toughness are needed to meet stringent design requirements for extreme environments. One complication in this pursuit is the evidence that metals rarely exhibit both high strength and good fracture toughness as the underlying mechanisms work in opposition. An exception to this behavior is found in multiphase alloys that form complex microstructures of mixed phases with variable grain sizes and shapes that provide increased fracture toughness by the arrangement of their constituent elements. We propose to explore this phenomenon using state-of-the-art machine learning (ML) techniques in a new and novel manner to identify and correlate the critical microstructural features in a Titanium-10Vanadium-2Iron-3Aluminum (Ti-10V-2Fe-3Al) alloy that is reported to exhibit high strength and fracture toughness. Additionally, we will employ multiple, complementary characterization techniques such as optical microscopy, electron backscatter diffraction (EBSD), energy dispersive spectroscopy (EDS) and scanning electron microscopy to provide multi-layer, quantitative ground truth measures of the microstructures. This data will be used to train a Convolutional Neural Network (CNN) in a semi-supervised environment to identify key microstructural features such as ? platelet dimensions and locations and ?/? phase boundaries and correlate those features with the strength and toughness. Here the ? and ? nomenclature refers to hexagonal close pack (hcp) and body center cubic (bcc) crystal structures, respectively. Previous work has focused on popular alloys and typically used one characterization technique. This research is focused on a promising titanium alloy, uses multiple complimentary characterization tools to provide precise microstructural information and correlates to improved fracture toughness. The resulting ML tool can be trained for additional microstructural features, different alloy(s), and or target mechanical properties.

36 MATERIALS SCIENCE↗

Native Defects Hybridization and Electronic Transport in Cu 2 Se–CuGaSe 2 Hierarchical Composites

Engineering the energy distribution of electronic defects in semiconductors can afford the coexistence of degenerate and nondegenerate transport behavior. By leveraging native defects in Cu 2 Se and CuGaSe 2 phases, the tunability of the concentration and energy distribution of active electronic defects in hierarchical (1-x)Cu 2 Se-(x)CuGaSe 2 composites is demonstrated. This study found that the electrical conductivity of various composites decreases with rising temperature indicating degenerate semiconducting behavior, whereas the carrier density increases with temperature, which is consistent with non-degenerate semiconductivity. Remarkably, this study found that while the carrier density and electrical conductivity drop with the increasing CuGaSe 2 content for samples with x ≤ 0.45 is consistent with an increase in the activation energy of “active” electronic defects, the sudden increase by 140% in the electrical conductivity and by 109% in the carrier density for near equimolar composition suggests the formation of a large density of electronic defects with lower activation energy. This unusual behavior is understood within the context of the hybridization of coexisting native electronic defects to form degenerate hybrid acceptor states with lower activation energy. The reported unique electronic transport can be leveraged for the development of more versatile electronic and optoelectronic devices with superior performance.

36 MATERIALS SCIENCE↗

Microgravity Fluid Separation Physics: Experimental and Analytical Results

Effective, low power, two-phase separation systems are vital for the cost-effective study and utilization of two-phase flow systems and flow physics of two-phase flows. The study of microgravity flows have the potential to reveal significant insight into the controlling mechanisms for the behavior of flows in both normal and reduced gravity environments. The microgravity environment results in a reduction in gravity induced buoyancy forces acting on the discrete phases. Thus, surface tension, viscous, and inertial forces exert an increased influence on the behavior of the flow as demonstrated by the axisymmetric flow patterns. Several space technology and operations groups have studied the flow behavior in reduced gravity since gas-liquid flows are encountered in several systems such as cabin humidity control, wastewater treatment, thermal management, and Rankine power systems.

Shoemaker, J. Michael↗

Mechanism of the wurtzite to rocksalt phase transformation in cadmium sulfide single crystals shock compressed along the 𝑐-axis to elastic impact stresses of ∼ 5 GPa

Cadmium sulfide (CdS), which exhibits a wurzite (WZ) to rocksalt (RS) phase transformation at elevated stresses, is an ideal system to address the role of deformation on phase transformation mechanisms and kinetics. CdS has been shown to have very different elastic-inelastic behavior for shock propagation along the WZ 𝑐- and 𝑎-axes, and also exhibits significant differences in the time scale for the phase transformation when shocked along these different axes. As an important first step in examining the role of deformation in shock-induced phase transformations, here we present in situ, time-resolved x-ray diffraction (XRD) measurements in single-event, shock wave experiments on CdS single crystals shocked along the WZ 𝑐-axis to elastic impact stresses near or above ∼ 5 GPa, where a marked increase in the kinetics of this transformation has been reported. The XRD measurements are compared with forward diffraction simulations to evaluate different proposed phase transformation mechanisms and are shown to be consistent with a shearing mechanism that results in the RS [001] direction being aligned with the original WZ 𝑐-axis and the RS [110] direction being aligned with the original WZ 𝑎-axis. In order to reproduce all observed RS diffraction spots the forward diffraction simulations required three different RS crystalline domains, each with a [110] direction aligned with one of the three original WZ 𝑎-axes, and a significant mosaicity, particularly about the RS [001] direction (the direction of shock propagation). In conclusion, this large mosaicity is likely due to variations in the possible shearing mechanisms that connect the WZ and RS structures, which can create crystallites with up to ∼ ±10° of relative rotations about the RS [001] direction, as well as further rotation of these crystallites as they grow, merge, and coalesce.

Crystal structure↗

Lithium's low-temperature phase transitions: Insights into quantum lattice dynamics and superconductivity

The large lattice dynamics of lithium, driven by its low atomic mass, results in energetically similar structures and significant isotope effects under pressure, posing challenges to current theoretical models. Above 20 GPa and at low temperatures, lithium's electronic properties deviate from simple metallic behavior, with superconductivity emerging in a complex, pressure-dependent manner, alongside an unusual isotope effect. The structural phases of 7 Li reported under these conditions are inconsistent across studies, and the structures of 6 Li remain unexamined. These gaps limit our understanding of the effects of pressure on lithium's electronic properties and the role of quantum lattice effects on its structural behavior under pressure. Here, we integrate experimental and theoretical approaches to investigate the low-temperature structural phase boundaries in lithium isotopes. We map the structural phase diagram of 7 Li from 5 to 55 GPa and 15–75 K, identifying the sequence fcc → ℎ⁡R⁢1 → cI16. A pronounced isotope effect is observed, with 6 Li shifting the fcc → ℎ⁡R⁢1 phase boundary to lower pressures at 15 K. Density functional theory calculations further clarify how these structural changes affect superconducting properties, particularly emphasizing the role of the fcc → ℎ⁡R⁢1 transition in lithium's superconductivity. Furthermore, our findings offer insights into the unique behavior of lithium isotopes under pressure.

36 MATERIALS SCIENCE↗

Bulk Spray and Individual Plume Characterization of LPG and Iso-Octane Sprays at Engine-Like Conditions

This study presents experimental and numerical examination of directly injected (DI) propane and iso-octane, surrogates for liquified petroleum gas (LPG) and gasoline, respectively, at various engine like conditions with the overall objective to establish the baseline with regards to fuel delivery required for future high efficiency DI-LPG fueled heavy-duty engines. Sprays for both iso-octane and propane were characterized and the results from the optical diagnostic techniques including high-speed Schlieren and planar Mie scattering imaging were applied to differentiate the liquid-phase regions and the bulk spray phenomenon from single plume behaviors. The experimental results, coupled with high-fidelity internal nozzle-flow simulations were then used to define best practices in CFD Lagrangian spray models. Optical imaging revealed that unlike iso-octane, propane’s spray propagation was fed by its flash boiling, spray collapse, and high degree of vaporization, resulting in a direct proportionality of propane’s penetration length to temperature. These unique features of propane and its variation from iso-octane’s spray pattern, contributed to its classification as an unconventional spray. Appropriate corrections to the injection and breakup models were developed to reproduce the under-expanded jet dynamics and to mimic the flash boiling-driven spray development observed with propane sprays. The simulation results were found to be sensitive to cone and inclusion angles of the blob injector. The current work represents a first assessment of the capability of the commonly available models for engine-spray simulations and highlights the fact that, despite the reasonable agreement obtained in the fuel vapor morphology, the representation of the liquid phase lacks accuracy and requires further model development.

02 PETROLEUM↗

Computational modeling of grain boundary segregation: A review

Nearly all metals, alloys, ceramics, and their associated composites are polycrystalline in nature, with grain boundaries that separate well-defined crystalline regions that influence materials properties. In all but the most pure elemental systems, intentional solutes or impurities are present and can segregate to, or less commonly away from, the grain boundaries, in turn influencing boundary behavior, their stability, and associated materials properties. In some cases, grain-boundary segregation can also trigger “phase-like” structural transitions that dramatically alter the essential nature of the boundary. With the development of advanced electron microscopy techniques, researchers can directly observe grain-boundary structures and segregation with atomic precision. Despite such spatial resolution, the underlying mechanisms governing grain-boundary segregation remain difficult to characterize. As a result, computational modeling techniques such as density functional theory, molecular dynamics, mesoscale phase-field, continuum defect theory, and others are important complementary tools to experimental observations for studying grain-boundary segregation behavior. In conclusion, these computational methods offer the ability to explore the underlying formation mechanisms of grain-boundary segregation, elucidate complex segregation behavior, and provide insights into solutions to effectively controlling microstructure.

36 MATERIALS SCIENCE↗

Comparative verification of hydro-mechanical fracture behavior: Task G of international research project DECOVALEX–2023

Numerical simulations become a necessity when experimental approaches cannot cover the required physical and time scale of interest. One of such area is a simulation of long-term host rock behaviors for nuclear waste disposal and simulation tools involved in the assessment must go through rigorous validation tests. The DECOVALEX project (Development of COupled models and their VAlidation against EXperiments) is dedicated to this purpose by international participants. This work is part of the ongoing phase DECOVALEX–2023 (D–2023, Task G) particularly aiming to simulate fracture behaviors under various conditions. Here, in this study, we cross-verified a variety of numerical methods including continuous and discontinuous approaches against four benchmark exercises with emphasis on numerical accuracy and parameterization of the various numerical approaches. The systematic inter-comparisons of test cases highlight advantages and disadvantages of the different numerical models. Numerical details on discretization effects (e.g. mesh density and orientation) and domain size were investigated in detail for practical applications. It became evident that meticulous attention to mesh resolution and domain size is imperative for achieving accurate numerical simulations, even for static cracks. Moreover, when comparing numerical methods to closed-form solutions for static cracks, all models successfully reproduced the maximum crack opening but encountered challenges near the crack tips. Finally, the paper discusses how to convert between and therefore compare parameters of various numerical approaches. Our benchmark studies reveal that each model necessitates a distinct number of parameters, even in simple scenarios like static crack aperture benchmarks. It is generally more practical to employ fewer parameters to mitigate model over-parameterization and enhance experimental feasibility.

58 GEOSCIENCES↗

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗

Tailoring Charge Transport and Magnetism in Complex Half-Heusler/Full-Heusler Nanocomposites (Final Report)

This project exploits (1) the facile co-crystallization of the half-Heusler (HH) and full-Heusler (FH) structures, (2) the high coherency and stability of the HH/FH interfaces, and (3) the solid-state inter-conversion between HH and FH structures through local atomic diffusion, to investigate, for selected compositions of the HH and FH phases, the effect of size, dimensionality, dispersion and volume fraction of FH nanostructures on the electronic, phonon and magnetic behavior of the resulting HH/FH nanocomposites. Our goal is to identify and control key material and growth parameters governing phase formation, microstructural evolution, and to understand the mechanism by which these changes of the internal structure modify the material’s performance. To elucidate the mechanism by which the FH nanostructures regulate electronic charge transport and induce ferromagnetism within non-magnetic and magnetic semiconducting HH matrices, suitable series of HH/0D-FH and HH/2D-FH nanocomposites will be fabricated using synthesis conditions suggested by theoretical calculations of the formation energy and stability of various FH phases (varying M) in HH matrices with known chemical composition. The structure of the HH/FH interfaces (size, chemical composition, volume fraction and dispersion) will be investigated along with the evaluation of the electronic (carrier density, mobility, thermopower, electrical conductivity, effective mass), thermal and magnetic (susceptibility, magnetization etc.) properties of the resulting HH/FH nanocomposites.

36 MATERIALS SCIENCE↗