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At least 91 records · Page 5

Revealing local order via high energy EELS

Short range order (SRO) is critical in determining the performance of many important engineering materials. However, accurate characterization of SRO with high spatial resolution – which is needed for the study of individual nanoparticles and at material defects and interfaces – is often experimentally inaccessible. Here, we locally quantify SRO via scanning transmission electron microscopy with extended energy loss fine structure analysis. Specifically, we use novel instrumentation to perform electron energy loss spectroscopy out to 12 keV, accessing energies which are conventionally only possible using a synchrotron. Our data is of sufficient energy resolution and signal-to-noise ratio to perform quantitative extended fine structure analysis, which allows determination of local coordination environments. To showcase this technique, we investigate a multicomponent metallic glass nanolaminate and locally quantify the SRO with <10 nm spatial resolution; this measurement would have been impossible with conventional synchrotron or electron microscopy methods. Finally, we discuss the nature of SRO within the metallic glass phase, as well as the wider applicability of our approach for determining processing–SRO–property relationships in complex materials.

36 MATERIALS SCIENCE↗

Kinetic Growth of Multicomponent Microcompartment Shells

An important goal of systems and synthetic biology is to produce high value chemical species in large quantities. Microcompartments, which are protein nanoshells encapsulating catalytic enzyme cargo, could potentially function as tunable nanobioreactors inside and outside cells to generate these high value species. Modifying the morphology of microcompartments through genetic engineering of shell proteins is one viable strategy to tune cofactor and metabolite access to encapsulated enzymes. However, this is a difficult task without understanding how changing interactions between the many different types of shell proteins and enzymes affect microcompartment assembly and shape. Here, we use multiscale molecular dynamics and experimental data to describe assembly pathways available to microcompartments composed of multiple types of shell proteins with varied interactions. As the average interaction between the enzyme cargo and the multiple types of shell proteins is weakened, the shell assembly pathway transitions from (i) nucleating on the enzyme cargo to (ii) nucleating in the bulk and then binding the cargo as it grows to (iii) an empty shell. Atomistic simulations and experiments using the 1,2-propanediol utilization microcompartment system demonstrate that shell protein interactions are highly varied and consistent with our multicomponent, coarse-grained model. Furthermore, our results suggest that intrinsic bending angles control the size of these microcompartments. Altogether, our simulations and experiments provide guidance to control microcomparmtent size and assembly by modulating the interactions between shell proteins.

defects↗

Direct Visualization of Electric-Field-Induced Structural Dynamics in Monolayer Transition Metal Dichalcogenides

Layered transition metal dichalcogenides offer many attractive features for next-generation low-dimensional device geometries. Due to the practical and fabrication challenges related to in situ methods, the atomistic dynamics that give rise to realizable macroscopic device properties are often unclear. Here in this study, in situ transmission electron microscopy techniques are utilized in order to understand the structural dynamics at play, especially at interfaces and defects, in the prototypical film of monolayer MoS 2 under electrical bias. Through our sample fabrication process, we clearly identify the presence of mass transport in the presence of a lateral electric field. In particular, we observe that the voids present at grain boundaries combine to induce structural deformation. The electric field mediates a net vacancy flux from the grain boundary interior to the exposed surface edge sites that leaves molybdenum clusters in its wake. Following the initial biasing cycles, however, the mass flow is largely diminished and the resultant structure remains stable over repeated biasing. We believe insights from this work can help explain observations of nonuniform heating and preferential oxidation at grain boundary sites in these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-classical crystallization in soft and organic materials

Classical nucleation and crystal growth theories describe how nuclei form, become stable after reaching a critical size and then enlarge through monomer attachment. More than two decades ago, non-classical pathways have been proposed for various types of (bio)molecules and materials, which can substantially alter the crystallization kinetics and outcomes. Direct observation of non-classical crystallization of inorganic nanomaterials, including metastable structure-mediated and particle attachment-based pathways that usually occur on the nanoscale, was enabled by in situ liquid-phase electron microscopy. However, it was not until recently that the crystallization dynamics of beam-sensitive soft materials were directly imaged with sufficient spatial resolution, and a level of microstructural understanding of defects and interfaces emerged. This article provides a high-level review of the non-classical crystallization pathways discovered in soft and organic materials and a forward-looking guide for future research. We first analyse how the characteristics of soft materials affect their crystallization pathways and kinetics. We then identify technical approaches to studying the crystallization trajectories of soft materials and discuss strategies to properly select and apply them to different systems. Breakthroughs made in understanding the crystallization of small organic molecules, (bio)macromolecules, colloids and reticular framework materials are examined. Lastly, we provide an outlook on the challenges in elucidating soft material crystallization pathways and the opportunities for assisting the design and synthesis of new materials and structures.

36 MATERIALS SCIENCE↗

Enhanced positive and negative exchange bias in FeF 2 /Ni with dusted interfaces

An enhanced exchange bias was found in FeF 2 /Ni interfaces by inserting dusting of Pd and Cu atoms. We have used an ultrathin wedge to investigate systematically the effect of a discontinuous nonmagnetic spacer between the antiferromagnetic and ferromagnetic layers. Negative and positive exchange biases are symmetric and maximized for less than two angstroms of the nonmagnetic layer. Moreover, the dusting reduces the field cooling threshold to switch between the negative and the positive exchange bias. This finding demonstrates that nonmagnetic dusted layers can improve the interfacial exchange energy density in antiferromagnetic/ferromagnetic heterostructures and modify the bulk antiferromagnetic domain structure. Other dusting materials such as Ag, Ti, V, and SiO 2 showed no enhancement in FeF 2 /Ni bilayers, which indicates the atomic sensitivity of this effect.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distinguishing bulk and surface recombination in CdTe thin films and solar cells using time-resolved terahertz and photoluminescence spectroscopies

Understanding the nature of recombination and its dependence on defects and interfaces is essential for engineering materials and contacts for higher open circuit voltage (V oc ) and power conversion efficiency in photovoltaic (PV) devices. Time-resolved photoluminescence (TRPL) has conventionally been used to evaluate recombination, but carrier redistribution often dominates the response at short times. In this work, we report on the quantification of carrier dynamics and recombination mechanisms by complementary use of both time-resolved terahertz spectroscopy (TRTS) and TRPL combined with numerical modeling of the continuity equations and Poisson’s equation. We have demonstrated this approach using CdTe thin films. A thin film stack with CdTe fabricated by vapor transport deposition and treated with CdCl 2 exhibited a bulk lifetime of 1.7 ± 0.1 ns, negligible CdTe/CdS interface recombination velocity, and back surface recombination velocity of 6.3 ± 1.3 x10 4 cm/s. In contrast, a film stack without CdCl 2 treatment had a bulk lifetime of only 68 ± 12 ps and a higher interface recombination velocity of 4 ± 2 x10 8 cm/s. By determining the locus and mechanisms of performance-limiting recombination, we can accelerate the development of thin-film PVs with higher V oc and efficiency. While the method has been demonstrated here using CdTe, it is also applicable to perovskites, Cu(InGa)Se 2 , Cu2ZnSn(S,Se) 4, and emerging technologies.

14 SOLAR ENERGY↗

Hubbard-corrected oxide formation enthalpies without adjustable parameters

A density functional theory (DFT) approach to computing transition metal oxide heat of formation without adjustable parameters is presented. Different degrees of d-electron localization in oxides are treated within the DFT+U approach with site-dependent, first-principles Hubbard U-parameters obtained from linear response theory, and delocalized states in the metallic phases are treated without Hubbard corrections. Comparison of relative stabilities of these differently treated phases is enabled by a local d-electron density matrix-dependent model, which was found by genetic programming against experimental reference formation enthalpies. This mathematically simple model does not explicitly depend on the Hubbard-corrected ionic species and is shown to reproduce the heats of formation of the Mott insulators Ca 2 RuO 4 and Y 2 Ru 2 O 7 within ~3% of experimental results, where the experimental training data did not contain Ru oxides. This newly developed method thus absolves from the need for element-specific corrections fitted to experiments in existing Hubbard-corrected approaches to the prediction of reaction energies of transition metal oxides and metals. The absence of fitting parameters opens up here the possibility to predict relative thermodynamic stabilities and reaction energies involving d-states of varying degree of localization at transition metal oxide interfaces and defects, where site-dependent U-parameters will be particularly important and devising a fitting scheme against experimental data with predictive power would be exceedingly difficult.

transition metal oxides↗

Enhanced superconducting qubit performance through ammonium fluoride etch

The performance of superconducting qubits is often limited by dissipation and two-level systems (TLS) losses. The dominant sources of these losses are believed to originate from amorphous materials and defects at interfaces and surfaces, likely as a result of fabrication processes or ambient exposure. Here, we explore a novel wet chemical surface treatment at the Josephson junction-substrate and the substrate-air interfaces by replacing a buffered oxide etch (BOE) cleaning process with one that uses hydrofluoric acid followed by aqueous ammonium fluoride. We show that the ammonium fluoride etch process results in a statistically significant improvement in median $\text{T}_1$ by $\sim22\%$ (p = 0.002), and a reduction in the number of strongly-coupled TLS in the tunable frequency range. Microwave resonator measurements on samples treated with the ammonium fluoride etch after niobium deposition and etching also show $\sim33\%$ lower TLS-induced loss tangent compared to the BOE treated samples. As the chemical treatment primarily modifies the Josephson junction-substrate interface and substrate-air interface, we perform targeted chemical and structural characterizations to examine materials differences at these interfaces and identify multiple microscopic changes that could contribute to decreased TLS losses.

36 MATERIALS SCIENCE↗

Atom Probe Tomography for the Observation of Hydrogen in Materials: A Review

Atom probe tomography (APT) is an emerging microscopy technique that has high sensitivity for hydrogen with sub-nanometre-scale spatial resolution, which makes it a unique method to investigate the atomic-scale distribution of hydrogen at interfaces and defects in materials. This article introduces the basics of APT-based hydrogen analysis, particularly the challenge of distinguishing a hydrogen background signal in APT by using hydrogen isotopes, along with strategies to yield high-quality analysis. This article also reviews several important findings on hydrogen distribution in a range of materials, including both structural alloys and functional materials, enabled by using APT. Limitations and future opportunities for hydrogen analysis by APT are also discussed.

42 ENGINEERING↗

Theory of oblique-field magnetoresistance from spin centers in three-terminal spintronic devices

Here, we present a general stochastic Liouville theory of electrical transport across a barrier between two conductors that occurs via sequential hopping through a single defect's spin-0 to spin-1/2 transition. We find magnetoconductances similar to Hanle features (pseudo Hanle features) that originate from Pauli blocking without spin accumulation, and also predict that evolution of the defect's spin modifies the conventional Hanle response, producing an inverted Hanle signal from spin center evolution. We propose studies in oblique magnetic fields that would unambiguously determine if a magnetoconductance results from spin-center assisted transport.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Laser melting modes in metal powder bed fusion additive manufacturing

In laser powder bed fusion additive manufacturing of metals, extreme thermal conditions create many highly dynamic physical phenomena such as vaporization and recoil, Marangoni convection, and protrusion and keyhole instability. Collectively however, the full set of phenomena is too complicated for practical applications and, in reality, the melting modes are used as a guideline for printing. With increasing local material temperature beyond the boiling point, the mode can change from conduction to keyhole. These mode designations ignore laser-matter interaction details but in many cases are adequate to determine the approximate microstructures and hence the properties of the build. To date, no consistent, common, and coherent definitions have been agreed upon because of historic limitations in melt pool and vapor depression morphology measurements. Here, we distinguish process-based definitions of different melting modes from those based on postmortem evidence. The latter are mainly derived from the transverse cross-sections of the fusion zone, whereas the former come directly from time-resolved x-ray imaging of melt pool and vapor depression morphologies. These process-based definitions are more strict and physically sound, and they offer new guidelines for laser additive manufacturing practices and create new research directions. Further, we highlight the significance of the keyhole, which substantially enhances the laser energy absorption by the melt pool. Recent studies strongly suggest that stable-keyhole laser melting enables efficient, sustainable, and robust additive manufacturing. The realization of this scenario demands the development of multiphysics models, signal translations from morphology to other feasible signals, and in-process metrology across platforms and scales.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Interfacial oxide and other species in trimethylaluminum-pretreated atomic layer deposition-Al 2 O 3 /GaN characterized by sputter-assisted ToF-SIMS

Deposition techniques, like atomic layer deposition (ALD), are used to form high-quality dielectrics for GaN-based metal–oxide–semiconductor (MOS) gate structures due to the lack of a reliable thermal oxide in GaN. Moreover, interfacial GaO x from pre-existing native oxides is thought to adversely impact channel carrier dynamics and induce undesired threshold voltage shifts in GaN-based MOS gate structures. Exposure of the GaN surface to the trimethylaluminum (TMA) precursor prior to standard alumina ALD decreases the native oxide layer on GaN, but the extent of chemical modification has not been well studied in the context of interface composition in a MOS gate structure. Herein, we compare annealed 55 nm Al 2 O 3 dielectric films on GaN grown using either a water-first ALD process or a process including sequential pulses of TMA immediately before the initiation of Al 2 O 3 ALD. Time-of-Flight Secondary Ion Mass Spectrometry measures differences in the interfacial GaO x content between each ALD film. Here, it also detects surface contaminant species like Si, F, S, and C. Furthermore, we report the formation of an AlN species at the Al 2 O 3 /GaN interface, which is more prominent for the film grown using the TMA pre-pulse step. In general, this work demonstrates that the TMA pre-pulse step is an effective strategy for cleaning substrate surfaces prior to ALD.

Atomic layer deposition↗

Lead-chelating hole-transport layers for efficient and stable perovskite minimodules

The defective bottom interfaces of perovskites and hole-transport layers (HTLs) limit the performance of p-i-n structure perovskite solar cells. We report that the addition of lead chelation molecules into HTLs can strongly interact with lead(II) ion (Pb 2+ ), resulting in a reduced amorphous region in perovskites near HTLs and a passivated perovskite bottom surface. Here, the minimodule with an aperture area of 26.9 square centimeters has a power conversion efficiency (PCE) of 21.8% (stabilized at 21.1%) that is certified by the National Renewable Energy Laboratory (NREL), which corresponds to a minimal small-cell efficiency of 24.6% (stabilized 24.1%) throughout the module area. Small-area cells and large-area minimodules with lead chelation molecules in HTLs had a light soaking stability of 3010 and 2130 hours, respectively, at an efficiency loss of 10% from the initial value under 1-sun illumination and open-circuit voltage conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Amorphous boron nitride: synthesis, properties and device application

Amorphous boron nitride (a-BN) exhibits remarkable electrical, optical, and chemical properties, alongside robust mechanical stability, making it a compelling material for advanced applications in nanoelectronics and photonics. This review comprehensively examines the unique characteristics of a-BN, emphasizing its electrical and optical attributes, state-of-the-art synthesis techniques, and device applications. Key advancements in low-temperature growth methods for a-BN are highlighted, offering insights into their potential for integration into scalable, CMOS-compatible platforms. Additionally, the review discusses the emerging role of a-BN as a dielectric material in electronic and photonic devices, serving as substrates, encapsulation layers, and gate insulators. Finally, perspectives on future challenges, including defect control, interface engineering, and scalability, are presented, providing a roadmap for realizing the full potential of a-BN in next-generation device technologies.

36 MATERIALS SCIENCE↗

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗

Advancing PV material performance using nanoscale opto-electrical characterization

The purpose of this program was to improve the efficiency of photovoltaics by characterizing their optoelectronic properties at the nanoscale. We investigated Copper Indium Gallium Selenide (CIGS) materials produced by Dow. We modified an atomic force microscope (AFM) to work with a highly controlled environment under controlled illumination at the probe to study the main power conversion efficiency determining parameters for photovoltaics of open circuit voltage, short circuit current, carrier lifetime and diffusion length, and band alignment at interfaces and defects with sub 10nm spatial resolution of their device materials.

14 SOLAR ENERGY↗

High-Quality Factor Microwave Resonators using Rhenium

Coplanar waveguide resonators are a perfect tool to evaluate the losses induced by defects and interfaces in superconducting devices. Even if niobium is the most used superconductor for resonators and qubits, its native oxide at the metal-air (MA) interface limits the device results. Tantalum has recently significantly improved qubit performances due to a thinner and less disordered oxide layer compared to Nb. To further improve the MA interface, we used rhenium, a superconducting material with 1.7 K critical temperature resistant to oxidation: it forms an oxide layer thinner than 1 nm. In this study, we will present a thorough investigation of rhenium CPW resonator measurements with internal quality factors at the single photon level exceeding 2 million. The devices have been fabricated on a sapphire substrate while the processing parameters have been varying and optimized. The measurements have been performed as a function of power and temperature to disentangle different sources of losses, such as two-level systems (TLS) and quasi-particles. A peculiar TLS temperature dependence has been measured and analyzed. In this work, we also vary the participation ratio of the devices to extract the losses introduced by the involved interfaces with higher fidelity and precision. We carried on a deep material characterization effort to link the results to the differences in the fabrication steps, and we will present material characterization measurements performed via AFM, ToF-SIMS, XPS, and TEM.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optimization of Functionally Graded Materials Using Additive Manufacturing: An Integrated Experimental and Computational Approach (Abbreviated Final Report)

Many advanced technologies, such as next-generation energy systems, aerospace vehicles, and defense platforms, require materials that can withstand extreme environments, including high temperatures, corrosion, and radiation, while remaining strong and lightweight. Traditionally, joining different materials to achieve these properties introduces weak, failure-prone interfaces and defects that limit performance. Our research aimed to overcome this challenge by using additive manufacturing, specifically directed energy deposition, to create functionally graded materials—components with smooth transitions between different metals. This approach eliminates sharp boundaries and allows for tailored material properties throughout a part.

36 MATERIALS SCIENCE↗