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At least 343 records · Page 19

All-optical control of charge-trapping defects in rare-earth doped oxides

Abstract Charge-trapping defects in crystalline solids play important roles in applications ranging from microelectronics, optical storage, sensing and quantum technologies. On one hand, depleting trapped charges in the host matrix reduces charge noise and enhances coherence of solid-state quantum emitters. On the other hand, stable charge traps can enable high-density optical storage systems. Here we report all-optical control of charge-trapping defects via optical charge trapping (OCT) spectroscopy of a rare-earth ion doped oxide (Y 2 O 3 ). Charge trapping is realized by low intensity optical excitation in the 200–375 nm range. Charge detrapping or depletion is carried out by optically stimulated luminescence (OSL) under 532 nm stimulation. Using a Pr-doped Y 2 O 3 polycrystalline ceramic host matrix, we observe charging pathways via the inter-band optical absorption of Y 2 O 3 and via the 4f-5d transitions of Pr 3+ . We demonstrate effective control of the density of trapped charges within the Y 2 O 3 matrix at ambient environment. These results point to a viable method for controlling the local charge environment in rare-earth doped crystals via all-optical means, and pave the way for further development of efficient optical storage technologies with ultrahigh storage capacity, as well as for the localized control of quantum coherence in rare-earth doped solids.

França, Leonardo V. S. [Pritzker School of Molecul↗

Determination of electron-hole pair creation energy in Cd 0.9 Zn 0.1 Te 0.98 Se 0.02 quaternary semiconductor for room-temperature gamma-ray detection

We report the first-time measurement of the electron-hole pair (ehp) creation energy (W ehp ) in novel Cd 0.9 Zn 0.1 Te 0.98 Se 0.02 (CZTS) quaternary semiconductor. CZTS in single crystalline form is poised to be the future of large-volume room-temperature gamma-ray detectors due to its excellent compositional homogeneity with highly reduced defects, high-Z (atomic number) constituents, wide bandgap (1.6 eV), and superior charge transport properties. Despite a great deal of study of the material and device properties since its inception, the W ehp in CZTS has not been measured experimentally. Accurate determination of W ehp is essential for calibration of the spectrometer and other theoretical calculations. In this study we have used an absolute calibration approach, which is based on an iterative approach that yields the Wehp as the best-fit parameter. Using a 241 Am alpha emitting radioisotope and a planar CZTS detector, the Wehp in CZTS was calculated to be 4.47 eV. The obtained value has been validated by accurately predicting the peak energy for gamma rays emitted by a 137 Cs source and read by a CZTS detector with different dimensions. The dependences of the calculated W ehp value on the detector dimensions, type of interaction, and effect of charge trapping are also discussed.

42 ENGINEERING↗

From Structure to Function: Zn/Mn-Modified Maghemite as an Advanced Nanoplatform for Magnetic Hyperthermia and Radionuclide Therapy

The development of nanoplatforms capable of efficient heat generation and stable radionuclide delivery is essential for effective bimodal cancer therapy. Here, in this study, binary (Fe–M) and ternary (Fe–M–M′) metal oxide nanoparticles were synthesized via a polyol method optimized to produce flower-like γ-Fe 2 O 3 (maghemite) structures, with M and M′ representing Zn and/or Mn. Comprehensive structural and magnetic characterization was conducted to explain the relationship between composition, defect structure, and hyperthermic performance. The analyses revealed that cation substitution induced an Fe-site vacancy, primarily at octahedral positions, leading to local structural distortions, as confirmed by powder X-ray diffraction and pair distribution function analysis. The optimized composition, with Zn/Mn/Fe = 0.040:0.182:1, exhibited the highest concentration of vacancies and structural disorder. These vacancies altered the bonding environment, enhancing magnetic interactions at tetrahedral sites while weakening those at the octahedral positions. The resulting multicore nanoflowers (20–63 nm; core size 13–18 nm) displayed strong heating performance, with intrinsic loss power ranging from 0.34 to 5.77 nHm 2 kg –1 . The optimized sample achieved a temperature increase of 30 °C within 2 min and a specific absorption rate of 369 W g –1 . This composition was further coated with citrate (CA) and successfully radiolabeled with 177 Lu, achieving a radiolabeling yield of 92.7% and excellent stability, thus forming a robust nanoplatform for combined magnetic hyperthermia and radionuclide therapy. Biological evaluation of the optimized S5 composition revealed selective cytotoxicity toward HeLa and LS174 cells, while toxicity was significantly lower to A549, A375, and normal MRC-5 cells. Citrate coating of S5 nanoparticles (S5@CA) drastically reduced their cytotoxicity across all tested cell lines (IC 50 > 200 μg mL –1 ), confirming their enhanced biocompatibility for therapeutic applications. In HeLa cells subjected to magnetic hyperthermia, the viability decreased to approximately 84% after 30 min and 61% after 60 min of treatment, demonstrating the sustained hyperthermic effect at a controlled working temperature of 48 °C. These results underscore the effectiveness of cation substitution and vacancy engineering in tailoring the functional properties of maghemite-based nanomaterials for advanced multimodal cancer therapies.

36 MATERIALS SCIENCE↗

Thermal conductivity measurement of U-Mo and U-Mo/Al interaction layers generated from in-pile irradiation using the suspended-bridge method

Here, this study presents the first measurement of the individual thermal conductivity of U-7wt.%Mo fuel particles and U-Mo/Al interaction layers (ILs) from in-pile irradiated dispersion fuel plates, using the suspended-bridge method. Nanorods of U-7wt.%Mo fuel and U-Mo/Al ILs were extracted by focused ion beam (FIB), and their microstructures were characterized with transmission electron microscopy (TEM). TEM revealed finely distributed nanobubbles in the U-7wt.%Mo matrix, along with an amorphous structure in the ILs. The thermal conductivity of in-pile irradiated U-7wt.%Mo was approximately 30% lower than that of the unirradiated material, ranging from 6.7 W/m·K at 300 K to 8.5 W/m·K at 380 K. The ILs exhibited even lower thermal conductivity, from 2.1 W/m·K at 300 K to 2.7 W/m·K at 380 K. These reductions, attributed to nanobubbles, fission products, and irradiation-induced point defects, were analyzed through a combination of microstructural characterization and literature-based transport models, which successfully reproduced the observed degradation trends.

42 - ENGINEERING↗

Tandem bulk oxygen diffusion and surface reactions in reducible metal oxides control redox cycle dynamics

The interplay between bulk oxygen diffusion and surface reactions in reducible metal oxides is key in heterogeneous catalysts, but direct measurements of oxygen mobility, transient kinetics, and in situ spectroscopies have been lacking. Here, we reveal complex dynamic behavior of ceria-zirconia by H 2 using transient kinetics via mass spectrometry and in situ Raman and near-ambient pressure x-ray photoelectron spectroscopies. Molecular dynamics simulations with a machine learning potential delineate competitive oxygen diffusion mechanisms, with an optimal mobility at intermediate reductions. We expose a compensation between vacancy availability and lattice distortion at intermediate to high reductions and Frenkel defects at low reductions, underscoring a potential deficiency of 16 O/ 18 O exchange experiments in deducing oxygen mobility. Vacancies in proximity require electron localization on Ce atoms further away. The continuous replenishment of surface oxygen results in a varying reduction rate, with H 2 dissociation being the rate-limiting step. Multiscale transient simulations, consistent with experiments, indicate catalysts of potentially spatially varying oxidation states. The approach is broadly applicable to reducible oxide materials.

36 MATERIALS SCIENCE↗

Mechanistic insights into rubidium ion adsorption at the quartz (101) surface from quantum chemical metadynamics

Ion sorption extent and mechanism depend in part on the mineral surface termination, which can be highly complex. Variations in surface functional groups, particularly with defect density and surface roughness, influence mineral reactivity towards solutes. In this work, we investigate the adsorption of a rubidium cation (Rb + ) at pristine and defect quartz (101) surface sites using well-tempered metadynamics, based on simulations with the quantum chemical density-functional tight-binding (DFTB) method. We compare the relative energetics of Rb + adsorption across selected sites for each surface, with nanosecond-level sampling, highlighting similarities between vicinal and geminal silanol sites. We find that the positive Rb + partial atomic charge can increase by as much as 0.5e as it approaches the surface, with implications for modulation of ion adsorption strength and extent at the quartz (101) surface with surface vacancies, silanol coverage, and charge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Alkali cation stabilization of defects in 2D MXenes at ambient and elevated temperatures

Transition metal carbides have been adopted in energy storage, conversion, and extreme environment applications. Advancements in their 2D counterparts, known as MXenes, enable the design of unique structures at the ~1 nm thickness scale. Alkali cations have been essential in MXenes manufacturing processing, storage, and applications, however, exact interactions of these cations with MXenes are not fully understood. In this study, using Ti 3 C 2 T x , Mo 2 TiC 2 T x , and Mo 2 Ti 2 C 3 T x MXenes, we present how transition metal vacancy sites are occupied by alkali cations, and their effect on MXene structure stabilization to control MXene’s phase transition. We examine this behavior using in situ high-temperature x-ray diffraction and scanning transmission electron microscopy, ex situ techniques such as atomic-layer resolution secondary ion mass spectrometry, and density functional theory simulations. In MXenes, this represents an advance in fundamentals of cation interactions on their 2D basal planes for MXenes stabilization and applications. Broadly, this study demonstrates a potential new tool for ideal phase-property relationships of ceramics at the atomic scale.

42 ENGINEERING↗

Precision Polishing of Ablator Capsules via in situ Process Monitoring and Machine Learning–Based Optimization

In inertial confinement fusion (ICF) experiments seeking output gains of unity and beyond, the quality of the ablator capsule is paramount for minimizing the hydrodynamic mix that quenches the central hot spot. Defects in the form of foreign particles or missing mass on the surface and within the wall of the capsule are primary offenders. High-density carbon capsules made for ICF experiments at the National Ignition Facility are precision polished to achieve surface smoothness on the order of a few nanometers as well as to minimize isolated defects in the form of pits. Given the critical role of this process, we are developing smart manufacturing techniques with the goal of elevating the efficiency of this process. Our approach is to use MEMS (micro-electromechanical systems)–based sensors to capture the fine vibration signals generated during the polishing process and combine them with synchronized visual feedback as needed. Beyond using these sensors for process monitoring, we use specific deep learning methods to analyze the data and extract correlations with both the process parameters and the final performance of the polishing run. Here, in this work, we describe the multiple fronts we have explored in this regard and the results we have gotten so far. This approach promises to have the potential to ultimately provide real-time feedback that can be used to ensure the progress of the run as well as a means for faster optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Czochralski Growth and Characterization of a Compositionally Complex Rare Earth Aluminum Garnet Scintillator: (Gd 1/4 Y 1/4 Tb 1/4 Lu 1/4 ) 3 Al 5 O 12 :Ce

Compositionally complex oxides have garnered increasing interest for their enhanced phase stability and tunable functional properties, yet their development as bulk single crystal scintillators remains limited. Herein, we report the Czochralski growth and characterization of (Gd 1/4 Y 1/4 Tb 1/4 Lu 1/4 ) 3 Al 5 O 12 :Ce (GYTLAG), a compositionally complex garnet incorporating four dodecahedrally coordinated principal rare earth elements. The garnet phase was confirmed by powder and single crystal X-ray diffraction, and macroscopic defects are described. X-ray absorption near-edge structure measurements confirm the 3+ oxidation state of all rare earths and support their occupation of the same crystallographic site; white line intensity variations correlate with the anticipated segregation behavior. Elemental segregation is quantified by SEM/EDS and ICP-OES, and a linear trend was established between the segregation coefficient and the difference between each rare earth’s ionic radius (r) and the average ionic radius (AIR) of the dodecahedral site. This trend offers a predictive framework for compositional control in future REAG crystals grown by the Czochralski method. Photoluminescence and radioluminescence measurements reveal both Ce 3+ and Tb 3+ emission. Scintillation pulses exhibit four-component decay with dominant ~230 µs and ~1.2 ms components, and the light yield is estimated to be up to 43,000 ph/MeV under 137Cs γ-ray excitation. GYTLAG also demonstrates a strong radioluminescence efficiency and 50% lower afterglow at 20 ms compared to a LuAG:Ce reference, underscoring its promise for scintillator applications.

Compositionally complex oxide, high entropy oxide,↗

Additive manufacturing for electrocaloric terpolymer thin films

Current heating, venting, and air conditioning (HVAC) systems have drawbacks of high energy consumption, large CO 2 emissions, and low efficiency. Electrocaloric (EC) cycles present an eco-friendly alternative by converting thermal energy to electrical energy. Defect-free thin films with uniform thickness are required to achieve optimal EC performance. A scalable thin film fabrication process is essential for integrating EC cycles into HVAC systems. This study introduces EC thin films prepared by electrospray (ES) processing, a manufacturing method that deposits EC polymer layer by layer using high voltage. The resulting films show superior thickness control, smoother surfaces, and improved thermal and electrical properties compared with solution casting. In addition, post-annealing at 120°C enhances the thermal and EC performance, with films achieving a temperature change (ΔT) of 3.6°C at 100 MV/m when tested near room temperature. With the potential for future scalability, the ES method offers a promising approach for fabricating EC thin films.

36 MATERIALS SCIENCE↗

Topological valley Hall polariton condensation

A photonic topological insulator features robust directional propagation and immunity to defect perturbations of the edge/surface state. Exciton-polaritons, that is, the hybrid quasiparticles of excitons and photons in semiconductor microcavities, have been proposed as a tunable nonlinear platform for emulating topological phenomena. However, mainly due to excitonic material limitations, experimental observations so far have not been able to enter the nonlinear condensation regime or only show localized condensation in one dimension. Here, in this study, we show a topological propagating edge state with polariton condensation at room temperature and without any external magnetic field. We overcome material limitations by using excitonic CsPbCl 3 halide perovskites with a valley Hall lattice design. The polariton lattice features a large bandgap of 18.8 meV and exhibits strong nonlinear polariton condensation with clear long-range spatial coherence across the critical pumping density. The geometric parameters and material composition of our nonlinear many-body photonic system platform can in principle be tailored to study topological phenomena of other interquasiparticle interactions. Polariton condensation of topological propagating edge states is demonstrated with halide perovskite microcavities.

42 ENGINEERING↗

Water content modulation enables selective ion transport in 2D MXene membranes

Separation membranes are critical for a range of processes, including but not limited to water desalination, chemical and fuel production, and recycling and recovery applications. Fundamentally, there are intrinsic trade-offs between permeability and selectivity. Local water organization and content can impact membrane structure (short- and long-range) in laminar transition metal carbide (MXene) membranes and impact selective ion permeation. Intercalation of chaotropic cesium (Cs + ) ions within the layers reduces the water content in the membrane and at the surface which cannot be found in the intercalation of other ions. Additionally, 3D imaging using focused ion beam scanning electron microscopy showed fewer defects in the Cs-MXene membrane, due to reduced local water content, leading to more efficient ion sieving. X-ray diffraction and density functional theory calculations on the nanochannel structure demonstrated that the chaotropic ion results in the smallest nanochannel size and induces a stronger resistance to water-induced nanochannel swelling. With a narrower nanochannel, the Cs-MXene membrane limits ion transport pathways, resulting in more selective transport of lithium over other metal cations, as evidenced in both experiment and molecular dynamics simulations. In conclusion, our findings highlight the potential for controlling the structural organization of 2D MXene membranes to enable on-demand transport of ions for diverse applications.

36 MATERIALS SCIENCE↗

InP- and GaAs-Based 0.6 eV GaInAs Devices for Thermophotovoltaics and Laser Power Conversion

Emerging applications such as thermal energy grid storage, waste heat recovery and portable power generation require efficient thermophotovoltaic (TPV) converters tuned to temperatures near 1000 Degrees Celsius or below. Metamorphic GaInAs with larger lattice constants than InP present a promising option for these needs. The ability to grow these devices on GaAs substrates instead of more expensive InP would enhance the scalability of these devices. In this talk, we present inverted metamorphic Ga0.3In0.7As photovoltaic converters with sub-0.60 eV bandgaps grown on InP and GaAs substrates. These devices are realized using InAsP or GaInP/InAsP compositionally graded buffers which exhibit threading dislocation densities of 1.3 +/- 0.6 x 106 cm-2 and 8.9 +/- 1.7 x 106 cm-2 on InP and GaAs, respectively. Despite this difference in defect density, the devices generate similar open-circuit voltages of 0.386 V and 0.383 V, respectively, under irradiance producing a short-circuit current density of -10 A/cm2, with bandgap-voltage offsets of 0.20 and 0.21 V. We estimate their thermophotovoltaic efficiency using these measurements coupled with broadband reflectance measurments. The InP-based cell is estimated to yield 1.09 W/cm2 at 1100 Degrees Celsius vs. 0.92 W/cm2 for the GaAs-based cell, with TPV efficiencies of 16.8 vs. 9.2%. Both devices are limited by sub-bandgap absorption, which we assess largely occurs in the graded buffers. We estimate that the 1100 Degrees Celsius thermophotovoltaic efficiencies would increase to 24.0% and 20.7% in structures with the graded buffer removed, if previously demonstrated reflectance is achieved. These devices also have application as laser power converters in the 2.0-2.3 um atmospheric window. We estimate efficiencies of 36.8% and 32.5% under 2.0 um monochromatic irradiance of 1.86 W/cm2 and 2.81 W/cm2, respectively.

ENGINEERING,MATERIALS SCIENCE,SOLAR ENERGY↗

A Pseudo‐Surfactant Chemical Permeation Enhancer to Treat Otitis Media via Sustained Transtympanic Delivery of Antibiotics

Abstract Chemical permeation enhancers (CPEs) represent a prevalent and safe strategy to enable noninvasive drug delivery across skin‐like biological barriers such as the tympanic membrane (TM). While most existing CPEs interact strongly with the lipid bilayers in the stratum corneum to create defects as diffusion paths, their interactions with the delivery system, such as polymers forming a hydrogel, can compromise gelation, formulation stability, and drug diffusion. To overcome this challenge, differing interactions between CPEs and the hydrogel system are explored, especially those with sodium dodecyl sulfate (SDS), an ionic surfactant and a common CPE, and those with methyl laurate (ML), a nonionic counterpart with a similar length alkyl chain. Notably, the use of ML effectively decouples permeation enhancement from gelation, enabling sustained delivery across TMs to treat acute otitis media (AOM), which is not possible with the use of SDS. Ciprofloxacin and ML are shown to form a pseudo‐surfactant that significantly boosts transtympanic permeation. The middle ear ciprofloxacin concentration is increased by 70‐fold in vivo in a chinchilla AOM model, yielding superior efficacy and biocompatibility than the previous highest‐performing formulation. Beyond improved efficacy and biocompatibility, this single‐CPE formulation significantly accelerates its progression toward clinical deployment.

Engineering↗

Quantum Anomalies in Condensed Matter

Quantum materials provide a fertile ground in which to test and realize unusual phenomena such as quantum anomalies predicted by quantum field theory. There are three important symmetries that are broken when classical field theory is moved into the quantum regime, the scale anomaly, the axial (chiral) anomaly, and the parity anomaly. Several potential device applications may be realized by the discovery of quantum anomalies in condensed matter, enabled by the new physics they embody, including ultra‐sensitive dark matter detectors, far infrared optical modulators, micro‐bolometric detectors, low‐dissipation ballistic transporters, terahertz‐based qubits, terahertz polarization state controls, passive magnetic field sensors, stable topological superconductors that host Majorana fermions, and qubits topologically protected against decoherence. In this perspective article, the definition of these quantum anomalies is laid out, how little is known in the context of condensed matter, and how quantum anomalies are predicted to manifest as anomalous electronic, thermal, and magnetic behavior in experiments on topological quantum materials, including Weyl and Dirac semimetals. Furthermore, the importance that mechanical strain and defects will play in modifying signatures of quantum anomalies is discussed.

36 MATERIALS SCIENCE↗

Quantitative analysis of leakage current in III-nitride micro-light-emitting diodes

In this study, the electrical characteristics under forward- and reverse-bias conditions of III-nitride blue and green micro-light-emitting diodes (μLEDs) are analyzed. A fitting model is proposed to determine the contributions of reverse leakage current and the effectiveness of sidewall treatments. Moreover, the forward-bias currents of the μLEDs are examined using the extracted ideality factor to examine the impacts of sidewall defects. The results show that sidewall treatments are highly effective for suppression of leakage currents. From the efficiency perspective, higher wall-plug efficiency (WPE) than external quantum efficiency (EQE) is observed when the operating voltage is lower than the photon voltage in both blue and green 20 × 20 μm 2 devices. This enhancement of the WPE over the EQE is due to the suppression of Shockley–Read–Hall (SRH) nonradiative recombination. These observations indicate that μLEDs with sidewall treatments not only improve optical performance but also further enhance the electrical performance of devices by suppressing the leakage current paths due to SRH nonradiative recombination processes.

42 ENGINEERING↗

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

42 ENGINEERING↗

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

36 MATERIALS SCIENCE↗