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At least 685 records · Page 38

Improving the short-wave infrared response of strained GeSn/Ge multiple quantum wells by rapid thermal annealing

In this work, the evolution of structural, optical and optoelectronic properties of coherently strained Ge 0.883 Sn 0.117 /Ge multiple quantum wells (MQWs) grown by molecular beam epitaxy under rapid thermal annealing (RTA) is systematically investigated. The MQW structure remains fully-strained state with RTA at 400 °C or below and disrupts at higher annealing temperatures due to Sn segregation and interdiffusion of Ge and Sn atoms. The GeSn well layers exhibit the strongest absorption in 2.0–2.4 μm after annealing at 400 °C and become transparent above 1.8 μm after RTA at 600 °C or beyond due to serve Sn segregation. Owing to improved crystal quality after RTA at 400 °C, the dark current of the fabricated metal-semiconductor-metal photodetector is effectively lowered by more than two times. Additionally, the responsivities at 1.55 and 2.0 μm are improved by 4.15 and 3.78 folds, respectively, compared to those of the as-grown sample. Here, the results can be an insightful guidance for the development of high-performance short-wave infrared photonic devices based on Sn-containing group-IV low-dimensional structures.

36 MATERIALS SCIENCE↗

Active and machine learning-based approaches to rapidly enhance microbial chemical production

In order to make renewable fuels and chemicals from microbes, new methods are required to engineer microbes more intelligently. Computational approaches, to engineer strains for enhanced chemical production typically rely on detailed mechanistic models (e.g., kinetic/stoichiometric models of metabolism)—requiring many experimental datasets for their parameterization—while experimental methods may require screening large mutant libraries to explore the design space for the few mutants with desired behaviors. To address these limitations, we developed an active and machine learning approach (ActiveOpt) to intelligently guide experiments to arrive at an optimal phenotype with minimal measured datasets. In this study, ActiveOpt was applied to two separate case studies to evaluate its potential to increase valine yields and neurosporene productivity in Escherichia coli. In both the cases, ActiveOpt identified the best performing strain in fewer experiments than the case studies used. This work demonstrates that machine and active learning approaches have the potential to greatly facilitate metabolic engineering efforts to rapidly achieve its objectives.

60 APPLIED LIFE SCIENCES↗

Stream lamination and rapid mixing in a microfluidic jet for X-ray spectroscopy studies

Microfluidic mixers offer new possibilities for the study of fast reaction kinetics down to the microsecond time scale, and methods such as soft X-ray absorption spectroscopy are powerful analysis techniques. These systems impose challenging constraints on mixing time scales, sample volume, detection region size and component materials. The current work presents a novel micromixer and jet device which aims to address these limitations. The system uses a so-called ‘theta’ mixer consisting of two sintered and fused glass capillaries. Sample and carrier fluids are injected separately into the inlets of the adjacent capillaries. At the downstream end, the two streams exit two micron-scale adjoining nozzles and form a single free-standing jet. The flow-rate difference between the two streams results in the rapid acceleration and lamination of the sample stream. This creates a small transverse dimension and induces diffusive mixing of the sample and carrier stream solutions within a time scale of 0.9 microseconds. The reaction occurs at or very near a free surface so that reactants and products are more directly accessible to interrogation using soft X-ray. We use a simple diffusion model and quantitative measurements of fluorescence quenching (of fluorescein with potassium iodide) to characterize the mixing dynamics across flow-rate ratios.

Huyke, Diego A. (ORCID:0000000283356613)↗

Rapid Droplet Sampling Interface for Low-Volume, High-Throughput Mass Spectrometry Analysis

Here, we present a rapid droplet sampling interface (RDSI) electrospray ionization mass spectrometry (ESI-MS) system as a high-throughput, low-volume, noncontact, and minimal-carryover approach for characterization of liquids. Liquid characterization was achieved by combining droplet ejection with an open-face microflow capillary with a 2.5 μL/min continuous flow of carrier solvent. Through this implementation, single 0.3 nL droplets containing the analyte effectively mix with 4–8 nL of carrier solvent and create a combined electrospray plume. The carrier solvent continuously cleaned the system, eliminating carryover. A sampling rate of 5 Hz was achieved for droplets containing 1 μM propranolol or 5 μM leu-enkephalin with each droplet fully baseline-resolved (138 ± 32 ms baseline-to-baseline). Using a SCIEX API4000 mass spectrometer, a lower limit of quantification (LLOQ) of propranolol was 15 nM, corresponding to 1.16 fg of propranolol in the droplet, and was linear across 3 orders of magnitude. Further, quantitation could be achieved by adding an isotopically labeled internal standard, as done in conventional ESI. Signal transients were faster than the acquisition speed of the mass spectrometer, resulting in artificially high reproducibility of 15–30% RSD droplet-to-droplet. Analyte–solvent mixing ratios could be controlled by adjusting droplet positioning along the open-face capillary with an optimal position about 0.4 mm from the tip end. The range of analyte coverage was exemplified by measures of peptides and drugs in methanol, water, and buffer solutions. In a comparison to the Open Port Sampling Interface (OPSI) implemented on the same system, the RDSI had 78× greater sensitivity, 6× greater throughput and used significantly less carrier solvent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid Screening of Single-Atom Catalyst Synthesis Conditions Using ToF-SIMS and Facet-Dependent Single-Crystal Substrates

Single-atom catalysts (SACs) offer superior catalytic performance compared to traditional nanoparticle catalysts but are challenging to develop because of the need for extensive optimization and specialized characterization techniques. Here, this study presents a rapid and versatile method for detecting synthesis conditions and elucidating deposition mechanisms of SACs on various substrates. By depositing active elements (Au, Cu, Ni and Rh) on facet-specific single-crystalline substrates (CeO 2 , TiO 2 , MgO and Al 2 O 3 ) and employing time-of-flight secondary ion mass spectroscopy (ToF-SIMS), we assessed facet-dependent deposition behaviors and identified optimal conditions for solution-based SAC synthesis. On CeO 2 and TiO 2 , we confirmed facet-dependent deposition, primarily influenced by oxygen vacancy density and photocatalytic activity, respectively. MgO exhibited the formation of metal oxide/hydroxide clusters for all active elements, and the degree of clustering for Cu and Ni was correlated with the facet hydrolysis susceptibility. Notably, Au and Rh deposition on MgO was facet-independent, attributed to the formation of hydroxide species in solution. Al 2 O 3 , due to its chemical stability and lack of surface defects, did not show active element deposition. This study not only provides a time and cost-efficient method for prescreening SAC synthesis conditions, but it also provides valuable insights into the various deposition mechanisms governing SAC formation on different substrates, paving the way for the rational design of tailored SACs for various catalytic applications.

ToF-SIMS↗

Robust Rapid Cellular Metabolite Sensing Using Benchtop NMR and SABRE-Hyperpolarized [1- 13 C]Pyruvate

Hyperpolarized NMR has emerged as a powerful analytical technique to significantly enhance targeted NMR signals, improving the sensitivity for investigations of unique chemical and biological dynamics. Here, we demonstrate the use of a hyperpolarization strategy based on Signal Amplification By Reversible Exchange (SABRE) to generate highly reproducible doses of a hyperpolarized [1- 13 C]pyruvate probe for benchtop characterization of yeast metabolism. This method allows rapid, scalable, and benchtop preparation of biocompatible hyperpolarized solutions suitable for live-cell experiments. We show that this production can be dove-tailed into a modular, compact workflow to characterize real-time metabolism in cell cultures, using Saccharomyces cerevisiae (Baker’s yeast) as a model organism. With high temporal resolution, we show that this method can resolve the conversion of hyperpolarized [1- 13 C]pyruvate into oxidative decarboxylation products CO 2 and bicarbonate. This conversion exhibits sustained and detectable metabolic activity for over 300 s after introduction of the agent to the cells. We model the metabolite kinetics to show decarboxylation activity and derive estimates of the pH over time from the CO 2 and bicarbonate (carbonic acid buffer system) equilibrium to probe changes in the cellular environment during active metabolism. These results highlight the utility of benchtop SABRE-hyperpolarized [1- 13 C]pyruvate as a scalable, specific probe for metabolic phenotyping of living cells using compact, low-cost instrumentation well-suited for future high-throughput applications across microbial engineering, drug response profiling, and dynamic metabolic screening.

fungi↗

Rapid Crystallization of Zeolites with Controllable Defects: Disentangling Fluoride Concentration and pH Using NH 4 F

Zeolite synthesis is typically conducted either under basic conditions or in neutral fluoride media using hydrofluoric acid (HF). While basic (OH − ) conditions generally result in faster zeolite crystallization, they can also increase the likelihood of framework defects and crystal intergrowths. In contrast, synthesis in neutral fluoride media tends to produce fewer defects because fluoride balances positive charges from structure-directing agents. However, this method often requires significantly longer crystallization times and involves the handling of dangerous HF. In the present study, we pursue the best of both synthesis conditions, rapid syntheses with controllable defect concentrations, by disentangling of mineralizing agent and chargebalancing agent using ammonium fluoride (NH 4 F) as an alternative to HF. We have investigated the use of NH 4 F in the syntheses of siliceous and aluminum-containing zeolite A (LTA, small pore), ZSM-5 (MFI, medium pore), and siliceous Beta(*BEA, large pore). The crystallization times of all four zeolites decreased substantially with an increasing NH 4 F concentration. Crystallization times were reduced from 24 to 4 h (Si-LTA), 96 to 36 h (Al-LTA), 240 to 6 h (ZSM-5), and 24 to 3 h (Si-*BEA). Additionally, increasing the NH 4 F concentration in the synthesis mixtures decreases the defect densities of siliceous zeolites. Raman spectroscopy, along with 29 Si MAS NMR, 19 F MAS NMR, 13 C MAS NMR, and fluorine elemental analysis of Si-LTA samples confirms that the reduction in charged defects (Si−O − ) is due to the higher incorporation of F − within the double four-membered ring (D4R) present in the LTA samples. We show that the accelerated crystallization is due to the role of F − in enhancing the silica mineralization rate (formation of silicon hexafluoride species) and stabilizing D4Rs under basic conditions. As a result, combining basic and fluoride-mediated synthesis could therefore be advantageous for faster zeolite production and improved control over structural properties for a wide variety of zeolite structures.

Anions↗

Rapid Identification of Synthetic Routes to Functional Metastable Phases Using X-ray Probed Laser Anneal Mapping (XPLAM) Time-Temperature Quench Maps

Many material systems have known or predicted functional phases that are metastable at standard temperature and pressure. While substantial advances have been made in the high-throughput and combinatorial synthesis of materials with a range of stoichiometries, investigation of thermal processing remains largely the domain of iterative uniform anneals or static gradients. Here we develop X-ray probed laser anneal mapping (XPLAM), a high throughput technique coupling spatially resolved X-ray diffraction with microsecond to millisecond laser gradient anneals to produce temperature–dwell–transformation (TDT) diagrams of the phase as a function of quench time and temperature. In addition to showing regimes where specific metastable phases form preferentially, TDT diagrams provide insight into the submillisecond kinetics of solid–solid phase transitions. This is a unique tool for mapping reaction pathways for metastable phases. As a first demonstration of XPLAM, we study Bi2O3, which has a rich set of polytypes, including the d-phase with an exceptionally high oxygen ion conductivity. We demonstrate the first annealing-driven synthesis of room temperature d-Bi2O3. We expect XPLAM to prove a powerful technique for rapid identification of synthetic routes to metastable phases and to generate the exhaustive data sets required for machine learning-guided exploration of materials processing.

36 MATERIALS SCIENCE↗

Rapid and Efficient Arsenic Removal by Iron Electrocoagulation Enabled with in Situ Generation of Hydrogen Peroxide

Millions of people are exposed to toxic levels of dissolved arsenic in groundwater used for drinking. Iron electrocoagulation (FeEC) has been demonstrated as an effective technology to remove arsenic at an affordable price. However, FeEC requires long operating times (~hours) to remove dissolved arsenic due to inherent kinetics limitations. Air cathode Assisted Iron Electrocoagulation (ACAIE) overcomes this limitation by cathodically generating H 2 O 2 in situ. In ACAIE operation, rapid oxidation of Fe(II) and complete oxidation and removal of As(III) are achieved. Here, we compare FeEC and ACAIE for removing As(III) from an initial concentration of 1464 μg/L, aiming for a final concentration of less than 4 μg/L. We demonstrate that at short electrolysis times (0.5 min), i.e., high charge dosage rates (1200 C/L/min), ACAIE consistently outperformed FeEC in bringing arsenic levels to less than WHO-MCL of 10 μg/L. Using XRD and XAS data, we conclusively show that poor arsenic removal in FeEC arises from incomplete As(III) oxidation, ineffective Fe(II) oxidation and the formation of Fe(II–III) (hydr)oxides at short electrolysis times (<20 min). Finally, we report successful ACAIE performance (retention time 19 s) in removing dissolved arsenic from contaminated groundwater in rural California.

54 ENVIRONMENTAL SCIENCES↗

Dominance of Particulate Mercury in Stream Transport and Rapid Watershed Recovery from Wildfires in Northern California, USA

Frequency and intensity of wildfires are expected to increase due to climate change, especially in areas with a long summer drought. Forests are a major sink for the global pollutant mercury (Hg), and fluvial transport of Hg from recently burned watersheds has not been widely investigated. Here, we examined two years of fluvial transport of Hg and its speciation (total Hg, methyl-Hg, particulate, and dissolved forms) under storm events and baseflow in two recently burned watersheds with different burned proportions and one nonburned reference watershed in the Coastal Ranges of northern California. We examined postfire storm-event transport of Hg and its methylated form (methyl-Hg), addressed the importance of the “initial runoff pulse” to postfire Hg fluvial transport and its predominant association with suspended solids, and elucidated potential sources of Hg exports from the burned landscapes using geochemical indicators, which suggested that ash materials were likely the significant sources of particulates in the first high-flow season postfire but not subsequently. The maximum total suspended solid and total Hg levels in the “first pulse” at the severely burned watershed were 442 and 46 times higher, respectively, than those at the reference watershed. Stream suspended solid and Hg levels declined substantially in the burned watersheds after just a few months of rainfall likely due to the rapid regrowth of vegetation commonly observed in postfire landscapes, implying that the wildfire effects on immediate Hg inputs from the burned landscape are at most transient in nature.

54 ENVIRONMENTAL SCIENCES↗

Benchmarking Concentration and Extraction Methods for Wastewater-Based Surveillance of Eight Human Respiratory Viruses: Implications for Rapid Application to Novel Pathogens

To provide early warning and support a rapid response to a novel virus through wastewater surveillance, it would be ideal to understand in advance which concentration and extraction methods are likely to be effective for dPCR-based methods, depending on virus characteristics. In this study, we spiked raw wastewater samples with eight human respiratory viruses and processed them with four methods that concentrate and/or extract nucleic acids from both liquid and solid fractions (Promega, Nanotrap, and InnovaPrep) or only the solid fraction of wastewater (Solids). Our findings provide encouraging evidence that all four methods combined with dPCR could detect an emerging virus in wastewater, although they differed in sensitivity. The pattern of recovery efficiency for adenoviruses, coronaviruses, and influenza A viruses was consistent across methods, with Promega producing higher median recovery efficiencies, while distinct patterns were observed for coxsackieviruses. We also normalized the concentration data with two endogenous fecal indicators, PMMoV and Carjivirus (formerly crAssphage). We found that normalization could reduce method-associated differences if the indicator exhibited a recovery pattern similar to that of the target virus. These findings can guide the selection of concentration and extraction methods for wastewater monitoring based on the properties of target viruses, thus enhancing pandemic preparedness.

Biological and medical sciences↗

Bench-Scale Apparatus for Rapid, Simultaneous, Comprehensive Vapor–Liquid Equilibrium and Kinetic Property Measurements to Advance CO 2 Capture Solvent Technology

We present here, the design, fabrication, and testing of a new "pressure, volume, temperature (PVT)" apparatus that enables rapid standardized testing for viscosity, vapor–liquid equilibria, and kinetics for water-lean carbon capture solvents. This unit is the first of its kind where equilibrium data are collected during operation as a PTx (pressure–temperature–composition) cell while kinetic data are collected simultaneously with an internal mini wetted-wall contactor (WWC) using controlled adjustments of CO 2 injections to allow for measurements of gas flux (in and out of the liquid). Additionally, in situ measurements of viscosity data are also continuously collected while a solvent is in circulation during gas absorption. This cell empowers comprehensive testing of critical CO 2 capture solvent properties in a single measurement, ensuring all data are collected at the same temperature, pressure, and CO 2 loading. This apparatus also expedites screening of materials since less than 50 mL of sample is needed as compared to 2–3 L needed to get similar data from a conventional WWC. In conclusion, we describe here the methodology of data collected on this new PVT cell, nicknamed “Gary” in honor of Professor Gary Rochelle, for multiple water-lean amine solvents, which we compare to data collected from conventional instrumentation for amine testing.

Zheng, Richard [STARS Technology Corporation, Rich↗

Hyperstoichiometric Uranium Dioxides: Rapid Synthesis and Irradiation-Induced Structural Changes

Uranium dioxide (UO 2 ), the primary fuel for commercial nuclear reactors, incorporates excess oxygen forming a series of hyperstoichiometric oxides. Thin layers of these oxides, such as UO 2.12 , form readily on the fuel surface and influence its properties, performance, and potentially geologic disposal. This work reports a rapid and straightforward combustion process in uranyl nitrate–glycine–water solutions to prepare UO 2.12 nanomaterials and thin films. We also report on the investigation of the structural changes induced in the material by irradiation. Despite the simple processing aspects, the combustion synthesis of UO 2.12 has a sophisticated chemical mechanism involving several exothermic steps. Raman spectroscopy and single-crystal X-ray diffraction (XRD) measurements reveal the formation of a complex compound containing the uranyl moiety, glycine, H 2 O, and NO 3 – groups in reactive solutions and dried combustion precursors. Combustion diagnostic methods, gas-phase mass spectroscopy, differential scanning calorimetry (DSC), and extracted activation energies from DSC measurements show that the rate-limiting step of the process is the reaction of ammonia with nitrogen oxides formed from the decomposition of glycine and uranyl nitrate, respectively. However, the exothermic decomposition of the complex compound determines the maximum temperature of the process. In situ transmission electron microscopy (TEM) imaging and electron diffraction measurements show that the decomposition of the complex compound directly produces UO 2 . The incorporation of oxygen at the cooling stage of the combustion process is responsible for the formation of UO 2.12 . Spin coating of the solutions and brief annealing at 670 K allow the deposition of uniform films of UO 2.12 with thicknesses up to 300 nm on an aluminum substrate. Irradiation of films with Ar 2+ ions (1.7 MeV energy, a fluence of up to 1 × 10 17 ions/cm 2 ) shows unusual defect-simulated grain growth and enhanced chemical mixing of UO 2.12 with the substrate due to the high uranium ion diffusion in films. As a result, the method described in this work allows the preparation of actinide oxide targets for fundamental nuclear science research and studies associated with stockpile stewardship.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation

Named entity recognition (NER) has been widely used in chemical text mining for the automatic identification and extraction of chemical entities. However, existing chemical NER systems primarily focus on scenarios with abundant training data, requiring significant human effort on annotations. This poses challenges for applications in the chemical field, such as catalysis, where many advancements have traditionally relied on trial-and-error investigations and incremental adjustment of variables. This hinders catalysis science and technology progress in addressing emerging energy and environmental crises. In this work, we propose a few-shot NER model that can quickly adapt to extract new types of chemical entities by using only a limited number of annotated examples. Our model employs a metric-learning approach to transfer entity similarity knowledge from high-resource chemical domains (with abundant annotations) to enable effective entity recognition in low-resource specialized domains (limited annotation). We validate the effectiveness of our model on a few-shot chemical NER benchmark built based on six existing chemical NER data sets. Experiments show that the proposed few-shot NER model can achieve reasonable performance with only 5 examples per entity type and shows consistent improvement as the number of examples increases. Furthermore, we demonstrate how the proposed model can be trained with large language model (LLM) annotated data, opening a new pathway for rapid adaptation of NER systems. Furthermore, our approach leverages the knowledge broadness of large language models for chemistry while distilling this knowledge into a lightweight model suitable for efficient and in-house use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations toward the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stabilizing NMC 811 Li-Ion Battery Cathode through a Rapid Coprecipitation Process

Improving the capacity of LiNi x Mn y Co 1-x-y O 2 (NMC) by increasing the Ni content results in materials with poor cycling performance and reduced thermal stability. These problems can be alleviated by creating concentration gradients in the materials, but this requires more expensive batch processing. Herein, a simple process is described that can create a coating that penetrates into the precursor particles, creating unique gradients in the precursor material. The coated material demonstrates improved cycling performance and thermal stability as compared to uncoated materials. Additionally, rapid heating to simulate a thermal runaway event while observing these materials with X-rays gives a deeper understanding of how the coating affects the decomposition process.

25 ENERGY STORAGE↗

Rapid Solidification Effects in Additively Manufactured Si and SiGe Compositions

SiGe alloys have a proven track record as robust high-temperature thermoelectric materials, powering NASA missions like SNAP-10A, LES-9, and Voyager 1 and 2. Enhancing thermoelectric efficiency hinges on minimizing thermal conductivity while preserving electrical conductivity. Rapid solidification via LPBF can generate microstructural features such as subgrain cellular boundaries and twinning, which may help reduce thermal conductivity while preserving semiconducting behavior. Here, this study investigates the potential of laser powder bed fusion (LPBF) additive manufacturing to fabricate nanostructured Si and SiGe thermoelectric materials. High cooling rates (10 5 to 10 7 K/s) rates inherent to the LPBF process are conducive to forming such nanostructures. Moreover, this fabrication technique could also be suitable for fabricating complex geometries needed to achieve improved device level performance. Process mapping of commercial Si powder with irregular morphology was first performed to understand the LPBF processing behavior of this semiconductor material. Subsequent studies included in-house synthesized B-doped (p-type) Si7 8 Ge 22 spherical powder that was produced via ultrasonic atomization. Scan strategies involved multiple laser exposures to mitigate solidification cracking: a high density of >98% was achieved, but solidification cracking could not be fully eliminated. Subsequently, a high electrical resistivity (i.e., low conductivity) was observed, but the measured Seebeck coefficient, ∼230 μV/K @ 500 °C, proved that good semiconductor material was being fabricated. A subgrain cellular structure (5–10 μm) was observed as defined by Ge segregation to the intercellular boundaries. The remelting strategies helped lower the cooling rates in processing SiGe, but this still resulted in high residual stresses, which induced a remarkably high density of twins (78–95%) to accommodate the deformation. This unique grain structure offers an avenue for phonon scattering and potential improvements in thermoelectric performance.

figure of merit↗

Plastic Scintillators via Rapid Photoinitiated Cationic Polymerization of Vinyltoluene

Cationic photopolymerization is applied for the rapid curing of a vinyltoluene and fluorophore solution into an efficient plastic scintillator. A hard solid is obtained via UV light-initiated polymerization of vinyltoluene, diaryliodonium salt, 9,9-dimethyl-2-phenylfluorene (PhF), and 9,9-dimethyl-2,7-distyrlfluorene (SFS) at ambient conditions with high conversion rates under a range of cationic photoinitiator concentrations, fluorophore concentrations, and light intensities. Insight into photopolymerization kinetics via photo differential scanning calorimetry (photoDSC) revealed photocuring time scales similar to those achieved in a commercial 3D printing resin. Furthermore, scintillator samples prepared cationically performed well compared to samples of equivalent compositions prepared by a lengthy thermally initiated radical polymerization.

36 MATERIALS SCIENCE↗