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At least 73 records · Page 4

Flash electropolishing of BCC Fe and Fe-based alloys

The preparation of transmission electron microscopy (TEM) samples is a critical step in the characterization of materials, and the focused ion beam (FIB) technique is a commonly used method. However, a significant limitation of this technique is the FIB-induced damages on the foil surfaces, which can obscure the real features of interest, particularly in radiation effects studies. To overcome this limitation, this study presents a detailed description of the flash electropolishing technique, which can be used to remove the FIB damage from samples. The flash electropolishing technique has been successfully applied to a range of materials, including Fe, Fe-based model alloys, commercial Fe-Cr alloys, and advanced Fe-Cr alloys, both in their as-received and ion-irradiated states. Furthermore, the parameters used for Fe-Cr model alloys can be adjusted for commercial and advanced alloys with minimal modifications. Further, the study also examined the effects of electropolishing variables, such as perchloric acid concentration, electropolishing temperature, Cr concentration, and voltage. Qualitatively, a general trend and scoping test strategy is explored in our experiments. Overall, the flash electropolishing technique offers a promising solution to the challenges posed by FIB-induced damages in the preparation of TEM samples.

36 MATERIALS SCIENCE↗

A low-cost, fluorine-free electrolyte for improved sodium batteries

Sodium batteries are an attractive alternative to lithium-ion technologies due to sodium’s lower cost and natural abundance—over 1,000 times greater than lithium, comprising approximately 2.4% of the Earth’s crust. However, most current electrolytes rely on fluorine-containing components, which raise economic and environmental concerns. This study explores fluorine-free, borate-based electrolytes that offer improved cycling stability and significant cost and sustainability benefits. We demonstrate stable sodium metal stripping and plating on aluminum foil, enabling anode-free cell configurations with over 50% capacity retention after 700 cycles. Spectroscopic and electrochemical analyses reveal the effects of solvents and salt composition on solvation, ionic conductivity, and oxidative stability. In full-cell configurations, the fluorine-free electrolyte maintains more than 98% capacity retention after 400 cycles. Furthermore, these findings represent a critical step toward the development of cost-effective, environmentally friendly, and high-performance sodium battery systems suitable for future electrification.

anode-free sodium batteries↗

B 2 H 6 splitting on catalytic surfaces and role of BH 3 towards hydrogen spillover

A fundamental understanding of the spillover mechanism is an open and challenging problem and plays an important role in catalysis. In particular, bond-exchange spillover mechanism is considered to be effective for reversible storage and release of hydrogen at near ambient conditions. For this, three critical steps are needed: finding the right support (acceptor), the right catalyst to split H 2 , and ensuring that once H 2 is split, the H atoms can migrate on the surface with the help of secondary catalysts and eventually hydrogenate the entire material. In this paper we address these challenges using density functional theory. Here we show that BH 3 , a secondary catalyst, can be produced by symmetrically splitting its stable precursor, B 2 H 6 , on doped metal-free surfaces such as graphene and h-BN as well as on MOF5. In addition, to reduce computational cost, we develop structural descriptor and predictive model equation to effectively screen potential BH 3 binding sites. Symmetrical splitting of B 2 H 6 on different types of materials can address the hydrogen spillover challenge, making efficient storage of hydrogen possible.

08 HYDROGEN↗

Volumetric analysis and mesh generation of real and artificial microstructural geometries

Producing a viable finite element mesh of realistic microstructural structural geometry is a critical step in analyzing the thermo-mechanical behavior of complex multi-material composites. Advancements in imaging technology such as micro computed tomography have allowed modelers to access high resolution mesoscale geometries for direct numerical simulation. However, converting from voxel based 3D images to usable finite element meshes has been challenging. A robust method including algorithms and software scripts for generating finite element meshes from 3D imaged microstructures is presented in this paper. It includes a routine for inserting cohesive elements around material interfaces to enable modeling of interface properties including delamination and damage. The algorithms and procedures presented in this method leverage currently available software packages for processing surface based geometry into volume based meshes. In addition to converting real geometry from physical imaging systems, algorithms for producing numerically generated and statistically equivalent microstructural geometry are also included. These artificial microstructures can be a valuable resource for modelers when physical specimens do not exist or are limited in quantity: Method establishes a workflow from voxel data to viable finite element mesh including interface information, and Includes a method for synthetic geometry generation based on metrics from real microstructures.

36 MATERIALS SCIENCE↗

Digital pixel test structures implemented in a 65 nm CMOS process

The ALICE ITS3 (Inner Tracking System 3) upgrade project and the CERN EP R&D on monolithic pixel sensors are investigating the feasibility of the Tower Partners Semiconductor Co. 65 nm process for use in the next generation of vertex detectors. The ITS3 aims to employ wafer-scale Monolithic Active Pixel Sensors thinned down to 20–40 µm and bent to form truly cylindrical half barrels. Among the first critical steps towards the realisation of this detector is to validate the sensor technology through extensive characterisation both in the laboratory and with in-beam measurements. The Digital Pixel Test Structure (DPTS) is one of the prototypes produced in the first sensor submission in this technology and has undergone a systematic measurement campaign whose details are presented in this article. The results confirm the goals of detection efficiency and non-ionising and ionising radiation hardness up to the expected levels for ALICE ITS3 and also demonstrate operation at + 20 °C and a detection efficiency of 99% for a DPTS irradiated with a dose of 10 15 1 MeV n eq cm -2 . Furthermore, spatial, timing and energy resolutions were measured at various settings and irradiation levels.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Investigations on the multiple-sector hard-copper X-band accelerating structures

The development of advanced, high gradient accelerating structures is one of the leading activity of the particle accelerator community. In the technological research of new construction methods for these devices, high-power testing is a critical step for the verification of their viability. Recent experiments showed that accelerating cavities made out of hard copper, fabricated without high-temperature processes, can achieve better performance as compared with soft copper ones. Recently, we have built cavities using Tungsten Inert Gas welding and the high-power experiments confirmed that this joining process is a robust and low-cost alternative to brazing or diffusion bonding. This is a good solution for high-gradient operation, with a gradient of about 150 MV/m in X-band, at a breakdown rate of 10 -3 /pulse/meter using a shaped RF pulse with a 150 ns flat part. We continue the design, construction and high power tests of three-cells standing-wave X-band accelerating cavities fabricated with a split-open geometry, made of hard copper and vacuum-sealed by welding. Our aim is the fabrication of accelerating structures made out of hard copper alloys by using innovative cost-effective technologies. Moreover, our method of multiple-sector structures opens the way to new technological approaches and design methods, for example providing the possibility of placing dampers of the parasitic higher-order modes. Such structures with dampers allow for acceleration of multi-bunch beams, both in standing and in travelling-wave accelerating modality. Here, this paper describes the design of two cavities made of multiple sectors that were fabricated at the Italian Institute for Nuclear Physics in Frascati, Italy (INFN-LNF), assembled by means of clamping and then joined with the Tungsten Inert Gas welding in order to preserve the hardness of the metal. These are three-cell standing-wave X-band accelerating cavities, to be operated in the π-mode. We report the low-power RF tests of the first one, made of two halves, and the RF design of the second one, made of four quadrants. Both structures were built for high-gradient tests at SLAC National Accelerator Laboratory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Better together: Protein partnerships for lineage-specific oil accumulation

Plant-derived oils are a major agricultural product that exist in both ubiquitous forms such as common vegetable oils and in specialized forms such as castor oil and coconut oil. These specialized oils are the result of lineage-specific metabolic pathways that create oils rich in unusual fatty acids. Considerable progress has been made toward understanding the enzymes that mediate fatty acid biosynthesis, triacylglycerol assembly, and oil storage. However, efforts to translate this knowledge into renewable bioproducts via engineered oil-producing plants and algae have had limited success. Here, we review recent evidence that protein–protein interactions in each of the three major phases of oil formation appear to have profound effects on specialized oil accumulation. We suggest that furthering our knowledge of the noncatalytic attributes of enzymes and other proteins involved in oil formation will be a critical step toward creating renewable bioproducts derived from high performing, engineered oilseeds.

59 BASIC BIOLOGICAL SCIENCES↗

An overview of data tools for representing and managing building information and performance data

Building information modeling (BIM) has been widely adopted for representing and exchanging building data across disciplines during building design and construction. However, BIM's use in the building operation phase is limited. With the increasing deployment of low-cost sensors and meters, as well as affordable digital storage and computing technologies, growing volumes of data have been collected from buildings, their energy services systems, and occupants. Such data are crucial to help decision makers understand what, how, and when energy is consumed in buildings—a critical step to improving building performance for energy efficiency, demand flexibility, and resilience. However, practical analyses and use of the collected data are very limited due to various reasons, including poor data quality, ad-hoc representation of data, and lack of data science skills. To unlock value from building data, there is a strong need for a toolchain to curate and represent building information and performance data in common standardized terminologies and schemas, to enable interoperability between tools and applications. This study selected and reviewed 24 data tools based on common use cases of data across the building life cycle, from design to construction, commissioning, operation, and retrofits. The selected data tools are grouped into three categories: (1) data dictionary or terminology, (2) data ontology and schemas, and (3) data platforms. The data are grouped into ten typologies covering most types of data collected in buildings. This study resulted in five main findings: (1) most data representation tools can represent their intended data typologies well, such as Green Button for smart meter data and Brick schema for metadata of sensors in buildings and HVAC systems, but none of the tools cover all ten types of data; (2) there is a need for data schemas to represent the basis of design data and metadata of occupant data; (3) standard terminologies such as those defined in BEDES are only adopted in a few data tools; (4) integrating data across various stages in the building life cycle remains a challenge; and (5) most data tools were developed and maintained by different parties for different purposes, their flexibility and interoperability can be improved to support broader use cases. Finally, recommendations for future research on building data tools are provided for the data and buildings community based on the FAIR principles to make data Findable, Accessible, Interoperable, and Reusable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Carbon dioxide capture with aqueous amino acids: Mechanistic study of amino acid regeneration by guanidine crystallization and process intensification

CO 2 capture from powerplant-generated flue gas via a phase-changing process involving absorption with aqueous amino acids (e.g., glycine or sarcosine) and bicarbonate crystallization with bis-iminoguanidines (e.g., glyoxal-bis-iminoguanidine or GBIG) is investigated in this paper. This process is of high interest due to its potential to decrease the energy penalty for CO 2 capture by significantly reducing the solvent regeneration energy typically associated with aqueous amine solvents. A critical step in the proposed CO 2 capture mechanism is the regeneration of the amino acid by removal of protons and bicarbonate ions from solution through crystallization of GBIGH 2 2+ bicarbonate salt. Here, we investigated the thermodynamics and kinetics of glycine regeneration by crystallization of GBIGH 2 2+ (HCO 3 – ) 2 (H 2 O) 2 . A theoretical model was developed and compared to experimental data to simulate and predict the glycine regeneration and determine its reaction mechanism. This combined experimental and theoretical study led to the conclusion that, while the GBIGH 2 2+ bicarbonate crystallization step provides most of the thermodynamic driving force for the glycine regeneration, the rate-limiting step is the protonation of GBIG prior to crystallization. The CO 2 loading and amino acid regeneration steps were combined into a single, intensified process using a bubble column reactor. The CO 2 loading capacity of GBIG was experimentally determined to be roughly 1.36 mol CO 2 per mol GBIG. These results provide the fundamental basis for developing an effective carbon capture technology with phase-changing amino acid/guanidine absorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic Insights into Dinitrogen Reduction to Ammonia in Light-Controlled Nanocrystal:Nitrogenase Complexes

Developing systems that can efficiently capture photon energy and convert this energy into fuels and chemicals requires understanding how to assemble molecular components with diverse functions into complete systems possessing selectivity and efficiency in directing charge carriers to catalytic reactions. There are many challenges to achieving this goal. One promising approach is the development of hybrid systems that combine semiconductor nanocrystals (NCs) for light capture and enzymes as efficient catalysts. Such biohybrid systems capitalize on the tunable electronic and optical properties of NCs while leveraging the unmatched specificity and efficiency of enzymes in catalyzing chemical reactions, thereby offering opportunities to surpass the limitations of each component alone. Here, we focus on recent progress in developing a biohybrid system that combines CdS NCs for photon capture with the enzyme nitrogenase to accomplish light-driven dinitrogen (N 2 ) reduction to ammonia (NH 3 ). Integrating light-harvesting materials with biological catalysts requires a deep understanding of NC properties, protein stability, and electron transfer (ET), making it an inherently multidisciplinary problem. The reduction of N 2 to NH 3 is a challenging reaction, with a high demand in both agriculture and industrial chemical production. This reaction is intrinsically energy intensive, due to the need to activate the N≡N triple bond. The current standard industrial approach to N 2 reduction, the Haber−Bosch reaction, obtains the necessary energy input from fossil fuels, whereas biological systems capable of N 2 reduction utilize the hydrolysis of ATP as their energy source. Replacing these costly, energy-intensive inputs with renewable light energy represents a critical step toward sustainable NH 3 production. Recent progress has demonstrated that semiconductor CdS NCs can be coupled to the catalytic component of nitrogenase, the MoFe protein, to form a biohybrid CdS NC:MoFe protein complex, enabling light-driven N 2 reduction rather than energy input from fossil fuels or ATP. This illustrates how inorganic NCs can functionally replace the natural Fe protein partner, yielding a biohybrid catalyst that enables controlled electron delivery and provides not only light-driven NH 3 production but also new approaches for probing enzyme catalytic function. The CdS NC:MoFe protein biohybrid system enables light-initiated electron delivery at ambient temperature, as well as temperatures below freezing, allowing for stabilization and spectroscopic characterization of key reaction intermediates. These findings highlight how photochemical biohybrids can serve as both functional catalysts and mechanistic probes. Beyond studies of the nitrogenase mechanism, studies of the CdS NC:MoFe system reveal how variables such as NC size, electrostatic binding interactions, and sacrificial electron donors (SEDs) govern complex stability, charge transfer efficiency, and catalytic performance. In addition, studies of nitrogenase and the high activation barrier for N 2 reduction are enabling investigations of new and interesting questions regarding the properties and limitations of NC biocatalysis. In this Account, we describe the key features of CdS NC:MoFe protein biohybrids and the parameters for optimal light-driven N 2 reduction, and how controlling ET with light illuminates the path to new insights into the nitrogenase mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Controlling Polymer Morphology in Blade-Coated All-Polymer Solar Cells

In this report translating all-polymer solar cells from spin-coating to scalable roll-to-roll-compatible fabrication techniques is a critical step toward the application of organic photovoltaics at a scale. Techniques to control polymer crystallization and phase separation during solution printing are essential to obtain high-performance printed organic solar cells. Here, we demonstrate a novel solvent additive approach employing trace amounts of phthalates as additives to control polymer crystallinity and suppress unfavorable phase separation in a representative PTB7-Th/P(NDI2OD-2T) all-polymer solar cell. The best-performing additive increased the blade-coated device performance from 2.09 to 4.50% power conversion efficiency, an over twofold improvement, mitigating the loss in performance that is typically observed during process transfer from spin-coating to blade-coating. It is suggested that the improved device performance stems from a finer polymer phase-separation size and overall improved active layer morphology, evidenced by device characterization data and indirectly supported by grazing incidence wide-angle X-ray scattering analyses. Real-time X-ray diffraction measurements during blade-coating provide mechanistic insights and suggest that the dioctyl phthalate additive may act as a compatibilizer, reducing the demixing of the donor and acceptor polymer during film formation, enabling a smaller phase separation and improved performance. The structural diversity of the class of phthalate additives makes this simple yet effective concept promising for translating other all-polymer material systems to blade-coating and other scalable printing techniques.

14 SOLAR ENERGY↗

Ternary Phase Diagram of Water/Bio-Oil/Organic Solvent for Bio-Oil Fractionation

Separating bio-oil by fractionation with different chemical composition is a critical step to refine these oils and obtain high value products. Cold-water precipitation of pyrolytic lignin from bio-oil is the most common approach used. However, the obtained aqueous phase from this method still contain phenols, is diluted and difficult to use. In this study, the use of liquid-liquid extraction with different solvents (1-butanol, ethyl acetate, 1-octanol, dichloromethane, toluene, and hexane) for the separation of targeted molecules (lignin oligomers, sugars, acetic acid) is explored. Ternary phase diagrams for the organic solvent/water/bio-oil are reported. The partition coefficient of compounds of interest (both light and heavy fraction) is reported for the liquid-liquid equilibrium zone. When using butanol as solvent, the highest separation factor of total phenols over total sugars was observed. Furthermore, our results provide information to design L-L separation units with the capacity to selectively recover targeted molecules from pyrolysis oils.

09 BIOMASS FUELS↗

Pilot-Scale Continuous Plug-Flow Hydrothermal Liquefaction of Food Waste for Biocrude Production

Pilot-scale hydrothermal liquefaction (HTL) of biowaste is a critical step toward commercialization of the HTL technology. Despite many HTL studies conducted with wet biomass, including food waste, few were performed with a pilot-scale continuous plug-flow reactor (PFR), with the biocrude yield and quality analysis based on dewatering (ASTM D2892 Annex X1). This paper describes the development and performance evaluation of a mobile pilot-scale HTL continuous PFR, with a processing capacity of 60 L/h of wet feedstock and 6 L/h of biocrude production. The reactor system was designed for reaction conditions of up to 325 °C and 17.25 MPa. The reactor has a volume of 28.88 L with an additional counterflow heat exchanger volume of 18.07 L. Two types of food wastes, from a food processing plant and grocery store, were processed at 280 °C for 30 min, producing biocrude oil yields of 52.19 and 47.06 wt %, energy recoveries of 68.17 and 70.77%, and carbon recoveries of 66.91 and 64.78%, respectively. Furthermore, due to its high feedstock capacity and reaction volume, large amounts of biocrude oil and post-HTL wastewater (PHW) were obtained from this pilot-scale reactor to allow downstream research on upgrading biocrude oil for transportation fuel as well as PHW treatment and nutrient recovery.

09 BIOMASS FUELS↗

Toward a Diverse Next-Generation Energy Workforce: Teaching Artificial Photosynthesis and Electrochemistry in Elementary Schools through Active Learning

Artificial photosynthesis is a promising approach to generate commodity chemicals using abundant chemical feedstocks and renewable energy sources. Despite its importance, affordable and effective hands-on classroom activities that demonstrate artificial photosynthesis and teach key concepts, especially for primary school students, are lacking. Educating young students on this topic is a critical step in the development of the next-generation energy workforce, especially one that is diverse in race and gender. Here, we hypothesize that an effective approach to educate a broad range of young students on the topic of artificial photosynthesis is through the use of an active learning-based lesson plan that employs cheap and accessible materials. This hypothesis is confirmed by evaluating the understanding of fifth grade students with a survey before and after a lesson plan on artificial photosynthesis that uses active-learning techniques and uses safe and highly accessible materials (baking soda, tap water, plastic jars, Ni coil, alligator clips, and a solar cell) to perform solar-powered water splitting. The lesson plan and survey questions are designed to align with the educational outcomes for fifth grade classrooms in California and to address four general learning objectives: (1) Motivations of Artificial Photosynthesis, (2) Applications of Artificial Photosynthesis, (3) Inputs and Outputs of Artificial Photosynthesis, and (4) Engineering Design for Artificial Photosynthesis. The survey data demonstrate a statistically significant improvement in overall student understanding from the lesson plan. Importantly, the data show that the lesson plan presented here is effective at narrowing the performance gap between minority students and overly represented groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking

A critical step in structure-based drug discovery is predicting whether and how a candidate molecule binds to a model of a therapeutic target. However, substantial protein side chain movements prevent current screening methods, such as docking, from accurately predicting the ligand conformations and require expensive refinements to produce viable candidates. Here, we present the development of a high-throughput and flexible ligand pose refinement workflow, called “tinyIFD”. The main features of the workflow include the use of specialized high-throughput, small-system MD simulation code mdgx.cuda and an actively learning model zoo approach. We show the application of this workflow on a large test set of diverse protein targets, achieving 66% and 76% success rates for finding a crystal-like pose within the top-2 and top-5 poses, respectively. We also applied this workflow to the SARS-CoV-2 main protease (M pro ) inhibitors, where we demonstrate the benefit of the active learning aspect in this workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Invariant Molecular Representations for Heterogeneous Catalysis

Catalyst screening is a critical step in the discovery and development of heterogeneous catalysts, which are vital for a wide range of chemical processes. In recent years, computational catalyst screening, primarily through density functional theory (DFT), has gained significant attention as a method for identifying promising catalysts. However, the computation of adsorption energies for all likely chemical intermediates present in complex surface chemistries is computationally intensive and costly due to the expensive nature of these calculations and the intrinsic idiosyncrasies of the methods or data sets used. This study introduces a novel machine learning (ML) method to learn adsorption energies from multiple DFT functionals by using invariant molecular representations (IMRs). To do this, we first extract molecular fingerprints for the reaction intermediates and later use a Siamese-neural-network-based training strategy to learn invariant molecular representations or the IMR across all available functionals. Our Siamese network-based representations demonstrate superior performance in predicting adsorption energies compared with other molecular representations. Notably, when considering mean absolute values of adsorption energies as 0.43 eV (PBE-D3), 0.46 eV (BEEF-vdW), 0.81 eV (RPBE), and 0.37 eV (scan+rVV10), our IMR method has achieved the lowest mean absolute errors (MAEs) of 0.18 0.10, 0.16, and 0.18 eV, respectively. These results emphasize the superior predictive capacity of our Siamese network-based representations. The empirical findings in this study illuminate the efficacy, robustness, and dependability of our proposed ML paradigm in predicting adsorption energies, specifically for propane dehydrogenation on a platinum catalyst surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Doping in Efficient Polycrystalline CdSeTe Solar Cells via AsCl 3 Vapor Annealing

Doping in cadmium telluride (CdTe) thin-film solar cells is a critical step in producing highly efficient CdTe solar modules. To date, copper (Cu) ex-situ diffusion doping and group V in situ doping (such as arsenic, As) have been effectively used in manufacturing CdTe solar modules. However, Cu doping is prone to rapid degradation, whereas the low activation ratio of the dopants constrains group V in situ doping. Recently, ex-situ group V doping has been developed, showing an improved doping activation ratio through a solution process. Here, in this study, we developed a vapor-based AsCl 3 doping method for diffusion doping of polycrystalline CdSeTe devices. AsCl 3 vapor annealing can promote the diffusion of As into the bulk CdSeTe through a surface chemical reaction between CdTe and AsCl 3 . This approach has led to a long carrier lifetime of over 72 ns, V oc of 850 mV, and power conversion efficiency of ~18% with Au metal electrodes. The vapor-based ex situ group V doping approach offers an effective means to perform group V diffusion doping into the CdSeTe device.

14 SOLAR ENERGY↗

Dangling Bonds as Possible Contributors to Charge Noise in Silicon and Silicon–Germanium Quantum Dot Qubits

Spin qubits based on Si and Si 1–x Ge x quantum dot architectures exhibit among the best coherence times of competing quantum computing technologies, yet they still suffer from charge noise that limit their qubit gate fidelities. Identifying the origins of these charge fluctuations is therefore a critical step toward improving Si quantum-dot-based qubits. Here, we use hybrid functional calculations to investigate possible atomistic sources of charge noise, focusing on charge trapping at Si and Ge dangling bonds (DBs). We evaluate the role of global and local environment in the defect levels associated with DBs in Si, Ge, and Si 1–x Ge x alloys, and consider their trapping and excitation energies within the framework of configuration coordinate diagrams. We additionally consider the influence of strain and oxidation in charge-trapping energetics by analyzing Si and GeSi DBs in SiO 2 and strained Si layers in typical Si 1–x Ge x quantum dot heterostructures. Our results identify that Ge dangling bonds are more problematic charge-trapping centers both in typical Si 1–x Ge x alloys and associated oxidation layers, and they may be exacerbated by compositional inhomogeneities. In conclusion, these results suggest the importance of alloy homogeneity and possible passivation schemes for DBs in Si-based quantum dot qubits and are of general relevance to mitigating possible trap levels in other Si, Ge, and Si 1–x Ge x -based metal-oxide-semiconductor stacks and related devices.

36 MATERIALS SCIENCE↗