Search NASA⌕ Search

SEARCH · Search NASA

Results for “Defect”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43

Unveiling long-lived dual emission in a tetraphenylethylene-based metal–organic framework

Incorporating photoactive linkers into metal–organic frameworks (MOFs) has proved useful in improving photophysical properties of organic chromophores. This is achieved by controlling the local packing of linkers or defect engineering within the MOF. Using these ideas, we demonstrate that a tetraphenylethylene-based MOF exhibits long-lived linker-based emission out to 1 μs—substantially longer than previously reported. The emission contains two independent components whose dynamics branch from early timescales. Furthermore these findings suggest that charge recombination and distinct defect sites exist and contribute a weak yet detectable emission, and demonstrate how high-sensitivity transient photoluminescence spectroscopy can reveal unexpected populations in nominally crystalline materials.

36 MATERIALS SCIENCE↗

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗

Synthetic active liquid crystals powered by acoustic waves.

Active nematic materials combine orientational order with activity at the microscopic level. Current experimental realizations of active nematics include vibrating elongated particles, cell layers, suspensions of elongated bacteria, and a mixture of bio-filaments with molecular motors. The majority of active nematics are of biological origin. The realization of a fully synthetic active liquid crystal comprised of a lyotropic chromonic liquid crystal energized by ultrasonic waves, is reported. This synthetic active liquid crystal is free from biological degradation and variability, exhibits phenomenology associated with active nematics, and enables precise and rapid activity control over a significantly extended range. It is demonstrated that the energy of the acoustic field is converted into microscopic extensile stresses disrupting long-range nematic order and giving rise to an undulation instability and proliferation of topological defects. The emergence of unconventional free-standing persistent vortices in the nematic director field at high activity levels is revealed. The results provide a foundation for the design of externally energized active liquid crystals with stable material properties and tunable topological defect dynamics crucial for the realization of reconfigurable microfluidic systems.

active matter↗

On the Structure–Property Relationship of Semi‐Coherent FeCr 2 O 4 /Cr 2 O 3 Spinel/Corundum Interfaces

Abstract Oxide heterointerfaces are extremely common in both natural and artificial composite structures, including corroded structural materials. Often, key properties such as segregation and atomic transport are dictated by the structure of these interfaces. However, despite this critical link, very few heterointerfaces have been studied in any detail at the atomic scale. Here, one important oxide heterointerface is examined, between spinel and corundum, using the chemical system FeCr 2 O 4 /Cr 2 O 3 as a representative and technologically important case. Using atomistic simulation techniques, it is found that the structure, particularly the local chemistry, of the interface depends on the crystal chemistry at the interface. This atomic and chemical structure further impacts important properties such as defect segregation and mass transport. It is found that defects can nucleate at some regions of these interfaces and migrate back and forth across the corundum layer, suggesting high atomic mobility that may be important for the evolution of spinel/corundum composite structures in extreme conditions.

36 MATERIALS SCIENCE↗

Inert Gas Element as Active Infrared‐Absorption Source and Donor in Silicon for Forbidden‐Wavelength Sensing

Intrinsic silicon (Si) is forbidden for infrared (IR) sensing at the communication wavelength like 1.31 or 1.55 µm due to the well‐known bandgap limitation. In this work, an unexpected physical picture of using argon (Ar) is identified, which is usually inert to the surrounding chemical environment and used as a protective agent in semiconductor processing, to overcome the IR‐sensing‐forbidden problem in Si. Here, in this work, it is shown by an analysis of a dynamic secondary ion mass spectrometer that such a Si, when exposed to laser pulse in Ar gas, can contain a very high dose of Ar up to 10 20 cm −3 even after 1300 days. First‐principles calculations, molecular dynamics, and Hall effect measurements reveal that, due to both steric and dynamic repulsions by Ar orbitals to Si dangling bonds, the Ar‐filled‐vacancy produces a much wider defect band inside the gap, which is not only responsible for strong infrared absorption, but also causes a significant increase in n‐type conductivity, both in line with experiments. The study proves that originally inert elements in fact can act as active impurities in semiconductors for advanced applications, which updates the current knowledge of defect physics.

36 MATERIALS SCIENCE↗

Revealing Robust Room Temperature Ferromagnetism in Gd‐Doped Few‐Layered MoS 2 Thin Films

2D MoS 2 holds great promise for spintronics, yet is limited by intrinsic diamagnetism. This study demonstrates inducing ferromagnetic behavior in MoS 2 films doped with 0.47% Gd, achieving an ultrahigh saturation magnetization of 454 emu/cm 3 in a few‐layered film over 11‐times higher than bulk films (40 nm). Raman spectroscopy, X‐ray photoelectron spectroscopy, X‐ray magnetic circular dichroism, and density functional theory (DFT) calculations reveal an interplay between Gd dopants and Mo, S vacancies (V 1Mo+2S ), leading to the formation of bound magnetic polarons (BMPs) that drive ferromagnetic ordering. H 2 S annealing and DFT calculations reveal that defect healing reduces the saturation magnetization by 83%. High sulfur migration barrier in few‐layered films helps preserve BMPs, thereby sustaining ferromagnetism, whereas lower migration barriers in bulk films lead to suppression. These findings highlight the synergy between Gd doping and defect engineering in achieving ultrahigh room‐temperature ferromagnetism, offering a scalable strategy for developing high‐performance 2D magnetic materials for spintronic applications.

36 MATERIALS SCIENCE↗

Interactions Enhance Ramp Reversal Memory in Locally Phase Separated Materials

The ramp-reversal memory (RRM) effect in metal–insulator transition metal oxides (TMOs), a non-volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non-volatile memory devices. Our previous defect motion model successfully explained RRM in vanadium dioxide (VO 2 ), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains. Here, we extend our model by combining a correlated Random Field Ising Model with defect diffusion-segregation, enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that the maximum RRM occurs when the turnaround temperature approaches the inflection point. This peak in RRM vs. turnaround temperature is consistent with prior transport measurements, as well as our own optical measurements reported here. Significantly, we find that increasing nearest-neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much-needed theoretical framework for optimizing device applications.

36 MATERIALS SCIENCE↗

Assessment of uranium nitride interatomic potentials

Uranium mononitride (UN) is a promising nuclear fuel due to its high fissile density, high thermal conductivity, and suitability for reprocessing. In this study, two uranium nitride interatomic potentials are assessed: Tseplyaev and Starikov's angular-dependent potential and Kocevski et al.'s embedded atom model potential. Predictions of the thermophysical and elastic properties of UN, UN 2 , and α- and β-U 2 N 3 computed using both potentials are assessed and compared to available experimental data. Notably, the Tseplyaev potential performs better with the energetic aspects of UN, e.g., specific heat capacity and point defect formation energies, whereas the Kocevski potential performs better with the structural aspects of UN, e.g., thermal expansion as well as with the elastic properties. The reasons why the Kocevski potential underestimates the UN specific heat are explained by examining the UN phonon properties modeled using both potentials. The Kocevski potential shows better identification of the mechanical stability ranges of UN, UN 2 , and α- and β-U 2 N 3 , reasonably predicting the melting point of UN and predicting stable structures for UN 2 and α- and β-U 2 N 3 . On the other hand, the Tseplyaev potential predicts a premature phase change of both UN and UN 2 and cannot stabilize α- nor β-U 2 N 3 . However, the Kocevski potential cannot predict a stable α-U phase and is thus not suitable for the calculation of formation energies for non-stoichiometric point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advances and perspectives of hard carbon anode modulated by defect/hetero elemental engineering for sodium ion batteries

Sodium-ion batteries (SIBs) serve as a promising complement to lithium-ion batteries for large-scale energy storage, leveraging the abundance of sodium resources and notable safety advantages. The key advancement in SIB industrialization hinges on identifying a cost-effective and high-performance anode material, similar to the graphite anode in lithium-ion batteries. Hard carbon emerges as prime anode materials for SIBs, boasting high specific capacity, low sodium storage potential, and wide availability. However, practical applications of hard carbon encounters challenges such as low initial Coulombic efficiency (ICE), inadequate long-term cycling stability, and poor rate performance. Recent research has focused on the optimization of hard carbon electrodes through functional design. In this comprehensive review, we have meticulously examined the progress in enhancing sodium storage performance through microstructural modulation within hard carbon, encompassing four pivotal aspects: heteroatom doping, incorporation of oxygen functional groups, surface coating, and intrinsic defect engineering. Progress in implementing these strategies is scrutinized, while the merits and challenges of each defect engineering approach are discussed. In conclusion, this review also looks into forthcoming opportunities and challenges in the practical application process of hard carbon electrodes in SIBs.

25 ENERGY STORAGE↗

Fabrication and characterization of boron-terminated tetravacancies in monolayer hBN using STEM, EELS and electron ptychography

Tetravacancies in monolayer hexagonal boron nitride (hBN) with consistent edge termination (boron or nitrogen) form triangular nanopores with electrostatic potentials that can be leveraged for applications such as selective ion transport and neuromorphic computing. In order to quantitatively predict the properties of these structures, an atomic-level understanding of their local electronic and chemical environments is required. Moreover, robust methods for their precision manufacture are needed. Here we use electron irradiation in a scanning transmission electron microscope (STEM) at a high dose rate to drive the formation of boron-terminated tetravacancies in monolayer hBN. Characterization of the defects is achieved using aberration-corrected STEM, monochromated electron energy-loss spectroscopy (EELS), and electron ptychography. Z-contrast in STEM and chemical fingerprinting by core-loss EELS enable identification of the edge terminations, while electron ptychography gives insight into structural relaxation of the tetravacancies and provides evidence of enhanced electron density around the defect perimeters indicative of bonding effects.

2D hBN↗

Enhancing MnBi 2 Te 4 Stability by Doping

MnBi 2 Te 4 (MBT) is an intrinsically magnetic topological material that possesses unique properties due to the quantum Hall effect. However, the low Mn–Bi mixed antisite formation energy is detrimental to these properties as it alters the long-range magnetic ordering in the Mn layer. Therefore, it is crucial to destabilize the antisite defects in MBT while preserving the favorable electronic properties. Here, to this end, we utilized a screening approach to understand the role of dopants in the Mn and Bi sites. We find that Sc, Y, and La dopings prefer substitutions on the Bi site and significantly increase the Mn–Bi antisite defect formation energy. We find that the contribution from the empty s and d states of Sc, Y, and La around the Fermi level is insignificant. However, at the high concentration limit, the Bi–Te octahedra are significantly modified with doping, leading to important changes in the band structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic-Scale Insights into Carbon Dissolution in α-, γ-, and θ-Al 2 O 3 : Phase-dependent Transport Dynamics from First-Principles Calculations

α-Al 2 O 3 exhibits superior carburizing corrosion resistance compared to metastable γ-Al 2 O 3 and θ-Al 2 O 3 phases in high-temperature CO 2 environments, yet its atomic-scale origins remain unclear. Using first-principles density functional theory, we systematically investigate carbon dissolution and diffusion in α-Al 2 O 3 , γ-Al 2 O 3 , and θ-Al 2 O 3 , including the effects of oxygen (O) and aluminum (Al) vacancies. Our results show that α-Al 2 O 3 consistently exhibits higher carbon solution enthalpies than γ-Al 2 O 3 and θ-Al 2 O 3 in both pristine and defective structures, indicating lower intrinsic carbon solubility in α-Al 2 O 3 . Vacancies significantly enhance carbon incorporation: O vacancies reduce solution enthalpy, while Al vacancies further amplify this effect, with a strong preference for carbon at Al vacancy sites. Carbon diffusion barriers are also highest in α-Al 2 O 3 , reflecting slower carbon mobility. Al vacancies increase diffusion barriers across all phases, while O vacancies raise barriers in α- and γ-Al 2 O 3 but slightly lower them in θ-Al 2 O 3 . These results reveal a dual mechanism behind the carburizing resistance of α-Al 2 O 3 : reduced carbon solubility and elevated diffusion barriers. Furthermore, this work provides atomic-scale insights to guide the design of alumina-based materials with improved carburizing resistance through phase selection and defect engineering.

36 MATERIALS SCIENCE↗

Scalable Bottom-Up Synthesis of Nanoporous Hexagonal Boron Nitride ( h -BN) for Large-Area Atomically Thin Ceramic Membranes

Nanopores embedded within monolayer hexagonal boron nitride (h-BN) offer possibilities of creating atomically thin ceramic membranes with unique combinations of high permeance (atomic thinness), high selectivity (via molecular sieving), increased thermal stability, and superior chemical resistance. However, fabricating size-selective nanopores in monolayer h-BN via scalable top-down processes remains nontrivial due to its chemical inertness, and characterizing nanopore size distribution over a large area remains extremely challenging. Here, we demonstrate a facile and scalable approach of exploiting the chemical vapor deposition (CVD) process temperature to enable direct incorporation of subnanometer/nanoscale pores into the monolayer h-BN lattice, in combination with manufacturing compatible polymer casting to fabricate centimeter-scale nanoporous atomically thin ceramic membranes. We leverage diffusive transport of analytes including size-selective Ficoll sieving to characterize subnanometer-scale and nanoscale defects that manifest as pores in centimeter-scale h-BN membranes, overcoming previous limitations in large-area characterization of nanoscale defects in h-BN. Our approach opens a new frontier to advance atomically thin membranes to 2D ceramic materials, such as h-BN via facile and direct formation of nanopores, for size-selective separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polytypic Zn–(In,Ga)–Se Nanocrystals with Tunable Emission

While the polymorphism of chalcopyrite semiconductors has been widely studied, the wurtzite analogues of defect-chalcopyrite II–III 2 –VI 4 compositions, such as Zn(In,Ga) 2 (S,Se) 4 , remain underexplored. Here, we report the synthesis of polytypic Zn–(In,Ga)–Se multipods via cation exchange using ZnSe as a template. With cubic cores and wurtzite arms elongated along the hexagonal c-axis, the multipods retain the structure and morphology of the ZnSe template. Optical characterization reveals composition-dependent absorption and photoluminescence, tunable from the visible to the near-infrared region, with spectral features distinct from those of previously reported defect-chalcopyrite structures. Temperature-dependent measurements demonstrate strong emission at cryogenic temperatures, which is quenched near room temperature due to thermally activated nonradiative processes. Here, we illustrate the use of ZnSe as a platform for cation exchange toward wurtzite multinary chalcogenides, unlocking access to novel structures with colorful optical properties.

cation exchange↗

Controllable Formation of Threefold-Coordinated Oxygen in Graphene by Low-Energy Ion Implantation

The atomically precise engineering of impurities in graphene and the understanding of their structural and carrier-dependent electronic properties at the nanoscale are crucial for advancing graphene-based nanoelectronics, catalysis, and energy technologies. Here, we demonstrate controllable incorporation of the elusive 3-fold-coordinated O substitutions into graphene using low-energy O + ion implantation under ultrahigh-vacuum conditions. By combining high-resolution scanning tunneling microscopy and spectroscopy (STM/S), bond-resolved noncontact atomic force microscopy techniques, and density functional theory (DFT) calculations, we resolve both the structural and electronic properties of the O-related defects. The STM/S measurements, corroborated by DFT calculations, uncover a characteristic impurity state that is energetically pinned to the Dirac point across different charge-carrier doping regimes. Molecular dynamics simulations further reveal the distribution of implantation-induced configurations and identify the formation of 3-fold-coordinated O dopants. Furthermore, this work provides a viable route to incorporate 3-fold-coordinated O dopants and opens new opportunities for controlled defect engineering in graphene.

3-fold-coordinated oxygen↗

Factors Affecting the Electron Conductivity in Single Crystal Li 7 La 3 Zr 2 O 12 and Li 7 P 3 S 11

One of the serious challenges in all solid-state Li ion batteries is neutral Li intrusion into the solid-state electrolyte that can ultimately cause catastrophic failure. One possibility for this is due to n-type electron conductivity that induces the reaction Li + + e – → Li 0 at sites where the potential is less than the Li + /Li potential. This paper reports hybrid density functional theory calculations of the electronic conductivity in two prototype single crystalline solid-state electrolytes, cubic Li 7 La 3 Zr 2 O 12 (c-LLZO) and Li 7 P 3 S 11 (LPS). The formation energies of important point defects that can affect electron conductivity are determined, and we find that the mechanism of n-type electron conductivity for both solid-state electrolytes is via “small” electron polaron hopping, where the quotes signify that substantial Li ion rearrangement is associated with the polaron formation and its migration. In both electrolytes, the formation energies for the small polarons at the Fermi energy are too high to generate measurable electron conductivity at room temperature. For c-LLZO, the concentration of electron polarons necessary to ensure charge neutrality from positively charged oxygen vacancies formed in synthesis can be significantly higher. Hence, the electron conductivity could be significant when measured with ion-blocking metal electrodes, and we discuss how the synthesis conditions could affect this magnitude. However, in the solid-state battery, these polarons are replaced by negatively charged Li vacancies so that the electron conductivity should remain minimal. For LPS single crystals, the inherent minimal electron conductivity is independent of synthesis conditions. Here we also show that the cost of forming Li 0 in bulk c-LLZO is enormous due to strain effects so that it could only potentially form at voids, grain boundaries, or around vacancy defects which relax the lattice strain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multinonmetal-Doped V 2 O 5 Nanocomposites for Lithium-Ion Battery Cathodes

Lithium-ion batteries (LIBs) are critical for portable electronics and electric vehicles, demanding higher energy density to meet increasing energy storage needs. Current commercial cathode materials, such as LiFePO 4 and LiCoO 2 , are limited by a single electron transfer, restricting their energy density. Vanadium pentoxide (V 2 O 5 ) emerges as a promising high-capacity cathode due to its high theoretical capacity of 443 mA h g –1 with three Li storage capacities, significantly surpassing conventional materials. However, the practical application of V 2 O 5 is hindered by a large structural evolution and rapid capacity fading during full lithium intercalation. Here, this study introduces a multinonmetal doping (MNM) strategy to enhance V 2 O 5 cathodes by incorporating all-nonmetal dopants (B, P, and Si) and graphene (G). MNM-V 2 O 5 -G exhibits increased surface oxygen defects, improving charge transfer kinetics and thus enhancing the rate performance and cycling stability. Our results provide valuable insights into the role of surface oxygen defects in stabilizing V 2 O 5 with element doping. This research highlights the potential of multinonmetal doping to improve LIB cathode materials, offering a promising pathway for design of high-energy-density V 2 O 5 cathodes and advancing the development of next-generation energy storage solutions.

25 ENERGY STORAGE↗

Depth-Resolved X-Ray Nanoimaging of Coherent and Incoherent Energy Transport in Silicon Carbide

Understanding lattice dynamics is crucial for optimizing the process of creating functional structures, such as laser writing of color-center defects. However, existing structural probes have difficulty measuring structural dynamics with submicrometer depth sensitivity. Here, in this study, a depth-resolved ultrafast X-ray nanodiffraction technique is developed to track the lattice dynamics of silicon carbide (SiC) in three dimensions. Upon laser excitation of an aluminum layer that acts as a heat and strain transducer, a specular Bragg peak of SiC shows an overall increase in the X-ray diffraction intensity rather than a peak shift. The relaxation dynamics of the increased intensity are significantly different when probed on and off the Bragg peak. The fast subnanosecond relaxation probed at the maximum of the Bragg peak is a result of the propagation of a coherent strain wave along the depth direction, while a slow relaxation probed at the wings of the Bragg peak reflects a localized incoherent lattice heating. To further visualize these processes, spatiotemporal maps were obtained by scanning the relative position and delay between the laser pump and X-ray probe beams, which capture the propagation of the strain wave, as well as a stationary structural distortion close to the aluminum/SiC interface. These depth-resolved structural measurements disentangle energy dissipation mechanisms in laser-excited SiC, and they open opportunities for finer control of, for example, the formation of optically addressable defect complexes central to quantum information applications.

X-ray nanodiffraction↗