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Composite laminate free-edge reinforcement with U-shaped caps. I - Stress analysis. II - Theoretical-experimental correlation

The present generalized plane-strain FEM analysis for the prediction of interlaminar normal stress reduction when a U-shaped cap is bonded to the edge of a composite laminate gives attention to the highly variable transverse stresses near the free edge, cap length and thickness, and a gap under the cap due to the manufacturing process. The load-transfer mechanism between cap and laminate is found to be strain-compatibility, rather than shear lag. In the second part of this work, the three-dimensional composite material failure criteria are used in a progressive laminate failure analysis to predict failure loads of laminates with different edge-cap designs; symmetric 11-layer graphite-epoxy laminates with a one-layer cap of kevlar-epoxy are shown to carry 130-140 percent greater loading than uncapped laminates, under static tensile and tension-tension fatigue loading.

Howard, W. E.↗

Analysis of AVHRR, CZCS and historical in situ data off the Oregon Coast

The original scientific objectives of this grant were to: (1) characterize the seasonal cycles and interannual variability for phytoplankton concentrations and sea surface temperature (SST) in the California Current using satellite data; and (2) to explore the spatial and temporal relationship between these variables and surface wind forcing. An additional methodological objective was to develop statistical methods for forming mean fields, which minimize the effects of random data gaps and errors in the irregularly sampled CZCS (Coastal Zone Color Scanner) and AVHRR (Advanced Very High Resolution Radiometer) satellite data. A final task was to evaluate the level of uncertainty in the wind fields used for the statistical analysis. Funding in the first year included part of the cost of an image processing system to enable this and other projects to process and analyze satellite data. This report consists of summaries of the major projects carried out with all or partial support from this grant. The appendices include a list of papers and professional presentations supported by the grant, as well as reprints of the major papers and reports.

Strub, P. Ted↗

Mobility Gaps between Low-Income and Not Low-Income Households: A Case Study in New York State

Understanding the travel challenges faced by low-income residents has always been and continues to be one of the most important transportation equity topics. This study aims to explore the mobility gaps between low-income households (HHs) and not low-income HHs, and how the gaps vary within different socio-demographic population groups in New York State (NYS). The latest National Household Travel Survey data was used as the primary data source for the analysis. The study first employed the K-prototype clustering algorithm to categorize the HHs in NYS based on their socio-demographic attributes. Five population groups were identified based on nine different household (HH) features such as HH size, vehicle ownership, and elderly status of its members. Then, the mobility differences, measured by trip frequency, trip distance, travel time, and person miles traveled, were examined among the five population groups. Results suggest that the individuals in low-income HHs consistently took fewer trips and made shorter trips compared to their not low-income counterparts in NYS. The travel distance gaps were most obvious among white HHs with more vehicles than drivers. In addition, while the population from low-income HHs made shorter trips on average (2.7 mi shorter per trip), they experienced longer travel time than those from not low-income HHs (1.8 min longer per trip). These key findings provide a deeper understanding of the travel behavior disparities between low-income and not low-income households. The findings could also support policymakers and transportation planners in addressing the critical needs of residents in low-income households in NYS and provide inputs for designing a more equitable transportation system.

Liu, Yuandong↗

Domain Adaptation for Measurements of Strong Gravitational Lenses

Upcoming surveys are predicted to discover galaxy-scale strong lenses on the magnitude of 105, making deep learning methods necessary in lensing data analysis. Currently, there is insufficient real lensing data to train deep learning algorithms, but training only on simulated data results in poor performance on real data. Domain adaptation can bridge the gap between simulated and real datasets. We adopt domain adaptation on the estimation of Einstein radius in simulated galaxy-scale gravitational lensing images. We evaluate two domain adaptation techniques - domain adversarial neural networks (DANN) and maximum mean discrepancy (MMD). We train on a source domain of simulated lenses and apply it to a target domain with emulation of DES survey conditions. We show that both domain adaptation techniques can significantly improve the model performance on the more complex target domain datasets. Our results show the potential of using domain adaptation to perform analysis on future survey data with a deep neural network trained on simulated data.

79 ASTRONOMY AND ASTROPHYSICS↗

AGR-5/6/7 CAPSULE 1 THERMAL MODEL WITH OFFSET GAS GAPS

Fuel compact temperatures are a crucial factor in assessing the irradiation performance of tristructural isotropic (TRISO) fuel particles. In the absence of direct measurement, fuel compact temperatures were calculated using a 3 D finite-element thermal model that was subject to simulation uncertainty. The most dominant factor in the uncertainty of calculated fuel temperatures is the gas gap uncertainty caused by the graphite holder nub-to-capsule clearance. This thermal model was revised to examine the most probable graphite offset position for Capsule 1 for four different days during the irradiation. In the analysis, the offset distance and azimuthal direction at both the top and bottom of the holder were varied. The best-fit offset was estimated based on the minimum root mean square error (RMSE) of the residuals (measured minus calculated thermocouple [TC] temperatures) for the operational TCs in Capsule 1. Near the end of the irradiation, when the graphite had shrunk and the gas gaps had grown, a peak temperature was found with maximum offset along the TC lines, with nickel introducing a potential mechanism for fuel particle failures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Tritium Transport Phenomena in Molten-Salt Reactors: Molten Salt Tritium Transport Experiment Design

Tritium is produced from neutron interactions with both lithium and beryllium. Large quantities of tritium are generated in Molten Salt Reactors (MSRs) which use LiF/BeF2 (FLiBe) as the fuel salt. Tritium is unique among the radionuclide hazards as it readily permeates through metal structural materials at high temperatures. All metal surfaces are potential release paths for tritium. For adequate safety analysis and eventual licensing of new reactors, predictive models for tritium transport and release from MSRs must be developed. These models must account for the multiple transport phenomena involved with tritium: fuel salt phase mass transport, dissociation/recombination reactions on metal surfaces, interstitial diffusion through the metal structure, and salt or gas phase mass transport in the downstream fluid. These models also must also be validated with representative experiments. Our previous report outlined tritium transport phenomena involved in MSRs, made suggestions on gaps in the transport dataset, and proposed an experimental test stand to test combined transport effects – tritium transport through pipe walls in a convective salt flow. In this report, we summarize an updated analysis framework for tritium transport in MSRs, report our results on hydrogen and deuterium permeation through Hastelloy N, and describe the final design of the Molten Salt Tritium Transport Experiment (MSTTE, pronounced “misty”). The MSRE provides the only wholistic experimental data set for tritium transport in MSRs and understanding the transport phenomena involved in the MSRE is crucial for future model development. One set of parameters in our analysis framework was unknown for the MSRE—surface reaction rates for tritium on Hastelloy N. This warranted our hydrogen and deuterium permeation campaign to assess the permeability, diffusivity, and solubility of hydrogen isotopes in clean Hastelloy N. Surface reaction rate constants were probed by low pressure measurements, however, no surface effects were observed in the limits of our permeation apparatus. Permeation experiments on oxidized Hastelloy N were not performed for this report but are planned in future work. The experimental test stand, MSTTE, measures combined transport properties of the salt-metal system. MSTTE is a forced convection FLiBe loop with custom designed test section to measure tritium transport through candidate structural materials. We use MSRE relevant dimensionless numbers to design and scale the test section. Hastelloy N is a candidate loop and test section material due to the relevance for the MSRE and related designs, however, other metals are being considered (e.g. 316H SS) which may better align with current vendor concepts.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Closing the Phenotypic Gap between Transformed Neuronal Cell Lines in Culture and Untransformed Neurons

Studies of neuronal dysfunction in the central nervous system (CNS) are frequently limited by the failure of primary neurons to propagate in vitro. Neuronal cell lines can be substituted for primary cells but they often misrepresent normal conditions. We hypothesized that a dimensional (3-D) cell culture system would drive the phenotype of transformed neurons closer to that of untransformed cells. In our studies comparing 3-D versus 2-dimensional (2-D) culture, neuronal SH-SY5Y (SY) cells underwent distinct morphological changes combined with a significant drop in their rate of cell division. Expression of the proto-oncogene N-myc and the RNA binding protein HuD was decreased in 3-D culture as compared to standard 2-D conditions. We observed a decline in the anti-apoptotic protein Bcl-2 in 3-D culture, coupled with increased expression of the pro-apoptotic proteins Bax and Bak. Moreover, thapsigargin (TG)-induced apoptosis was enhanced in the 3-D cells. Microarray analysis demonstrated significantly differing mRNA levels for over 700 genes in the cells of each culture type. These results indicate that a 3-D culture approach narrows the phenotypic gap between neuronal cell lines and primary neurons. The resulting cells may readily be used for in vitro research of neuronal pathogenesis.

Myers, Tereance A.↗

Eucalyptus – An Analysis Suite for Fault Trees with Uncertainty Quantification

Eucalyptus is a novel code developed at Lawrence Livermore National Laboratory to incorporate uncertainty quantification into Fault Tree Analysis (FTA). This tool addresses the challenge of imperfect knowledge in “grey-box” systems by allowing analysts to incorporate and propagate uncertainty from component-level assessments to system-level effects. Eucalyptus facilitates a consistent evaluation of the impact of subject matter expert judgment and knowledge gaps on overall system response by Monte Carlo generation of possible system fault trees, sampling probabilities of the existence of subsystems and components. Here, the code supports the specification of fault trees through text and allows export to various formats, including auto-generated images, easing analysis and reducing errors. It has undergone extensive verification testing, demonstrating its reliability and readiness for deployment, and leverages on-node parallelism for rapid analysis. Example analyses are shown that include the identification of system failure paths and quantification of the value of further information about system components.

Fault Tree Analysis↗

Artificial Intelligence for Enhancing Multiscale Analysis: Buildings Focus

This project aims to develop multi-scale building energy data, potentially improving the representation of the U.S. buildings sector in GCAM-USA, an U.S.-focused human-energy-Earth systems model. Existing building energy datasets are typically limited to national or regional levels, which constrains the ability of models to capture fine-scale human-energy-Earth systems interactions and reduces their relevance for decision-making on issues such as energy security, resilience, and energy planning. By leveraging AI and advanced data integration methods, this work fuses multiple existing datasets to enhance the physical and geographic representation of both residential and commercial building energy use. So far, progress includes processing residential building data, designing the data structure for commercial buildings, and testing AI approaches for integrating datasets and addressing spatial-temporal gaps. This effort can not only advances GCAM-USA’s capability in modeling the buildings sector but also supports broader DOE missions, such as developing digital testbeds, enhancing grid resilience analysis, and improving building–energy system modeling at decision-relevant scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

MHD stability trends and improved performance of LHD inward-shifted configurations: The role of the neutral beam current drive and thermal plasma density

The aim of the present study is to analyze the effect of the neutral beam current drive (NBCD), thermal plasma density, and NBI operational regime on the stability of pressure gradient-driven modes (PGDM) and Alfvén eigenmodes (AE) in LHD inward-shifted configurations. The stabilization of n/m = 1/2 PGDM (n toroidal mode and m poloidal mode) is observed in the discharge 167 800 during the co-NBCD phase. The iota profile evolution measured by motional stark effect diagnostic may indicate the iota profile up-shift caused by the co-NBCD can induce a non-resonant transition of the rational surface 1/2 before the mode stabilization. The evolution of the iota profile and continuum gaps in the discharge 167 805 during the ctr-NBCD phase leads to the stabilization of the AE, caused by the narrowing of the continuum gap as the iota profile down-shift. Opposite stability trends are identified for PGDM and AE stability with respect to the thermal plasma density. A larger thermal plasma density (larger thermal β) further enhances PGDM although the continuum gaps are narrower leading to configurations with stable AEs. The linear stability of AEs is analyzed using the gyro-fluid FAR3d code to reproduce the AE stability trends observed in the experiments with respect to the NBCD and thermal plasma density. The analysis of hypothetical scenarios dedicated to study different NBI operational regimes with respect to EP energy, and β and radial density profiles indicate off-axis NBI operation shows a higher EP β threshold to destabilize AEs compared to on-axis configuration. This is explained by the presence of a TAE gap in the inner plasma region, easily destabilized by an on-axis NBI injection. The control of the NBCD and thermal plasma in the discharge 167 800 shows a transitory stabilization of PGDM and AEs, as well as an improved discharge performance identified by an increment of the neutron fluxes.

Varela, Jacobo↗

Sensitive Top-Down Proteomics Analysis of a Low Number of Mammalian Cells Using a Nanodroplet Sample Processing Platform

Top-down proteomics is a powerful tool for characterizing genetic variations and post-translational modifications at intact protein level. That being said, one significant technical gap of top-down proteomics is the inability to analyze low amount of biological samples, which limits its access to isolated rare cells, fine-needle aspiration biopsies, and tissue substructures. Herein, we developed an ultrasensitive top-down platform by incorporating a microfluidic sample preparation system, termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples), into a top-down proteomics workflow. A unique combination of a nonionic detergent dodecyl-ß-D-maltopyranoside (DDM) with urea as protein extraction buffer significantly improved both protein extraction efficiency and sample recovery. We hypothesize that the DDM detergent improves protein recovery by efficiently reducing non-specific adsorption of intact proteins on container surfaces, while urea serves as a strong denaturant to disrupt noncovalent complexes and release intact proteins for downstream analysis. The nanoPOTS-based top-down platform reproducibly and quantitatively identified ~170 to ~620 proteoforms from ~70 to ~770 HeLa cells containing ~10 to ~115 ng of total protein. A variety of post-translational modifications including acetylation, myristoylation, and iron binding were identified using only less than 800 cells. We anticipate the nanoPOTS top-down proteomics platform will be broadly applicable in biomedical researches, particularly where clinical specimens are not available in amounts amenable to standard workflows.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A comprehensive and synthetic dataset for global, regional, and national greenhouse gas emissions by sector 1970–2018 with an extension to 2019

To track progress towards keeping global warming well below 2 °C or even 1.5 °C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO 2 emissions, CH 4 emissions, N 2 O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF 6 , NF 3 ) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO 2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (~ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO 2 eq. consisting of CO 2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO 2 , CO 2 -LULUCF 5.7 ± 4.0 GtCO 2 , CH 4 10 ± 3.1 GtCO 2 eq., N2O 2.6 ± 1.6 GtCO 2 eq., and F-gases 1.3 ± 0.40 GtCO 2 eq. Initial estimates suggest further growth of 1.3 GtCO 2 eq. in GHG emissions to reach 59 ± 6.6 GtCO 2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr –1 ) compared to 2000–2009 (2.4 % yr –1 ), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

54 ENVIRONMENTAL SCIENCES↗

Policy implications of net-zero emissions: A multi-model analysis of United States emissions and energy system impacts

Many countries, subnational jurisdictions, and companies are setting net-zero emissions goals; however, questions remain about strategies to reach these targets, policy measures, technology gaps, and economic impacts. Here, we investigate the potential policy implications of reaching economy-wide net-zero CO 2 emissions across the United States by 2050 using results from a multi-model comparison with 14 energy-economic models. Model results suggest that achieving net-zero CO 2 targets depends on policies that accelerate deployment of zero- and low-emitting technologies that have seen rapid cost reductions in recent years (including wind, solar, battery storage, and electric vehicles) as well as relatively nascent options (including carbon capture and storage, advanced biofuels, low-carbon hydrogen, advanced nuclear, and long-duration energy storage). While net-zero policies are likely to lower fossil fuel consumption, including considerable coal and petroleum reductions, achieving net-zero emissions does not necessarily mean phasing out all fossil fuels. Model results indicate that the Inflation Reduction Act’s energy and climate provisions amplify near-term decarbonization but that net-zero policies have larger impacts on long-run outcomes. Stringent climate policy can have large fiscal impacts on tax revenue and government spending—revenues from carbon pricing and subsidies for carbon removal range from 0.1 % to 3.7 % of GDP in 2050 across models. Each dollar per metric ton carbon price leads to a 0.06 % to 0.31 % reduction in economy-wide CO 2 emissions relative to a reference scenario with current policies. Spending on energy across the economy decreases relative to today for many models under reference and net-zero policies, especially as a share of GDP, due primarily to end-use electrification and energy efficiency.

54 ENVIRONMENTAL SCIENCES↗

A theoretical study of heterojunction and graded band gap type solar cells

The theory of heterojunction and graded bandgap solar cells was studied to help determine the material compositions and device dimensions needed for high efficiency solar cells. Because of the involved analysis of the fundamental equations describing solar cell operation, a general numerical device analysis program was used. A major part of the initial work was involved in modifying an existing silicon solar cell analysis program to account for the unique features of graded bandgap and heterojunction solar cells. The most successful III-V solar cells have so far been constructed in the GaAs and Gal-xAlxAs material systems; this project was concerned with such solar cells. The most efficient solar cell so far evaluated is an abrupt heterojunction cell with a pure AlAs layer at the surface with a GaAs substrate. The predicted efficiency for this cell is slightly larger than that of a graded bandgap Gal-xAlxAs solar cell.

Hauser, J. R.↗

The spectral analysis of an aero-engine assembly incorporating a squeeze-film damper

Aero-engine structures have very low inherent damping and so artificial damping is often introduced by pumping oil into annular gaps between the casings and the outer races of some or all of the rolling-element bearings supporting the rotors. The thin oil films so formed are called squeeze film dampers and they can be beneficial in reducing rotor vibration due to unbalance and keeping to reasonable limits the forces transmitted to the engine casing. However, squeeze-film dampers are notoriously non-linear and as a result can introduce into the assembly such phenomena as subharmonic oscillations, jumps and combination frequencies. The purpose of the research is to investigate such phenomena both theoretically and experimentally on a test facility reproducing the essential features of a medium-size aero engine. The forerunner of this work was published. It was concerned with the examination of a squeeze-film damper in series with housing flexibility when supporting a rotor. The structure represented to a limited extent the essentials of the projected Rolls Royce RB401 engine. That research demonstrated the ability to calculate the oil-film forces arising from the squeeze film from known motions of the bearing components and showed that the dynamics of a shaft fitted with a squeeze film bearing can be predicted reasonably accurately. An aero-engine will normally have at least two shafts and so in addition to the excitation forces which are synchronous with the rotation of one shaft, there will also be forces at other frequencies from other shafts operating on the squeeze-film damper. Theoretical and experimental work to consider severe loading of squeeze-film dampers and to include these additional effects are examined.

Holmes, R.↗

Axolotl: a scalable genomics library based on Apache Spark (Axolotl) v1.0.0

Axolotl is a Python library for scalable distributed genome and metagenome data analysis. Existing tools and systems that we rely on are struggling to keep up with the rapid explosion of genomic data. Compounding this issue, developing scalable solutions require a steep learning curve in parallel programming, which presents a barrier to academic researchers. While we do have scalable solutions for specific tasks, we lack comprehensive, end-to-end solutions. It's this gap in our toolkit that we aim to address with Axolotl. The Axolotl library is built for easy parallel processing, efficiently handling multiple tasks or large datasets simultaneously, and scaling up to meet the demands of extensive genomic data analysis.

Wang, Zhong↗

X ray observations of late-type stars using the ROSAT all-sky survey

The ROSAT mission made the first x ray survey of the entire sky using an imaging detector. Although ROSAT is a joint NASA/German project and involves direct American participation during its second phase of pointed observations, the all-sky survey remains the sole property of the German investigators. NASA grant represented the first use of ROSAT data analysis funds to support direct American participation in the ROSAT all-sky survey. The project involved a collaborative agreement between the Joint Institute for Laboratory Astrophysics (JILA) and the Max-Planck-Institut fur Extraterrestrische Physik (MPE) where JILA supplied MPE with a post-doctoral research associate with experience in the field of stellar (coronal) x ray emission to work within their ROSAT group. In return, members of the cool star research group at JILA were given the opportunity to collaborate on projects involving ROSAT all-sky survey data. Both sides have benefitted (and still benefit) from this arrangement since MPE suffers from a shortage of researchers who are interested in x ray emission from 'normal' stars and white dwarfs. MPE has also drawn upon experience in optical identification of x ray sources from the Einstein Extended Medium Sensitivity Survey in planning their own identification strategies for the ROSAT all-sky survey. The JILA cool stars group has benefitted since access to all-sky survey data has expanded the scope of their already extensive research programs involving multiwavelength observations of late-type stars. ROSAT was successfully launched on 1 June 1990 and conducted the bulk of the survey from 30 July 1990 to 25 January 1991. Data gaps in the survey have subsequently been made up. At the time of this writing (February 1992), the survey data have been processed once with the Standard Analysis Software System (SASS). A second processing will soon begin with improvements made to the SASS to correct errors and bugs found while carrying out scientific projects with data from the first processing. We outline the major research activities of Dr. Fleming over the past year (detailed accounts of his activities during the first two years of this grant can be found in the first-year and second-year status reports on this grant). Regarding the three specific projects which were proposed in the original proposal, two of them (White Dwarfs and Late M Dwarfs) are near completion. The results are described in two conference proceedings which are appended.

Linsky, Jeffrey L.↗

Photoinduced Dirac semimetal in ZrTe5

Abstract Novel phases of matter with unique properties that emerge from quantum and topological protection present an important thrust of modern research. Of particular interest is to engineer these phases on demand using ultrafast external stimuli, such as photoexcitation, which offers prospects of their integration into future devices compatible with optical communication and information technology. Here, we use MeV Ultrafast Electron Diffraction (UED) to show how a transient three-dimensional (3D) Dirac semimetal state can be induced by a femtosecond laser pulse in a topological insulator ZrTe 5 . We observe marked changes in Bragg diffraction, which are characteristic of bond distortions in the photoinduced state. Using the atomic positions refined from the UED, we perform density functional theory (DFT) analysis of the electronic band structure. Our results reveal that the equilibrium state of ZrTe 5 is a topological insulator with a small band gap of ~ 25 meV, consistent with angle-resolved photoemission (ARPES) experiments. However, the gap is closed in the presence of strong spin-orbit coupling (SOC) in the photoinduced transient state, where massless Dirac fermions emerge in the chiral band structure. The time scale of the relaxation dynamics to the transient Dirac semimetal state is remarkably long, τ ~ 160 ps, which is two orders of magnitude longer than the conventional phonon-driven structural relaxation. The long relaxation is consistent with the vanishing density of states in Dirac spectrum and slow spin-repolarization of the SOC-controlled band structure accompanying the emergence of Dirac fermions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗