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At least 361 records · Page 20

Radiological Safety Analysis Computer (RSAC 7.2) Presentation

This presentation will be for the graduate seminar class for the University of New Mexico. We will discuss the Radiological Safety Analysis Computer (RSAC) version 7.2, a critical tool in radiological consequence analysis within the nuclear safety domain. We will begin with an introduction to radiological consequence analysis and the importance of dose modeling in nuclear safety, referencing key regulatory frameworks such as DOE-STD-3009 and 10 CFR 20. The presentation will provide an overview of RSAC, including its history, primary functions, and the inputs and outputs involved in its calculations. A detailed examination of RSAC's atmospheric dispersion model, based on the Gaussian plume methodology, will be presented, highlighting how meteorological factors influence the results. We will discuss the regulatory alignment of RSAC with DOE and NRC guidelines, emphasizing the assumptions required for compliance and the balance between conservative and realistic inputs. The presentation will also address the limitations and assumptions inherent in RSAC, comparing it with other consequence analysis codes like MACCS, HotSpot, and RASCAL. An example RSAC run will be demonstrated, showcasing a hypothetical accident scenario and interpreting the resulting dose calculations. Finally, we will introduce new ideas to enhance the current RSAC framework. This future work aims to provide multi-industry adaptability and integration with new dispersion models, addressing the evolving needs of DOE and NRC. The presentation will conclude with a discussion on RSAC's ongoing role in nuclear safety and the opportunities for future innovation.

computer program↗

Simple Monomers for Precise Polymer Functionalization During Ring-Opening Metathesis Polymerization

Controlling the monomer sequence of synthetic polymers is a grand challenge in polymer science. Conventional sequence control has been achieved in dispersed polymers by exploiting the kinetic tendencies of monomers and their order of addition. While the sequence of blocks in multiblock copolymers can be readily tuned using sequential addition of monomers (SAM), control over the sequence distribution is eroded as the targeted block size approaches a single monomer unit (i.e., X n ~ 1) due to the stochastic nature of chain-growth reactions. Thus, unique monomers are needed to ensure precise single additions. Herein, we investigate common classes of cyclic olefin monomers for ring-opening metathesis polymerization (ROMP) to identify monomers for single unit addition during sequential monomer addition synthesis. Through careful analysis of polymerization kinetics, we find that easily synthesized oxanorbornene imide monomers are suitable for single-addition reactions. With the identified monomers, we demonstrate the synthesis of multiblock copolymers containing up to three precise functionalization sites and singly cross-linked four-armed star copolymers. In conclusion, we envision that expanded kinetic analyses of monomer reactivities in ROMP reactions will enable novel polymer synthesis capabilities such as the autonomous synthesis of sequence-defined polymers or one-shot multiblock copolymer syntheses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models

Abstract Background A mechanistic understanding of the spread of SARS-CoV-2 and diligent tracking of ongoing mutagenesis are of key importance to plan robust strategies for confining its transmission. Large numbers of available sequences and their dates of transmission provide an unprecedented opportunity to analyze evolutionary adaptation in novel ways. Addition of high-resolution structural information can reveal the functional basis of these processes at the molecular level. Integrated systems biology-directed analyses of these data layers afford valuable insights to build a global understanding of the COVID-19 pandemic. Results Here we identify globally distributed haplotypes from 15,789 SARS-CoV-2 genomes and model their success based on their duration, dispersal, and frequency in the host population. Our models identify mutations that are likely compensatory adaptive changes that allowed for rapid expansion of the virus. Functional predictions from structural analyses indicate that, contrary to previous reports, the Asp 614 Gly mutation in the spike glycoprotein (S) likely reduced transmission and the subsequent Pro 323 Leu mutation in the RNA-dependent RNA polymerase led to the precipitous spread of the virus. Our model also suggests that two mutations in the nsp13 helicase allowed for the adaptation of the virus to the Pacific Northwest of the USA. Finally, our explainable artificial intelligence algorithm identified a mutational hotspot in the sequence of S that also displays a signature of positive selection and may have implications for tissue or cell-specific expression of the virus. Conclusions These results provide valuable insights for the development of drugs and surveillance strategies to combat the current and future pandemics.

59 BASIC BIOLOGICAL SCIENCES↗

A Eulerian three-fluid flow framework for the study of fuel dispersal behavior under loss-of-coolant accident conditions

As the nuclear industry explores new fuel designs to accommodate increased burnup, studying fuel behavior during loss-of-coolant accidents is essential for ensuring the safe operation of light-water reactors. Here, this study presents a computational model to simulate the intricate three-phase flow dynamics of fuel dispersal following cladding breach, where solid fuel particles and carrier fission gases interact with the surrounding liquid or gas medium. The model utilizes a Eulerian three-fluid framework to depict the phase interaction within interpenetrating continua, treating fragmented fuel as granular material. Closure relationships for bulk-flow properties of the solid phase and detailed interfacial exchange terms in high-temperature, high-speed gas-solid-liquid flow scenarios are proposed. The model was validated using adiabatic experimental results in the literature, focusing on characterizing fuel dispersal behavior during loss-of-coolant accidents conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched probability density functions reported in experimental studies. Key highlights of this study include the theoretical description of a coupled three-phase flow with phase change, interpretation of the high-pressure boundary conditions and insights into the transient behavior of gas-solid-liquid phase dynamics during a simulated high-speed dispersal event.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Electronic properties of single-layer CoO 2 /Au(111)

Here we report direct measurements via angle-resolved photoemission spectroscopy (ARPES) of the electronic dispersion of single-layer (SL) CoO 2 . The Fermi contour consists of a large hole pocket centered at the $\overline{\Gamma}$ point. To interpret the ARPES results, we use density functional theory (DFT) in combination with the multi-orbital Gutzwiller Approximation (DFT+GA), basing our calculations on crystalline structure parameters derived from x-ray photoelectron diffraction and low-energy electron diffraction. Our calculations are in good agreement with the measured dispersion. We conclude that the material is a moderately correlated metal. We also discuss substrate effects, and the influence of hydroxylation on the CoO 2 SL electronic structure.

36 MATERIALS SCIENCE↗

Using Complex Probability Amplitudes to Simulate Solute Transport in Composite Porous Media

Probability amplitudes are fundamental to quantum mechanics and offer robust descriptions of complicated systems, which have allowed physicists to explain behaviors inaccessible to classical physics. This article ponders how some of the same conceptual underpinnings of the mathematics used for modeling quantum systems might be applied to subsurface water resources problems and speculates how these tools could facilitate applications on quantum computers. A probability amplitude-based model for describing advective-dispersive transport in porous media using linear operators is investigated. The proposed complex valued model decomposes spreading into two “sub-continuum partial dispersion” coefficients, and this recovers classical spreading when the sum of these coefficients is the Fickian dispersion coefficient. However, the probability amplitudes have a manyto-one relationship to a probability distribution, so it embeds a level of heterogeneity into seemingly equivalent functions. Two propagators with different sub-continuum coefficients may have the same macroscopic behavior when either is considered in isolation, but when they act on the other the system’s behavior changes. Additionally, differences in the amplitudes cause a reduction in spreading as velocity correlations are disrupted, despite both propagators having identical dispersion coefficients, and this cannot be achieved using classical methods without changing the dispersion coefficient. The main point is that these amplitude-based models offer a way to embed information about the system into the propagators, instead of just “averaging it out” when making an upscaled model.

54 ENVIRONMENTAL SCIENCES↗

Ectomycorrhizal Plant-Fungal Co-invasions as Natural Experiments for Connecting Plant and Fungal Traits to Their Ecosystem Consequences

Introductions and invasions by fungi, especially pathogens and mycorrhizal fungi, are widespread and potentially highly consequential for native ecosystems, but may also offer opportunities for linking microbial traits to their ecosystem functions. In particular, treating ectomycorrhizal (EM) invasions, i.e., co-invasions by EM fungi and their EM host plants, as natural experiments may offer a powerful approach for testing how microbial traits influence ecosystem functions. Forests dominated by EM symbiosis have unique biogeochemistry whereby the secretions of EM plants and fungi affect carbon (C) and nutrient cycling; moreover, particular lineages of EM fungi have unique functional traits. EM invasions may therefore alter the biogeochemistry of the native ecosystems they invade, especially nitrogen (N) and C cycling. By identifying “response traits” that favor the success of fungi in introductions and invasions (e.g., spore dispersal and germination) and their correlations with “effect traits” (e.g., nutrient-cycling enzymes) that can alter N and C cycling (and affect other coupled elemental cycles), one may be able to predict the functional consequences for ecosystems of fungal invasions using biogeochemistry models that incorporate fungal traits. Here, we review what is already known about how EM fungal community composition, traits, and ecosystem functions differ between native and exotic populations, focusing on the example of EM fungi associated with species of Pinus introduced from the Northern into the Southern Hemisphere. We develop hypotheses on how effects of introduced and invasive EM fungi may depend on interactions between soil N availability in the exotic range and EM fungal traits. We discuss how such hypotheses could be tested by utilizing Pinus introductions and invasions as a model system, especially when combined with controlled laboratory experiments. Finally, we illustrate how ecosystem modeling can be used to link fungal traits to their consequences for ecosystem N and C cycling in the context of biological invasions, and we highlight exciting avenues for future directions in understanding EM invasion.

59 BASIC BIOLOGICAL SCIENCES↗

Variations in GARS powder microstructure as a function of powder chemistry and particle size

The properties of metal produced through powder metallurgy depends on the feedstock used. Powders produced via gas atomization reaction synthesis (GARS) are used to produce oxide dispersion strengthened alloys. The desired powder size range can vary for each consolidation technique. However, powder microstructure also can vary with powder particle size, which in turn can impact the microstructure and properties of the consolidated parts. In this study, GARS powders are characterized via inductively coupled plasma mass spectroscopy, inert gas fusion, and high-resolution x-ray diffraction to determine variations in elemental and phase compositions. Transmission electron microscopy was used to understand microstructure variations as a function of chemistry and size. Across the three batches tested intermetallic content was 0.73–1.35 wt% in the 0-20 μm powder batch and increased to 2.46–3.80 wt% in the coarse 45-106 μm batch. Across all batches, volume percent of surface oxidation decreased with powder diameter, with volume percents within the range of 0.75–1.2 % across 10 μm powder particles, and below 0.4 % across coarse powder particles approximately 100 μm in diameter. These observations were supported by inert gas fusion measurements. However, the oxide layer was thicker in coarse powder particles due to a slower cooling rate. Increasing oxygen content in atomization gas to 2000 ppm and adding yttrium increased both the surface oxidation content and yttrium intermetallic content. Lastly, intermetallic phases within the powder coarsened with powder size. Intermetallic morphology changed from fine spherical intermetallic and columnar dendritic growth to a cellular structure with finer spherical intermetallic, to coarse irregular intermetallic and intermetallic along grain boundaries as a result of slower cooling rate and solidification rate in coarse powder particles. Furthermore, the addition of zirconium does not appear to significantly change intermetallic morphology, but the composition changed from a Y-Fe rich intermetallic to a Y-Zr-Fe intermetallic.

42 ENGINEERING↗

Higher-order SPOP assembly reveals a basis for cancer mutant dysregulation

The speckle-type POZ protein (SPOP) functions in the Cullin3-RING ubiquitin ligase (CRL3) as a receptor for the recognition of substrates involved in cell growth, survival, and signaling. SPOP mutations have been attributed to the development of many types of cancers, including prostate and endometrial cancers. Prostate cancer mutations localize in the substrate-binding site of the substrate recognition (MATH) domain and reduce or prevent binding. However, most endometrial cancer mutations are dispersed in seemingly inconspicuous solvent-exposed regions of SPOP, offering no clear basis for their cancer-causing and peculiar gain-of-function properties. Herein, we present the first structure of SPOP in its oligomeric form, uncovering several new interfaces important for SPOP self-assembly and normal function. Given that many previously unaccounted-for cancer mutations are localized in these newly identified interfaces, we uncover molecular mechanisms underlying dysregulation of SPOP function, with effects ranging from gross structural changes to enhanced self-association, and heightened stability and activity.

59 BASIC BIOLOGICAL SCIENCES↗

Low-Energy Ion Scattering Intensities from Supported Nanoparticles: The Spherical Cap Model

Supported nanoparticles are of great importance to many technologies like fuel processing and chemical synthesis using catalysts and electrocatalysts, energy storage and generation using fuel cells and batteries, electrochemistry, magnetic information storage, and more. Low-energy ion scattering spectroscopy (LEIS) with noble gas ions like He+ is a powerful tool for the characterization of nanoparticles dispersed across flat support surfaces due to its ability to probe the elemental composition in the topmost atomic layer of a surface, providing quantitative information regarding the size and number density of nanoparticles. In this work, we present a derivation of the LEIS intensities expected from nanoparticles and the support material as a function of the average particle size, their number per unit area, and their contact angle with the support when modeled as spherical caps of the nanoparticle material dispersed over the surface of a flat support. The model assumes that the ion intensities are determined only by the physical blocking of linear ion trajectories and independent of the tilt angle of the local surface relative to the incident and scattered ion directions, an assumption we support by quantitative modeling of published data which tested tilt-angle effects. The model is a generalization to arbitrary contact angles of the hemispherical cap model, which assumes 90° contact angle and has been widely used to model spectroscopic signals in LEIS (and also in Auger and photoelectron spectroscopies) during nanoparticle growth. Here, this new model quantitatively reveals how LEIS signals are sensitive not only to the diameter and number density of the nanoparticle but also to their contact angle (or height/diameter ratio). With the use of additional data (e.g., from microscopy or adsorption microcalorimetry), the model presented here will enable more accurate determination of the average size, shape, and number density of supported nanoparticles based on LEIS intensity measurements.

99 GENERAL AND MISCELLANEOUS↗

magnetoARPES: Angle Resolved Photoemission Spectroscopy with magnetic field control

Angle-Resolved Photoemission Spectroscopy (ARPES) is a premier technique for understanding the electronic excitations in conductive, crystalline matter, in which the induced photocurrent is collected and dispersed in energy and angle of emission to reveal the energy- and momentum-dependent single particle spectral function A (k,ω). So far, ARPES in a magnetic field has been precluded due to the need to preserve the electron paths between the sample and detector. Here, in this paper we report progress towards “magnetoARPES”, a variant of ARPES that can be conducted in a magnetic field. It is achieved by applying a microscopic probe beam (≲10 μm) to a thinned sample mounted upon a special sample holder that generates magnetic field confined to a thin layer near the sample surface. In this geometry we could produce ARPES in magnetic fields up to around ±100 mT. The magnetic fields can be varied from purely in-plane to nearly purely out-of-plane, by scanning the probe beam across different parts of the device. We present experimental and simulated data for graphene to explore the aberrations induced by the magnetic field. These results demonstrate the viability of the magnetoARPES technique for exploring symmetry breaking effects in weak magnetic fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multi-modal characterization methods of solid-electrolyte interphase in silicon-graphite composite electrodes

Composite silicon-graphite (Si-Gr) anodes can improve battery energy density, due to Si's high gravimetric capacity, while mitigating mechanical degradation of the anode and solid-electrolyte interphase (SEI) caused by Si volumetric expansion. Optimizing these anodes is challenging, in part due to difficulty characterizing the SEI structure and composition. In this work, we present multi-modal characterization of the SEI on composite Si-Gr anodes to relate SEI chemical composition and structure to functional properties. Discrepancies in elemental concentrations from X-ray photoelectron spectroscopy, Auger electron spectroscopy, and energy-dispersive X-ray spectroscopy (EDS) are attributed to varying information depth and lateral resolution of the individual probes. However, by combining quantitative composition information with spatially resolved element mapping from scanning transmission electron microscopy, EDS, and electron energy loss spectroscopy, a holistic picture of the SEI emerges. We observe the bilayer SEI structure and a direct correlation between elemental Li and F, suggesting that most Li in the SEI exists as lithium fluoride (LiF). Further, LiF concentration is directly proportional to the maximum SEI resistivity, as determined by scanning spreading resistance microscopy. Lastly, there is an inverse relationship between lithium carbonate and LiF concentration in the SEI, providing insight into the detailed chemistry of SEI formation and evolution.

25 ENERGY STORAGE↗

Designing Porous Ion Emitters for Thermal Ionization Mass Spectrometry: Evaluating Metal-Organic Frameworks

In this work we describe the first exploration of metal-organic frameworks (MOFs) as ‘next generation’ ion emitters for thermal ionization mass spectrometry (TIMS). MOFs were identified as promising candidates for this application given the synthetic control over their desired structural properties. This tunability results in well-ordered, high surface area, high porosity frameworks with targeted sorption affinities. Here we explored an aluminum-based, bipyridine-containing MOF (MOF-253) with and without incorporating the high work function metal, rhenium (Re). After analysis of a Nd-bearing MOF, we hypothesized that the well-dispersed, sponge-like interconnected network of the degraded structure would enhance Nd ionization more than traditional TIMS loading activators (i.e., phosphoric acid). Compared to filaments loaded with phosphoric acid that require an additional benzene carburization step, the Nd ionization efficiencies (atoms detected relative to atoms loaded) for heated filaments loaded with MOF-253 were similar (~1%). Electron microscopy after TIMS analysis demonstrated that the MOF was retained on the filament and, as hypothesized, preserved sub-micron porosity post analysis. While these results are preliminary, they demonstrate that MOFs have potential to enhance ionization and exceed the performance of traditional loading techniques by forming nano-porous ion emitters (nano-PIEs). Thus, further experimentation is likely to exceed this performance through more specific selection of the base MOF structure and modifications to porosity and composition. This work represents a novel application of MOFs and a next step in the pursuit of advanced thermal ionization with potential to expand across the periodic table.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bulk Fermi surfaces of the Dirac type-II semimetallic candidate NiTe 2

Here, we present a study on the Fermi surface of the Dirac type-II semimetallic candidate NiTe 2 via the temperature and angular dependence of the de Haas–van Alphen (dHvA) effect measured in single crystals grown through Te flux. In contrast to its isostructural compounds like PtSe 2 , band-structure calculations predict NiTe 2 to display a tilted Dirac node very close to its Fermi level that is located along the Γ to A high-symmetry direction within its first Brillouin zone. The angular dependence of the dHvA frequencies is found to be in agreement with the first-principles calculations when the electronic bands are slightly shifted with respect to the Fermi level (ε F ), and therefore provide support for the existence of a Dirac type-II node in NiTe 2 . Nevertheless, we observed mild disagreements between experimental observations and density functional theory (DFT) calculations as, for example, nearly isotropic and light experimental effective masses. This indicates that the dispersion of the bands is not well captured by DFT. Despite the coexistence of Dirac-like fermions with topologically trivial carriers, samples of the highest quality display an anomalous and large either linear or sublinear magnetoresistivity. Finally, this suggests that Lorentz invariance breaking Dirac-like quasiparticles dominate the carrier transport in this compound.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

PET Imaging of Leg Arteries for Determining the Input Function in PET/MRI Brain Studies Using a Compact, MRI-Compatible PET System

In this work, we used a compact, high-resolution, and magnetic resonance imaging (MRI)-compatible positron emission tomography (PET) camera (VersaPET) to assess the feasibility of measuring the image-derived input function (IDIF) from arteries in the leg with the ultimate goal of enabling fully quantitative PET brain imaging without blood sampling. We used this approach in five 18 F-FDG PET/MRI brain studies in which the input function was also acquired using the gold standard of serial arterial blood sampling. After accounting for partial volume, dispersion, and calibration effects, we compared the metabolic rates of glucose (MRglu) quantified from VersaPET IDIFs in 80 brain regions to those using the gold standard and achieved a bias and variability of <5% which is within the range of reported test-retest values for this type of study. We also achieved a strong linear relationship (R 2 >0.97) against the gold standard across regions. The results of this preliminary study are promising and support further studies to optimize methods, validate in a larger cohort, and extend to the modeling of other radiotracers.

47 OTHER INSTRUMENTATION↗

Proton and electron RLA optics design

We describe optics designs of the key components of proton and electron Recirculating Linear Accelerators (RLAs). They are presented in the context of a high-power hadron accelerator being considered at ORNL and a CEBAF electron energy doubling study, FFA@CEBAF, being developed at Jefferson Lab. Both concepts rely on the Fixed-Field Alternating gradient (FFA) arc optics designs where multiple beam passes are transported by a single beam line. Some of the main challenges of the optics design are in synchronization and orbital and linear optics match of the individual passes with the linac straight. To minimize the complexity of the matching sections and make them more practical, it is preferable to complete as much of the orbital and optical match as possible within a single beam line using the FFA approach. The adiabatic matching technique proposed earlier is one such solution, but it requires a large number of cells. We present a much shorter matching section design based on another approach. A compact dog-leg-type section of several bending dipoles and quadrupoles is used to suppress the orbital offset and dispersion coming out of a periodic cell. Additional quadrupoles are used in the section to keep the beta functions under control and simplify their subsequent match to the linac. Initial beam tracking results are presented.

Benesch, J.↗

Survey and Assessment of Computational Capabilities for Advanced (Non-LWR) Reactor Mechanistic Source Term Analysis.

A vital part of the licensing process for advanced (non-LWR) nuclear reactor developers in the United States is the assessment of the reactor’s source term, i.e., the potential release of radionuclides from the reactor system to the environment during normal operations and accident sequences. In comparison to source term assessments which follow a bounding approach with conservative assumptions, a mechanistic approach to modeling radionuclide transport, which realistically accounts for transport and retention phenomena, is expected to be used for advanced reactor systems. As the designs of advanced reactors increase in maturity and progress towards licensing, there is a need to advance modeling and simulation capabilities in analyzing the mechanistic source term (MST) of a prospective reactor concept. In the present work, a survey is provided of existing computational capabilities for the modeling of advanced reactors MSTs. The following reactors are considered: high temperature gas reactors (HTGR); molten salt reactors (MSR) which include salt-fueled reactors and fluoride salt-cooled high temperature reactors (FHR); and sodium- and lead-cooled fast reactors (SFR, LFR). A review of relevant codes which may be useful in providing information to MST analyses is also completed, including codes that have been used for source term analyses of LWRs, as well as those being developed for other aspects of advanced reactor system modeling such as reactor physics, thermal hydraulics, and chemistry. A discussion of MST modeling capabilities for each reactor type is provided with additional focus on important phenomena and functional requirements. Additionally, a comprehensive survey is provided of tools for consequence modeling such as atmospheric transport and dispersion (ATD).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluation of assumptions made by Hygroscopic Tandem Differential Mobility Analyzer inversion routines

The Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA) measures the hygroscopicity of atmospheric particles, and many atmospheric processes that change this hygroscopicity also change the atmospheric size distribution. Two assumptions made during H-TDMA inversion create spurious hygroscopic trends as a function of the changing inlet size distribution. These two assumptions—that the particles exiting the first Differential Mobility Analyzer (DMA1) are singly charged and that the inlet size distribution has a slope of zero (flat)— generate Multi-Charge Dispersion (MCD) bias and Slope bias, respectively. First, we use a model, named TAO, to show that the inlet size distribution could theoretically change the measured ammonium sulfate hygroscopicity by 10%–20% as a function of diameter or experimental time with no change in relative humidity. Secondly, we show experimentally that aerosol emitted from the flaming combustion of grass creates MCD bias. Here, in this experiment, we measure the CPC response of the first three charges and invert these responses using a new routine named Junior. Junior's inversion of each charge shows that one growth factor distribution describes all measured diameters (no growth dependence on diameter). As in the modeling study above, previous publications of this aerosol system, using traditional inversion assumptions, report a decrease in hygroscopicity as DMA1 diameter increases. Unlike traditional inversions, Junior's inversion does not assume the particles are singly charged nor does it make the flat inlet size distribution assumption. Instead, both the inlet size distribution and each charge's CPC response are measured quantities. Thus, the discrepancy between our inversion results and previous publications is likely due to the traditional inversion routine assumptions. This underscores the importance for accounting for Slope and MCD bias during inversions. Experimental results should be carefully analyzed when reporting hygroscopic trends with respect to diameter or experimental time when using the traditional inversion assumptions.

42 ENGINEERING↗