Engineering topics
Publications and source records attributed to Kim, H..
The alphas sublibrary aims to describe nuclear reactions between incident alpha particles and different nuclei. For ENDF/B-VIII.1, the LLNL ECPL evaluation for 6Li, and the JENDL-based NNL evaluations of 9 Be and 16,17 O were adopted. Also, there were minor fixes done to 4 He.
The atomic relaxation sublibrary aims to describe atomic binding energies. For ENDF/B-VIII.1 we adopted the EPICS2023 EADL evaluations.
The decay sublibrary aims to describe all known spontaneous decays and branching ratios for all nuclei across the nuclide chart. ENDF/B-VIII.1 remains unchanged from ENDF/B-VIII.0 for the decay sublibrary.
The deuterons sublibrary aims to describe nuclear reactions between incident deuteron particles and different nuclei. For ENDF/B-VIII.1, we adopted additions and corrections to the ENDF/B-VIII.0 d+t file, as well as new LANL evaluation updates for 3 He and 6 Li.
The electrons sublibrary aims to describe electron-atomic cross section data, corresponding to the interaction between electrons and the different atoms. For ENDF/B-VIII.1 we adopted the EPICS2023 EEDL evaluations.
The ENDF/B-VIII.1 release is the newest evaluated nuclear data library produced, distributed, and recommended by CSEWG for use in nuclear science and technology applications. Among the many key advances, relative to the previous version ENDF/B-VIII.0, are: re-evaluation of 239Pu file by a joint international effort; updated 16,18O, 19F, 28-30Si, 50-54Cr, 55Mn, 54,56,57Fe, 63,65Cu, 139La, 233,235,238U, and 240,241Pu neutron nuclear data by the IAEA-coordinated INDEN collaboration; significant changes for 3He, 6Li, 9Be, 51V, 88Sr, 103Rh, 140,142Ce, Dy, 181Ta, Pt, 206-208Pb, and 234,236U neutron data; new nuclear data for the photo-nuclear, being 196 adopted from the IAEA2019 Photonuclear Data Library and one new file from JENDL-5; and new evaluations for the charged-particle and atomic sublibraries. Numerous thermal neutron scattering kernels were re-evaluated or provided for the very first time. Additionally, new covariance testing was implemented. ENDF/B-VIII.1 reduced bias in the simulations of many integral experiments with particular progress noted for fluorine, copper and stainless steel containing benchmarks. Data issues which had hindered the deployment of ENDF/B-VIII.0 for commercial nuclear power applications in high burn-up situations, were addressed. ENDF/B-VIII.1 data are distributed in both ENDF-6 and GNDS formats.
The photonuclear sublibrary aims to describe nuclear reactions between incident gamma particles and different nuclei. For ENDF/B-VIII.1, we adopted around 200 evaluations from the IAEA Coordinated Research Project (CRP) on photonuclear data while, for a few select mission-critical materials, evaluations from ENDF/B-VIII.0 were maintained. Additionally, many fixes to many files were implemented. Finally, ENDF/B-VIII.1 includes a new photonuclear file, 242 Pu, which was adopted from JENDL-5.0.
The Helium-3 (Helions) sublibrary aims to describe nuclear reactions between incident 3 He particles and different nuclei. For ENDF/B-VIII.1, we adopted a new 4He evaluation from the INDEN collaboration and the LLNL ECPL evaluation for 7 Li.
The neutrons sublibrary aims to describe nuclear reactions between incident neutron particles and different nuclei. For ENDF/B-VIII.1, many neutron files were re-evaluated or received major changes. A new 239Pu evaluation was jointly-produced by IAEA, LANL, LLNL and ORNL bringing important updates to fission neutron multiplicity, Prompt Fission Neutron Spectrum, resonance and fast regions. Around one third of the new neutron evaluations were performed as part of the INDEN collaboration, including 16,18 O, 19 F, 28,29,30 Si, 63,65 Cu, 50,51,52,53,54 Cr, 55 Mn, 54,56,57 Fe, 139 La, 233,235,238 U, 240,241 Pu. Important non-INDEN evaluations include 234,236 U, 206,207,208 Pb, 181 Ta, 88 Sr, 140,142 Ce, Pt and Dy isotopes, and many others. Also, dosimetry reactions from IRDFF-II were adopted for many materials.
The neutron-induced fission yields (NFY) sublibray aims to describe fission yields in neutron-induced reactions. For ENDF/B-VIII.1, there were no new fission yields complete evaluations. However, an important fix the 241 Pu NFY file was implemented, solving a long-standing anomalous discontinuity issue accidentally introduced in ENDF/B-VI.2, decades ago. Additionally, many erroneously large uncertainties, present in NFY from ENDF/B-VIII.0, were corrected.
The photo-atomic sublibrary aims to describe atomic photon cross section data, corresponding to the interaction between photons and the different atoms. For ENDF/B-VIII.1 we adopted the EPICS2023 EPDL evaluations.
The protons sublibrary aims to describe nuclear reactions between incident proton particles and different nuclei. For ENDF/B-VIII.1, compared to ENDF/B-VIII.0, there were only evaluation updates for 4 He.
The spontaneous fission yields (SFY) sublibray aims to describe fission yields that happen spontaneous, without any incident particle. For ENDF/B-VIII.1, there were no new fission yields complete evaluations. However, many erroneously large uncertainties, present in both SFY from ENDF/B-VIII.0, were corrected.
The neutron standards sublibrary describes specific reaction cross sections, in a limited range, that are so well-known that they are used as ratios or references in other measurements. ENDF/B-VIII.1 remains unchanged from ENDF/B-VIII.0 for the neutron standards sublibrary
The thermal neutron scattering law (TSL) sublibrary aims to describe the interaction of incident neutrons at thermal or sub-thermal energies with different compound materials such fuels, moderators and special-purpose materials. In ENDF/B-VIII.1 there was a large number of new and updated TSL evaluations, including traditional moderators (light water, Beryllium metal, Beryllium Oxide, Calcium Hydride, plastics (Polystyrene and Lucite), graphite (reactor-grade and crystalline), anhydrous Hydrogen Fluoride, and heavy paraffinic oil); exotic moderators (Beryllium Carbide, Zirconium Hydride, Yttrium Hydride, Lithium-7 Hydride and Deuteride), FLiBe molten salt, structural materials and cladding (Silicon Carbide, Silicon Dioxide, Zirconium Carbide), fuels (Plutonium Dioxide, Uranium Carbide, Uranium metal, Uranium Nitride, Uranium Dioxide, Uranium Hydride), and special purpose materials. In ENDF/B-VIII.1 we also distribute alongside the evaluated files, a comma-separated file (CSV), named TSL_MAT_numbers.csv, which lists all evaluated files in the current release and their corresponding unique MAT number.
The tritons sublibrary aims to describe nuclear reactions between incident triton particles and different nuclei. For ENDF/B-VIII.1, compared to ENDF/B-VIII.0, there were only evaluation updates for 4 He.
Embedded field programmable gate array (eFPGA) technology allows the implementation of reconfigurable logic within the design of an application-specific integrated circuit (ASIC). This approach offers the low power and efficiency of an ASIC along with the ease of FPGA configuration, particularly beneficial for the use case of machine learning in the data pipeline of next-generation collider experiments. An open-source framework called "FABulous" was used to design eFPGAs using 130 nm and 28 nm CMOS technology nodes, which were subsequently fabricated and verified through testing. The capability of an eFPGA to act as a front-end readout chip was assessed using simulation of high energy particles passing through a silicon pixel sensor. A machine learning-based classifier, designed for reduction of sensor data at the source, was synthesized and configured onto the eFPGA. A successful proof-of-concept was demonstrated through reproduction of the expected algorithm result on the eFPGA with perfect accuracy. Finally, further development of the eFPGA technology and its application to collider detector readout is discussed.
The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we plan to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We also plan to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task to identify pan-coronavirus protease inhibitors such as SARS-CoV-2. While the overall goals and milestones remain consistent with the original proposal, certain technical details have been modified, which we will describe in this report.