Nguyen, Vivian | Search NASA

DOE OSTI2022

Synthesis, Crystal and Electronic Structures, Nonlinear Optical Properties, and Magnetic Properties of Two Thiophosphates: KInP 2 S 7 and KCrP 2 S 7

Two thiophosphates, KInP 2 S 7 and KCrP 2 S 7 , were structurally characterized without investigating any optical properties. Herein in this work, KInP 2 S 7 and KCrP 2 S 7 were revisited to investigate their optical and magnetic properties, respectively. Pure polycrystalline samples and crystals of KInP 2 S 7 and KCrP 2 S 7 were grown by high temperature solid state reactions, where mm-sized crystals of KCrP 2 S 7 were collected. KCrP 2 S 7 is isostructural to KInP 2 S 7 , which features a layered structure. KInP 2 S 7 and KCrP 2 S 7 possess close relationship to the layered thiophosphate M 2 P 2 S 6 (M = Fe, Co, Zn, etc.). The bonding pictures of KInP 2 S 7 were studied using the electron localization function (ELF) coupled with crystal orbital Hamilton population (COHP) calculations. The intrinsically distorted [PS 4 ] tetrahedra and [InS 6 ] octahedra are made by strong covalent P-S interactions and ionic In-S interactions, respectively. Electronic structure analysis confirmed that the optical properties of KInP 2 S 7 are mainly contributed to by [PS 4 ] tetrahedra together with small amounts of the contributions coming from [InS 6 ] octahedra. Magnetic measurement on mm-sized crystals of KCrP 2 S 7 verified that there is an antiferromagnetic transition around 21 K, and the Cr atoms are trivalent. KInP 2 S 7 is predicated to be an indirect bandgap semiconductor of 2.38 eV, which is confirmed by the UV-Vis measurement of 2.4(1) eV. KInP 2 S 7 is not a type-I phase-matching material and exhibits moderate second harmonic generation (SHG) response (0.51 × AgGaS 2 , sample of particle size of 100 µm). The laser damage threshold (LDT) of KInP 2 S 7 is very high of 5.2 × AgGaS 2 . Bandgap engineering were undergone to enhance the SHG response of KInP 2 S 7 .

36 MATERIALS SCIENCE↗

DOE OSTI2018

Creating an Interprocedural Analyst-Oriented Data Flow Representation for Binary Analysts (CIAO)

National security missions require understanding third-party software binaries, a key element of which is reasoning about how data flows through a program. However, vulnerability analysts protecting software lack adequate tools for understanding data flow in binaries. To reduce the human time burden for these analysts, we used human factors methods in a rolling discovery process to derive user-centric visual representation requirements. We encountered three main challenges: analysis projects span weeks, analysis goals significantly affect approaches and required knowledge, and analyst tools, techniques, conventions, and prioritization are based on personal preference. To address these challenges, we initially focused our human factors methods on an attack surface characterization task. We generalized our results using a two-stage modified sorting task, creating requirements for a data flow visualization. We implemented these requirements partially in manual static visualizations, which we informally evaluated, and partially in automatically generated interactive visualizations, which have yet to be integrated into workflows for evaluation. Our observations and results indicate that 1) this data flow visualization has the potential to enable novel code navigation, information presentation, and information sharing, and 2) it is an excellent time to pursue research applying human factors methods to binary analysis workflows.

42 ENGINEERING↗