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At least 289 records · Page 16

Carbodiimide‐Driven Toughening of Interpenetrated Polymer Networks

Abstract Recent work has demonstrated that temporary crosslinks in polymer networks generated by chemical “fuels” afford materials with large, transient changes in their mechanical properties. This can be accomplished in carboxylic‐acid‐functionalized polymer hydrogels using carbodiimides, which generate anhydride crosslinks with lifetimes on the order of minutes to hours. Here, the impact of the polymer network architecture on the mechanical properties of transiently crosslinked materials was explored. Single networks (SNs) were compared to interpenetrated networks (IPNs). Notably, semi‐IPN precursors that give IPNs on treatment with carbodiimide give much higher fracture energies (i.e., resistance to fracture) and superior resistance to compressive strain compared to other network architectures. A precursor semi‐IPN material featuring acrylic acid in only the free polymer chains yields, on treatment with carbodiimide, an IPN with a fracture energy of 2400 J/m 2 , a fourfold increase compared to an analogous semi‐IPN precursor that yields a SN. This resistance to fracture enables the formation of macroscopic complex cut patterns, even at high strain, underscoring the pivotal role of polymer architecture in mechanical performance.

Rajawasam, Chamoni W. H.↗

Secure Collaborative Environment for Seamless Sharing of Scientific Knowledge

In a secure collaborative environment, tera-bytes of data generated from powerful scientific instruments are used to train secure machine learning (ML) models on exascale computing systems, which are then securely shared with internal or external collaborators as cloud-based services. Devising such a secure platform is necessary for seamless scientific knowledge sharing without compromising individual, or institute-level, intellectual property and privacy details. By enabling new computing opportunities with sensitive data, we envision a secure collaborative environment that will play a significant role in accelerating scientific discovery. Several recent technological advancements have made it possible to realize these capabilities. In this paper, we present our efforts at ORNL toward developing a secure computation platform. We present a use case where scientific data generated from complex instruments, like those at the Spallation Neutron Source (SNS), are used to train a differential privacy enabled deep learning (DL) network on Summit, which is then hosted as a secure multi-party computation (MPC) service on ORNL’s Compute and Data Environment for Science (CADES) cloud computing platform for third-party inference. In this feasibility study, we discuss the challenges involved, elaborate on leveraged technologies, analyze relevant performance results and present the future vision of our work to establish secure collaboration capabilities within and outside of ORNL.

Yoginath, Srikanth↗

Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning

We present Adrastea, an efficient FPGA design environment for developing scientific machine learning applications. FPGA development is challenging, from deployment, proper toolchain setup, programming methods, interfacing FPGA kernels, and more importantly, the need to explore design space choices to get the best performance and area usage from the FPGA kernel design. Adrastea provides an automated and scalable design flow to parameterize, implement, and optimize complex FPGA kernels and associated interfaces. We show how virtualization of the development environment via virtual machines is leveraged to simplify the setup of the FPGA toolchain while deploying the FPGA boards and while scaling up the automated design space exploration to leverage multiple machines concurrently. Adrastea provides an automated build and test environment of FPGA kernels. By exposing design space hyper-parameters, Adrastea can automatically search the design space in parallel to optimize the FPGA design for a given metric, usually performance or area. Adrastea simplifies the task of interfacing with the FPGA kernels with a simplified interface API. To demonstrate the capabilities of Adrastea, we implement a complex random forest machine learning kernel with 10,000 input features while achieving extremely low computing latency without loss of prediction accuracy, which is required by a scientific edge application at SNS. We also demonstrate Adrastea using an FFT kernel and show that for both applications Adrastea is able to systematically and efficiently evaluate different design options, which reduced the time and effort required to develop the kernel from months of manual work to days of automatic builds.

Young, Aaron↗

Reduced order models for Lagrangian hydrodynamics

It is reported, as a mathematical model of high-speed flow and shock wave propagation in a complex multimaterial setting, Lagrangian hydrodynamics is characterized by moving meshes, advection-dominated solutions, and moving shock fronts with sharp gradients. These challenges hinder the existing projection-based model reduction schemes from being practical. We develop several variations of projection-based reduced order model techniques for Lagrangian hydrodynamics by introducing three different reduced bases for position, velocity, and energy fields. A time-windowing approach is also developed to address the challenge imposed by the advection-dominated solutions. Lagrangian hydrodynamics is formulated as a nonlinear problem, which requires a proper hyper-reduction technique. Therefore, we apply the over-sampling DEIM and SNS approaches to reduce the complexity due to the nonlinear terms. Finally, we also present both a posteriori and a priori error bounds associated with our reduced order model. We compare the performance of the spatial and time-windowing reduced order modeling approaches in terms of accuracy and speed-up with respect to the corresponding full order model for several numerical examples, namely Sedov blast, Gresho vortices, Taylor-Green vortices, and triple-point problems.

97 MATHEMATICS AND COMPUTING↗

Data-Driven Modeling of a High Capacity Cryogenic System for Control Optimization

The Cryogenic Moderator System (CMS) is responsible for maintaining a steady flow of cold neutrons for numerous physics experiments at the Spallation Neutron Source (SNS) in Oak Ridge National Laboratory (ORNL). Sudden losses in beam power, known as beam trips, cause a major disturbance to the CMS due to large step changes in cooling demands. Ongoing efforts on upgrading the neutron beam power from 1.4 to 2.0MW are expected to generate larger transients that can further strain the CMS subsystems if they are not properly controlled. To manage such disturbances, four flow valves and one electric heater are adjusted by five decentralized proportional-integral-derivative (PID) controllers. However, the original PID gains were calibrated empirically based only on tracking performance and not based on disturbance rejection. To address this issue without compromising current CMS operations, a control-oriented model was developed to recalibrate the PID controllers offline. The zero-dimensional (0-D) model was based on simple physics-based principles and data-driven system identification techniques. The CMS was broken into several subsystems for analysis, each of which corresponds to a parametric model tied to the thermodynamic states of the working fluid. The model parameters were identified using the nonlinear least squares method where the residuals were calculated from available sensor data. Simulation results show that the proposed model can capture the dynamics of the CMS at steady state and during beam trips.

Maldonado Puente, Bryan↗

Dynamic phase transformations in additively manufactured Ti-6Al-4V during thermo-mechanical gyrations

A complex interaction of process parameters, geometry and scan strategies in Additive Manufacturing (AM), can bring about spatial and temporal transients, i.e., Σ T ( x, y, z, time ), within a part. Published literature focusses on fluctuating thermal cycles on the microstructure evolution. However, the microstructural variations have not been correlated to dynamic flow behavior due to the macro- and micro-scale phenomena, i.e., accumulated plastic strains brought about by large thermal gradients, transformational strains and crystallographic misfit strains. Therefore, here we studied the mechanical response of Ti6Al4V alloys produced by AM under externally imposed controlled thermo-mechanical reversals in a Gleeble® thermo-mechanical simulator. The stress-strain behaviors were correlated to phase fractions, lattice strains, and also limited information on crystallographic texture using neutron diffraction techniques at the VULCAN Beamline at SNS, ORNL and also metallographic studies. The results are discussed and rationalized based on theories of static and dynamic phase transformations.

36 MATERIALS SCIENCE↗

Incorporating bubble growth volume feedback to improve simulation of the response of a structure containing liquid and gas to sudden energy input

The SNS target module is a stainless-steel structure that contains and directs mercury. The mercury is struck with short, intense proton pulses to create neutrons. The pulses deposit energy and cause loads on the target structure and mercury cavitation. Helium bubbles are introduced into the mercury to reduce loads and cavitation. This gas complicates the prediction of the target module’s physical response. The current method used to simulate the structural response to the proton pulse incorporates a simple but effective approach to approximate mercury cavitation effects. This method cannot account for the changes from injected non-condensable gas. The ability to model the target vessel response is a prerequisite for estimating its life. Known approaches for simulating a bubbly fluid mixture’s response are computationally expensive and impractical for detailed engineering models. A constitutive model is proposed for target mercury with injected gas bubbles, with the intent of providing more accurate mercury–vessel response behavior without the computing costs required to track individual bubbles. The model’s assumptions and a computational model embodiment are described. The bubbly mercury computational model is subjected to test problems to assess its potential utility. Here, the model was able to better predict the effect of gas on wave propagation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Improvements of pre-emptive identification of particle accelerator failures using binary classifiers and dimensionality reduction

In this paper we look at the properties of the Spallation Neutron Source (SNS) Differential Beam Current Monitor (DCM) data and various methods of data transformation to improve pre-emptive detection of machine trips. In this study, the foundation of the approach is the analysis of new underlying data and understanding various properties with the goal of faster classification, higher precision and higher recall with the aim to reduce false positives as low as required. The result of the research presented in this paper are a binary classifier capable of predicting accelerator failures with millisecond classification time, 96% precision, 58% true positive and 0% false positive rate and optimization techniques enabling real-time implementations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Ba 6 (Cu x Z y )Sn 4 S 16 (Z = Mg, Mn, Zn, Cd, In, Bi, Sn): High Chemical Flexibility Resulting in Good Nonlinear-Optical Properties

Seven acentric sulfides Ba 6 (Cu x Z y )Sn 4 S 16 (Z = Mg, Mn, Zn, Cd, In, Bi, Sn) were grown by a high-temperature salt flux method. The crystal structures of the Ba 6 (Cu x Z y )Sn 4 S 16 (Z = Mg, Mn, Zn, Cd, In, Bi, Sn) compounds were determined by single-crystal X-ray diffraction with the aid of solid-state NMR spectroscopy. The Ba 6 (Cu x Z y )Sn 4 S 16 (Z = Mg, Mn, Zn, Cd, In, Bi) compounds are isostructural and crystallize in the Ba 6 Ag 4 Sn 4 S 16 structure type. The Sn-containing compound exhibits high structural similarity to Ba 6 (Cu x Z y )Sn 4 S 16 (Z = Mg, Mn, Zn, Cd, In, Bi) with the presence of an interstitial atomic position partially occupied by Sn atoms. The chemical bonding characteristics of Ba 6 (Cu 2.9 Sn 0.4 )Sn 4 S 16 were understood with electron localization function calculations coupled with crystal orbital Hamilton population calculations. The Ba–S and Cu–S interactions are dominantly ionic, but the Sn–S interactions consist of strong covalent bonding characteristics in Ba 6 (Cu 2.9 Sn 0.4 )Sn 4 S 16 . The monovalent Cu atoms, mixed with certain metals with various oxidation states, significantly shift the optical properties of the Ba 6 (Cu x Z y )Sn 4 S 16 (Z = Mg, Mn, Zn, Cd, In, Bi) compounds. This results in a good balance between the second-harmonic-generation (SHG) response and laser damage threshold (LDT). Ba 6 (Cu 1.9 Zn 1.1 )Sn 4 S 16 possesses a high SHG response and a high LDT of 2.8 × AGS and 3 × AGS, respectively. Here, a density functional theory calculation revealed that CuS 4 and SnS 4 tetrahedra significantly contribute to the SHG response in Ba 6 (Cu 2 Mg)Sn 4 S 16 , which also confirmed that CuS 4 tetrahedra are crucial for the stability and optical properties of the Ba 6 (Cu x Z y )Sn 4 S 16 (Z = Mg, Mn, Zn, Cd, In, Bi, Sn) compounds revealed by electronic structure analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metal Sulfide Ion Exchangers: High Acid Stability of Na 2 x Mg 2 y – x Sn 4– y S 8 (NMS) and Topotactic Conversion to 2D Solid Acids with Semiconducting Character

Metal sulfide ion exchange materials (MSIEs) are of interest for nuclear waste remediation applications. Here, we report the high stability of two structurally related metal sulfide ion exchange materials, Na 2x Mg 2y–x Sn 4–y S 8 (Mg-NMS) and Na 2 SnS 3 (Na-NMS), in strongly acid media, in addition to the preparation of Na 2x Ni 2y–x Sn 4–y S 8 (Ni-NMS). Their formation progress during synthesis is studied with in-situ methods, with the target phases appearing in <15 min, reaction completion in <12 h, and high yields (75–80%). Upon contact with nitric or hydrochloric acid, these materials topotactically exchange Na + for H + , proceeding in a stepwise protonation pathway for Na 5.33 Sn 2.67 S 8 . Na-NMS is stable in 2 M HNO 3 and Mg-NMS is stable in 4 M HNO 3 for up to 4 h, while both NMS materials are stable in 6 M HCl for up to 4 days. However, the treatment of Mg-NMS and Na-NMS with 2–6 M H 2 SO 4 reveals a much slower protonation process since after 4 h of contact both NMS and HMS are present in the solution. The resultant protonated materials, H 2x Mg 2y–x Sn 4–y S 8 and H 4x [(H y Na y–1 ) 1.33x Sn 4––1.33x ]S 8 , are themselves solid acids and readily react with and intercalate a variety of organic amines, where the band gap of the resultant adduct is influenced by amine choice and can be tuned within the range of 1.88(5)–2.27(5) eV. The work function energy values for all materials were extracted from photoemission yield spectroscopy in air (PYSA) measurements and range from 5.47 (2) to 5.76 (2) eV, and the relative band alignments of the materials are discussed. DFT calculations suggest that the electronic structure of Na 2 MgSn 3 S 8 and H 2 MgSn 3 S 8 makes them indirect gap semiconductors with multi-valley band edges, with carriers confined to the [MgSn 3 S 8 ] 2– layers. Light electron effective masses indicate high electron mobilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vibrational Properties of a Naturally Occurring Semiconducting van der Waals Heterostructure

We present vibrational properties of Franckeite, which is a naturally occurring van der Waals heterostructure consisting of two different semiconducting layers. Franckeite is a complex layered crystal composed of alternating SnS 2 -like pseudohexagonal and PbS-like pseudotetragonal layers stacked on top of each other, providing a unique platform to study vibrational properties and thermal transport across layers with mass density and phonon mismatches. Using micro-Raman spectroscopy and first-principles Raman simulations, we found that the PbS-like pseudotetragonal structure is mostly composed of Pb 3 SbS 4 . We also discovered several low-frequency Raman modes that originate from the intralayer vibrations of the pseudotetragonal layer. Using density functional theory, we determined all vibrational patterns of Franckeite, whose signatures are observed in the Raman spectrum. By studying temperature-dependent Raman spectroscopy (300–500 K), we have found different temperature coefficients for both pseudotetragonal and pseudohexagonal layers. Here, we believe that our study will help understand the vibration modes of its complex heterostructure and the thermal properties at the nanoscale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engineering Catalysts for Selective Ester Hydrogenation

The development of efficient catalysts and processes for synthesizing functionalized (olefinic and/or chiral) primary alcohols and fluoral hemiacetals is currently needed. These are valuable building blocks for pharmaceuticals, agrochemicals, perfumes, and so forth. From an economic standpoint, bench-stable Takasago Int. Corp.’s Ru-PNP, more commonly known as Ru-MACHO, and Gusev’s Ru-SNS complexes are arguably the most appealing molecular catalysts to access primary alcohols from esters and H 2 . This work introduces economically competitive Ru-SNP(O) z complexes ( z = 0, 1), which combine key structural elements of both of these catalysts. In particular, the incorporation of SNP heteroatoms into the ligand skeleton was found to be crucial for the design of a more product-selective catalyst in the synthesis of fluoral hemiacetals under kinetically controlled conditions. Based on experimental observations and computational analysis, this paper further extends the current state-of-the-art understanding of the accelerative role of KO- t -C 4 H 9 in ester hydrogenation. Finally, it attempts to explain why a maximum turnover is seen to occur starting at ~25 mol % base, in contrast to only ~10 mol % with ketones as substrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heteroepitaxial control of thickness, strain, and domain architecture in few-layer ferroelectric tin monochalcogenides

Thin-film epitaxy and epitaxial strain have been widely exploited to tune domain configurations, switching behavior, and ferroic properties in conventional three-dimensional ferroelectric thin films; however, its application to controlling the properties of two-dimensional (2D) ferroelectrics has remained largely unexplored. Here, using SnX (X = Se, S) as a model system, we demonstrate heteroepitaxial control of thickness, strain state, and domain architecture in few-layer ferroelectric SnX via growth on monolayer MoS2 van der Waals (vdW) templates. Compared with conventional growth, MoS2-templated heteroepitaxy promotes epitaxial alignment, yielding ultrathin SnSe films with improved crystalline quality, full areal coverage, and enlarged lateral dimensions. Strong interfacial epitaxial coupling induces pronounced in-plane strain and stabilizes a hierarchical ferroelastic domain architecture, in which long-range 90° stripe domains are further subdivided into nanoscale rotational variants, as revealed by scanning transmission electron microscopy and synchrotron X-ray microscopy. Piezoresponse force microscopy and second-harmonic polarimetry confirm robust in-plane polarization, while ferroelectricity in SnSe is established through polarization-electric field hysteresis and nonvolatile ferroelectric resistive switching with on/off ratios approaching 1000. A nonvolatile, switchable ferroelectric diode effect further evidences direct coupling between polarization and charge transport. Notably, ferroelectric switchability exhibits a strong thickness dependence and is preserved only below ∼10 layers. This vdW heteroepitaxial strategy is further extended to ferroelectric SnS. The seamless heteroepitaxial integration of 2D ferroelectrics with CMOS-compatible, wafer-scale MoS2 templates provides a general and scalable route for strain-enabled structural and ferroelectric engineering in emerging memory and low-power optoelectronic applications.

Wang, Yueyin↗

Mixed Cationic and Anionic Redox in Ni and Co Free Chalcogen-Based Cathode Chemistry for Li-Ion Batteries

Mixed cationic and anionic redox cathode chemistry is emerging as conventional cationic-redox of transition metal based layered oxides are reaching their theoretical capacity limit. However, these anionic redox in transition metal oxide-based cathodes attained by taking excess lithium has resulted in stability issues due to weak metal - oxygen ligand covalency. Here, we present an alternative approach of improving metal - ligand covalency by introducing less electronegative chalcogen ligand (sulfur) in the cathode structural framework where the metal dband penetration into ligand p-band thereby utilizing reversible mixed anionic and cationic redox chemistry. Through this design strategy, we report possibility of developing a new family of layered cathode materials when partially filled d orbital redox couples like Fe 2+/3+ are introduced in the Li-ion conducting phase (Li 2 SnS 3 ). Further, the electron energy loss spectroscopy (EELS) and X-ray absorption near-edge structure (XANES) analysis are used to qualitatively identify the charge contributors at the metal and ligand sites during Li + extraction. The detailed high-resolution transmission electron microscopy (HR-TEM) and high annular dark field-scanning transmission electron microscopy (HAADF-STEM) investigation reveal the multi redox induced structural modifications and its surface amorphization with nanopore formation during cycling. Findings from this study will shed light on designing Ni and Co free chalcogen cathodes and various functional materials in the chalcogen based dual anionic and cationic redox cathode avenue.

25 ENERGY STORAGE↗

Macroscopic Monochalcogenide van der Waals Ferroics: Growth, Domain Structures, and Curie Temperature

Two-dimensional and layered van der Waals materials promise to overcome the limitations of conventional ferroelectrics in terms of miniaturization and material integration, but synthesis has produced only small (up to few micrometer-sized) ferroic crystals. Here, we report the realization of in-plane ferroelectric few-layer crystals of the monochalcogenides tin(II) sulfide and selenide (SnS, SnSe) whose linear dimensions exceed the current state of the art by up to 1 order of magnitude. Such large crystals allow the investigation of ferroic domain patterns that are unaffected by edges and finite-size effects. Analysis of the abundant stripe domains by electron microscopy and nanobeam electron diffraction shows two distinct domain types: twin domains separated by positively charged walls with alternating head-to-head and tail-to-tail polarization as well as not previously observed purely rotational domains connected by neutral domain walls with head-to-tail dipoles. Access to large crystals allowed the determination of the Curie temperature of few-layer SnSe van der Waals ferroelectrics, and it enables the investigation of this class of ferroelectrics by widely available methods such as polarized optical microscopy. Furthermore, the combination with layer transfer protocols promises uniform materials for exploring fundamentals and for implementing devices for information processing and energy conversion.

36 MATERIALS SCIENCE↗

Realization of a two-dimensional Weyl semimetal and topological Fermi strings

A two-dimensional (2D) Weyl semimetal, akin to a spinful variant of graphene, represents a topological matter characterized by Weyl fermion-like quasiparticles in low dimensions. The spinful linear band structure in two dimensions gives rise to distinctive topological properties, accompanied by the emergence of Fermi string edge states. We report the experimental realization of a 2D Weyl semimetal, bismuthene monolayer grown on SnS(Se) substrates. Using spin and angle-resolved photoemission and scanning tunneling spectroscopies, we directly observe spin-polarized Weyl cones, Weyl nodes, and Fermi strings, providing consistent evidence of their inherent topological characteristics. Our work opens the door for the experimental study of Weyl fermions in low-dimensional materials.

36 MATERIALS SCIENCE↗

Pressurized formic acid dehydrogenation: an entropic spring replaces hydrogen compression cost

Formic acid is unique among liquid organic hydrogen carriers (LOHCs), because its dehydrogenation is highly entropically driven. This enables the evolution of high-pressure hydrogen at mild temperatures that is difficult to achieve with other LOHCs, conceptually by releasing the “spring” of energy stored entropically in the liquid carrier. Applications calling for hydrogen-on-demand, such as vehicle filling, require pressurized H 2 . Hydrogen compression dominates the cost for such applications, yet there are very few reports of selective, catalytic dehydrogenation of formic acid at elevated pressure. Herein, we show that homogenous catalysts with various ligand frameworks, including Noyori-type tridentate (PNP, SNS, SNP, SNPO), bidentate chelates (pyridyl)NHC, (pyridyl)phosphine, (pyridyl)sulfonamide, and their metallic precursors, are suitable catalysts for the dehydrogenation of neat formic acid under self-pressurizing conditions. Quite surprisingly, we discovered that their structural differences can be related to performance differences in their respective structural families, with some tolerant or intolerant of pressure and others that are significantly advantaged by pressurized conditions. Here, we further find important roles for H 2 and CO in catalyst activation and speciation. In fact, for certain systems, CO behaves as a healing reagent when trapped in a pressurizing reactor system, enabling extended life from systems that would be otherwise deactivated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stability and synthesis across barium tin sulfide material space

The underexplored Ba–Sn–S phase space is explored at various temperatures and cation ratios with combinatorial sputtering, crystallizing rocksalt-derived phases, Ba 2 SnS 4 , and Ba 7 Sn 5 S 15 . These findings are supported by DFT computed phase diagrams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗