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At least 253 records · Page 14

Synthesis of nanodiamonds encapsulated by zeolitic imidazole framework-8 for quantum sensing applications

Nitrogen vacancy (NV)-containing nanodiamonds are widely used in quantum sensing applications due to their high sensitivity to magnetic fields, relatively low cost, and ability to be initialized, manipulated, and read out at room temperature. Quantum sensing techniques such as optically detected magnetic resonance (ODMR) and spin relaxometry have exploited the sensitivity of the NV nanodiamonds to magnetic fields to detect a range of analytes, such as pH, metal ions, and biomolecules. However, diversifying the sensing targets accessible by NV diamond quantum sensors typically requires careful engineering of the diamond surface chemistry with stimuli-responsive functional groups. Here, a simple protocol for coating NV nanodiamonds with the zeolitic imidazole framework 8 (ZIF-8), a widely used metal-organic framework, is presented. ZIF-8 is a highly porous material that has been used as a selective sensor for gasses, metal ions, and other analytes. The material is well-characterized by x-ray diffraction, transmission electron microscopy, scanning electron microscopy, x-ray photoelectron spectroscopy, and luminescence spectroscopy. Encapsulation of NV nanodiamonds with a porous scaffold such as ZIF-8 provides a promising method for improving the selectivity for the quantum sensing of various analytes. Importantly, the ZIF-8 coating does not impact the luminescence properties of the NV diamond, which is a key readout in ODMR and spin relaxometry sensing approaches. Indeed, the ODMR spectra with and without the ZIF-8 shell is nearly identical. Moreover, the ZIF-8 coating increases the longitudinal spin relaxation time of the NV nanodiamond by a factor of 4 relative to aggregated diamond, a desirable outcome for spin relaxation-based quantum sensing. Metal-organic framework composites with nanodiamonds thus are an exciting strategy for enhancing NV nanodiamond performance in applications such as quantum sensing and quantum-enhanced nuclear magnetic resonance spectroscopy.

nitrogen vacancy nanodiamond↗

Advancing Multi-Hazard Risk and Safety Considerations for Aging Nuclear Facilities (Revision 1)

This project will demonstrate a multi-hazard time-dependent probabilistic risk assessment (PRA) approach for nuclear facilities considering aging-related deterioration of structures. A generic pressurized water reactor (PWR) reactor subjected to seismic mainshock-aftershock sequences considering the aging of the containment structure will be used as a case study to demonstrate the multi-hazard PRA approach. Using advanced modeling and simulation, seismic mainshock-aftershock fragility functions will be simulated for the containment structure considering aging effects. A multi-hazard PRA model for a generic PWR reactor will be built to quantify the multi-hazard core damage frequency (CDF) and large early release frequency (LERF) with explicit time-dependent modeling of event sequences. To date, the cascading impacts of multi-hazards are not adequately accounted for in the PRA models for nuclear facilities. In addition, for both initial and periodic evaluation of facilities to withstand natural phenomena hazards (NPH), deterioration of the SSCs due to aging and other effects is not adequately considered. By advancing multi-hazard considerations accounting for aging effects, this project will contribute to improved understanding of the safety of aging nuclear facilities. Project outcomes such as the multi-hazard CDF and LERF will also allow facility owners to optimize upgrade and retrofit protocols. This project is divided into two components: (1) advanced modeling and simulations; and (2) multi-hazard PRA. For the first component, Idaho National Laboratory’s (INL) Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) and BlackBear codes will be used to simulate the seismic response and damage of a containment structure under cascading mainshock-aftershock sequences with aging effects. Uncertainties related to the seismic inputs, material parameters, and environmental factors such as temperature and humidity will be identified and propagated to the fragility functions. These fragility functions, which consider aging effects, will be time dependent. The second component will take the fragility information from the first component to build a multi-hazard time-dependent PRA model starting from a generic PWR model to evaluate the multi-hazard CDF and LERF and characterize the associated consequences. For this component, OpenPRA Web Application and SAPHIRE code will be used. Events such as the Fukushima Daiichi accident have highlighted the importance of considering the cascading impacts of multi-hazards for PRA. Moreover, many of the reactors in the current nuclear fleet in the United States (US) are already operating well beyond their initially planned design life, and applications for further extensions to operating licenses are being considered. Therefore, considering multi-hazard effects and aging deterioration in the NPH risk assessment process will contribute to the safety of both existing and future nuclear facilities. Outcomes of this project will thus directly benefit the standards DOE-STD-1020-16 and DOE-HDBK-1224-18.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Synthesis, crystal and electronic structures, linear and nonlinear optical properties, and photocurrent response of oxyhalides CeHaVIO 4 (Ha = Cl, Br; VI = Mo, W)

Four heteroanionic oxyhalides, CeClMoO 4 , CeBrMoO 4 , CeClWO 4 , and CeBrWO 4 , have been studied as multifunctional materials, which show a combination of good second harmonic generation (SHG) response and photocurrent signals. Millimeter-sized CeHaVIO 4 (Ha = Cl, Br; VI = Mo, W) crystals were grown by halide salt flux. The crystal structure of CeHaVIO 4 crystals was accurately determined by single-crystal X-ray diffraction. CeClMoO 4 , CeBrMoO 4 , and CeBrWO 4 are isostructural to each other, and crystallize in the acentric LaBrMoO 4 structure type. CeClWO 4 crystallizes in a new structure type with unit cell parameters of a = 19.6059(2) Å, b = 5.89450(10) Å, c = 7.80090(10) Å, and β = 101.4746(8)°. The bandgaps of CeHaVIO 4 fall into the range of 2.8(1)–3.1(1) eV, which are much smaller than those of isotypic LaHaVIO 4 (Ha = Cl, Br; VI = Mo, W) in the range of 3.9(1)–4.3(1) eV. The narrowing of bandgaps in CeHaVIO 4 originates from the presence of partially filled 4f orbitals of cerium atoms, which was confirmed by density functional theory (DFT) calculations. The moderate bandgaps make CeHaVIO 4 suitable for infrared nonlinear optical (IR NLO) applications. CeBrMoO 4 and CeBrWO 4 exhibit moderate SHG responses of 0.58× AGS and 0.46× AGS, respectively, and are both type-I phase-matching materials. Moderate SHG response, easy growth of crystals, high ambient stability, and type-I phase-matching behavior make CeBrMoO 4 and CeBrWO 4 great materials for IR NLO applications. CeHaVIO 4 films also exhibited good photocurrent response upon light radiation. Furthermore, this work demonstrates the rich structural chemistry of the REHaVIO 4 (RE = Y, La–Lu; Ha = Cl, Br; VI = Mo, W) family and the potential presence of more multifunctional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

$\mathrm{REX}$: An analytical tool for reactor operating envelope expansion through fuel-clad thermo-mechanics

Here REX, an analytical reactor design tool for the identification and expansion of reactor operating envelopes, is introduced and detailed. Written in MATLAB, REX takes core geometries and axially discretized detector and depletion output from the Serpent neutron transport code and performs full-core, pin-specific thermal-hydraulic and thermo-mechanical calculations. REX identifies the operating envelopes of advanced, solid-fuel nuclear reactors on the basis of their fuel-cladding, fuel-gas, and coolant-cladding interfacial thermo-mechanics. It iteratively pushes coolant inlet temperatures and modifies fuel pin geometries to induce mechanical failure in their original cladding materials at the fullest extent of their fuel cycle lengths and permissible coolant inlet temperatures. It then attempts to expand their operating envelopes by determining the mechanical responses of alternative cladding materials under the same geometric conditions. The result of the REX calculation sequence is a set of 5-D variables describing the temperatures, pressures, geometries, and mechanics of the core as functions of assembly, fuel pin, axial zone, depletion step, and coolant inlet temperature for each candidate cladding material with the limiting fuel pin geometry for the original material.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

New self-consistent homogenization for thermo-elastic polycrystals with imperfect interfaces

Here we present a new thermo-elastic self-consistent formulation to calculate the thermo-mechanical response of polycrystalline aggregates with imperfect interfaces. The new model is based on an improved treatment of the effect of imperfect interfaces on the micromechanical response of the grains compared to pre-existing models. New expressions/algorithms are derived for the effective elastic and thermal properties, localization relations, and calculation of intragranular field fluctuations. In addition, derivation of a novel integral equation for the strain field in a heterogeneous elastic medium subjected to arbitrary thermal strain field and displacement jumps is presented. The new model is applied to study the effective thermo-elastic properties and average field fluctuations as a function of the interface properties for imperfectly-bonded triaminotrinitrobenzene (TATB) polycrystalline granular aggregates. The proposed formulation is general in the sense that it can be extended to other material systems and deformation regimes that require a proper consideration of the effect of imperfect interface properties on the material's thermo-mechanical response.

36 MATERIALS SCIENCE↗

Colloidal structure and proton conductivity of the gel within the electrosensory organs of cartilaginous fishes

Cartilaginous fishes possess gel-filled tubular sensory organs called Ampullae of Lorenzini (AoL) that are used to detect electric fields. Although recent studies have identified various components of AoL gel, it has remained unclear how the molecules are structurally arranged and how their structure influences the function of the organs. Here we describe the structure of AoL gel by microscopy and small-angle X-ray scattering and infer that the material is colloidal in nature. To assess the relative function of the gel’s protein constituents, we compared the microscopic structure, X-ray scattering, and proton conductivity properties of the gel before and after enzymatic digestion with a protease. We discovered that while proteins were largely responsible for conferring the viscous nature of the gel, their removal did not diminish proton conductivity. The findings lay the groundwork for more detailed studies into the specific interactions of molecules inside AoL gel at the nanoscale.

59 BASIC BIOLOGICAL SCIENCES↗

Complex pH-Dependent Interactions between Weak Polyelectrolyte Block Copolymer Micelles and Molecular Fluorophores

Amphiphilic block copolymers with weak polyelectrolyte blocks can assemble stimulus-responsive nanostructures and interfaces. Applications of these materials in drug delivery, biomimetics, and sensing largely rely on the well-understood swelling of polyelectrolyte chains upon deprotonation, often induced by changes in pH or ionic strength. This deprotonation can also tune interfacial interactions between the polyelectrolyte blocks and surrounding solution, an effect which is less studied than morphological swelling of polyelectrolytes but can be just as critical for intended function. Here, we investigate whether the pH-driven morphological response of polyelectrolyte-bearing nanostructures also affects the interactions of these nanostructures with molecules in solution, using micelles of a short-chain polybutadiene-block-poly(acrylic acid) (pBd–pAA) as a model system. Here we introduce a Förster resonance energy transfer (FRET) approach to probe interactions between micelles and fluorescent molecular solutes as a function of solution pH. As expected, the pAA corona of these pBd–pAA micelles increases in thickness monotonically as a function of pH. However, FRET efficiency, which provides a metric of the spatial proximity of fluorescently labeled micelles and freely diffusing fluorophores, exhibits complex nonmonotonic behavior as a function of pH, indicating that the average separation of micelles and acceptor fluorophores is not strictly correlated with micelle swelling. Dialysis experiments quantify the affinity of fluorophores for micelles as a function of pH, confirming that changes in FRET are driven almost entirely by the pH-dependent affinity of the pAA block for the investigated molecular fluorophores, not simply by a shape change of the pAA corona. This study provides key insights into the interfacial interactions between weak-polyelectrolyte-bearing nanostructures and molecular solutes, of importance for the development of their stimulus-responsive applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗

A machining digital twin for hybrid manufacturing

Hybrid manufacturing consisting of metal additively manufactured preforms and computer numerical control (CNC) machining has been established to be an effective method for high material use rates. However, hybrid manufacturing introduces unique challenges. Near-net shape designs are typically selected, which result in a smaller margin for part placement within the stock and stringent requirements for work coordinate system identification. Additionally, less stock material reduces the preform stiffness, which limits the material removal rates during machining. This paper demonstrates a digital twin for CNC machining of a wire arc additively manufactured preform that implements: 1) structured light scanning for stock model identification and tool path generation; 2) a fused filament fabrication apparatus to attach temporary fiducials and scan targets to the preform that enable coordinate system definition for both the CAM and CNC machine; 3) preform and tool tip frequency response function measurements to enable stable milling parameter selection; and 4) post-manufacturing measurements of geometry, surface finish, and structural dynamics to confirm designer intent. These efforts define key components of the machining digital twin for hybrid manufacturing.

36 MATERIALS SCIENCE↗

Physics augmented machine learning discovery of composition-dependent constitutive laws for 3D printed digital materials

Multi-material 3D printing, particularly through polymer jetting, enables the fabrication of digital materials by mixing distinct photopolymers at the micron scale within a single build to create a composite with tunable mechanical properties. Here, this work presents an integrated experimental and computational investigation into the composition-dependent mechanical behavior of 3D printed digital materials. We experimentally characterize five formulations, combining soft and rigid UV-cured polymers under uniaxial tension and torsion across three strain and twist rates. The results reveal nonlinear and rate-dependent responses that strongly depend on composition. To model this behavior, we develop a physics-augmented neural network (PANN) that combines a partially input convex neural network (pICNN) for learning the composition-dependent hyperelastic strain energy function with a quasi-linear viscoelastic (QLV) formulation for time-dependent response. The pICNN ensures convexity with respect to strain invariants while allowing non-convex dependence on composition. To enhance interpretability, we apply $L_0$ sparsification. For the time-dependent response, we introduce a multilayer perceptron (MLP) to predict viscoelastic relaxation parameters from composition. The proposed model accurately captures the nonlinear, rate-dependent behavior of 3D printed digital materials in both uniaxial tension and torsion, achieving high predictive accuracy for interpolated material compositions. This approach provides a scalable framework for automated, composition-aware constitutive model discovery for multi-material 3D printing.

Constitutive modeling↗

Imaging Nanoscale Energy Transport and Conversion with Ultrafast Electron Microscopy (Final Technical Report)

Light-matter interactions are ubiquitous in nature and reside at the heart of innumerable technologies. The cascade of processes that occur when a material absorbs a photon of light are exceedingly complex and are interwoven in both space and time, rendering precise determination of the atomic-scale and ultrafast mechanisms immensely challenging. The advent of methods for generating short pulses of light several decades ago led to major advances in understanding the initial moments of light absorption and the resultant effects, though directly interrogating the response of the atoms within the material continued to prove challenging. More recently, methods for generating ultrashort pulses of X-rays and fast electrons have opened the way to probing photoinduced structural dynamics of a wide range of matter in multiple phases. An especially promising laboratory-scale method is ultrafast electron microscopy (UEM), wherein the modalities of conventional transmission electron microscopes (imaging, diffraction, spectroscopy) are extended into the femtosecond temporal regime. Here, the ultrafast imaging and diffraction modalities of UEM were used to study the transient structural aspects of photoexcitation of semiconducting materials (e.g., spatially-resolved electron-phonon coupling, excitation and emission of acoustic phonons, and discrete nanoscale scattering processes). The project had three main objectives: (1) determination of the excitation mechanisms of dense, hypersonic charge-carrier waves and the spatially mediated means by which they couple to the lattice via coherent phonon emission, especially with UEM imaging, wherein effects of nanoscale structural and morphological features on the coupling and relaxation dynamics are expected to dictate nucleation sites and preferred wave vectors, (2) elucidation of photoinduced acoustic-phonon seeding, emergence, propagation, and decay over nanoscale crystal regions and especially with respect to local strain fields and atomic-scale disruptions in lattice order, and (3) interwoven with the first two were efforts aimed at realizing combined angstrom-femtosecond spatiotemporal imaging with UEM. The outcomes and impacts of this project were the generation of new knowledge with respect to fundamental light-matter interactions and, especially, the spatially-mediated excitation and evolution of the structural response of materials following coherent photoexcitation. Importantly, the spatial and temporal resolutions of the UEM imaging modalities used are well-suited for such studies and enable spatially-resolved mechanisms to be determined as a function of atomic order, structural features, and morphology. In addition, ultrafast crystallographic measurements were used to correlate real- and reciprocal-space dynamics in order to determine atomic-scale preferential wave vectors and ultrafast scattering mechanisms, especially as dictated by specimen boundary conditions. The obtained results, as detailed in peer-reviewed publications and presentations, illustrate the importance of ultrafast, angstrom-scale real-space imaging for developing a comprehensive understanding of energy transport and conversion in materials.

47 OTHER INSTRUMENTATION↗

Revealing the synergistic effects of sequential and simultaneous dual beam irradiations in tungsten via in-situ TEM

Elucidating the synergistic effects of different energetic beams on the radiation response of nuclear materials is critical for developing an improved methodology for their evaluation when exposed to extreme environments. This article describes in-situ sequential (He implantation followed by Kr irradiation and vice-versa) and simultaneous (heavy ion Kr irradiation and He implantation) dual beam irradiations performed on tungsten at 1223 K. Dislocation loop density, average area, and total loop damage as a function of irradiation history and dose/fluence are quantified. The loop Burgers vectors and cavity damage (cavity density, size and total change in volume) are also determined at the final maximum dose for each condition. The loop damage evolution was different in all cases, with the smallest loop damage observed in the simultaneous experiment. Annihilation of Kr generated dislocation loops during He implantation in the Kr + He experiment was an unanticipated observation that may be explained by the dynamic evolution of dislocation loop sink strengths and time-dependent defect fluxes. Dislocation loop raft formation, denuded zones near extended defects, and cavity damage are compared across the different conditions. The phenomena observed and discussed in this work will stimulate further experimental and computational modeling activities leading to improved fundamental understanding of the irradiation response of nuclear materials under reactor-similar environments.

36 MATERIALS SCIENCE↗

A composite electrodynamic mechanism to reconcile spatiotemporally resolved exciton transport in quantum dot superlattices

Quantum dot (QD) solids are promising optoelectronic materials; further advancing their device functionality requires understanding their energy transport mechanisms. The commonly invoked near-field Förster resonance energy transfer (FRET) theory often underestimates the exciton hopping rate in QD solids, yet no consensus exists on the underlying cause. In response, we use time-resolved ultrafast stimulated emission depletion (STED) microscopy, an ultrafast transformation of STED to spatiotemporally resolve exciton diffusion in tellurium-doped cadmium selenide–core/cadmium sulfide–shell QD superlattices. We measure the concomitant time-resolved exciton energy decay due to excitons sampling a heterogeneous energetic landscape within the superlattice. The heterogeneity is quantified by single-particle emission spectroscopy. This powerful multimodal set of observables provides sufficient constraints on a kinetic Monte Carlo simulation of exciton transport to elucidate a composite transport mechanism that includes both near-field FRET and previously neglected far-field emission/reabsorption contributions. Uncovering this mechanism offers a much-needed unified framework in which to characterize transport in QD solids and additional principles for device design.

36 MATERIALS SCIENCE↗

Interfacial-Strain-Controlled Ferroelectricity in Self-Assembled BiFeO 3 Nanostructures

Self-assembled BiFeO 3 -CoFe 2 O 4 (BFO-CFO) vertically aligned nanocomposites are promising for logic, memory, and multiferroic applications, primarily due to the tunability enabled by strain engineering at the prodigious epitaxial vertical interfaces. However, local investigations directly revealing functional properties in the vicinity of such critical interfaces are often hampered by the size, geometry, microstructure, and concomitant experimental artifacts. Ferroelectric switching in the presence of lateral distributions of vertical strain thus remains relatively unexplored, with broader implications for all strain-engineered functional devices. Additionally, by implementing tomographic atomic force microscopy, 3D domain orientation mapping, and spatially-resolved ferroelectric switching movies, local tensile strain significantly impacts the ferroelectric switching, principally by retarding domain nucleation in the BFO nearest to the vertically epitaxial tensile-strained interfaces. The relaxed centers of the BFO pillars become preferred domain nucleation and growth sites for low biases, with up to an order of magnitude change in the edge:center switching ratio for high biases. The new, multi-dimensional imaging approach—and its corresponding insights especially for directly strained interface effects on local properties—thereby advances the fundamental understanding of polarization switching and provides design principles for optimizing functional response in confined nanoferroic systems.

36 MATERIALS SCIENCE↗

Combining Experimental and Theoretical Techniques to Gain an Atomic Level Understanding of the Defect Binding Mechanism in Hard Carbon Anodes for Sodium Ion Batteries

Sodium ion batteries (NIBs) are an attractive alternative to lithium–ion batteries in applications that require large–scale energy storage due to sodium's high natural abundance and low cost. Hard carbon (HC) is the most promising anode material for NIBs; however, there is a knowledge gap in the understanding of the sodium binding mechanism that prevents a rational design of HC. This study tunes sucrose–derived HC via synthesis temperature then evaluates the structural, physical, and electrochemical properties. Neutron total scattering is used to generate structural models by fitting pair distribution functions (PDF) with a combination of molecular dynamics and reverse Monte Carlo methods. From this model, the number and type of structural features are identified, quantified, and correlated to the galvanostatic charge/discharge. A method of PDF “fingerprinting” binding sites using Na probe atoms is developed and analyzing these PDFs reveals an atomistic view of ion binding sites responsible for “defect” storage mechanisms. Combining these techniques results in an atomic–level study that provides a big picture of the Na–binding mechanism in NIBs, which allows for more precise tuning of the structure–property relationships in the future. Finally, the methodologies developed will also enable new strategies for the analysis of amorphous functional materials.

25 ENERGY STORAGE↗

Structural and mechanical properties of monolayer amorphous carbon and boron nitride

Amorphous materials exhibit various characteristics that are not featured by crystals and can sometimes be tuned by their degree of disorder (DOD). Here, we report results on the mechanical properties of monolayer amorphous carbon (MAC) and monolayer amorphous boron nitride (maBN) with different DOD. The pertinent structures are obtained by kinetic-Monte-Carlo (kMC) simulations using machine-learning potentials (MLP) with density-functional-theory (DFT)-level accuracy. An intuitive order parameter, namely the areal fraction F x occupied by crystallites within the continuous random network, is proposed to describe the DOD. We find that F x captures the essence of the DOD: Samples with the same F x but different sizes and arrangements of crystallites, obtained using two distinct kMC procedures, have virtually identical radial distributions functions as well as bond-length and bond-angle distributions. Furthermore, by simulating the fracture process with molecular dynamics, we found that the mechanical responses of MAC and maBN before fracture are mainly determined by F x and are insensitive to the sizes and specific arrangements and to some extent the numbers and area distributions of the crystallites. The behavior of cracks in the two materials is analyzed and found to mainly propagate in meandering paths in the CRN region and to be influenced by crystallites in distinct ways that toughen the material. Furthermore, the present results reveal the relation between structure and mechanical properties in amorphous monolayers and may provide a universal toughening strategy for 2D materials.

2-dimensional systems↗

Rheology guiding the design and printability of aqueous colloidal composites for additive manufacturing

Vat photopolymerization (VP) and direct ink write (DIW) additive manufacturing (AM) provide complex geometries with precise spatial control employing a vast array of photo-reactive polymeric systems. Although VP is recognized for superior resolution and surface finish, DIW provides versatility for higher viscosity systems. However, each AM platform presents specific rheological requirements that are essential for successful 3D printing. First, viscosity requirements constrain VP polymeric materials to viscosities below 10 Pa s. Thus, this requirement presents a challenging paradox that must be overcome to attain the physical performance of high molecular weight polymers while maintaining suitable viscosities for VP polymeric materials. Second, the necessary rheological complexity that is required for DIW pastes requires additional rheological measurements to ensure desirable thixotropic behavior. Further, this manuscript describes the importance of rheological measurements when designing polymeric latexes for AM. Latexes effectively decouple the dependency of viscosity on molecular weight, thus enabling high molecular weight polymers with low viscosities. Photo-crosslinking of water-soluble monomers and telechelic oligomeric diacrylates in the presence of the latex enables the fabrication of a scaffold, which is restricted to the continuous aqueous phase and effectively surrounds the latex nanoparticles enabling the printing of otherwise inaccessible high molecular weight polymers. Rheological testing, including both steady and oscillatory shear experiments, provides insights into system properties and provides predictability for successful printing. This perspective article aims to provide an understanding of both chemical functionality (photo- and thermal-reactivity) and rheological response and their importance for the successful design and evaluation of VP and DIW processable latex formulations.

36 MATERIALS SCIENCE↗