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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Linking structural and rheological memory in disordered soft materials

Linking the macroscopic flow properties and nanoscopic structure is a fundamental challenge to understanding, predicting, and designing disordered soft materials. Under small stresses, these materials are soft solids, while larger loads can lead to yielding and the acquisition of plastic strain, which adds complexity to the task. In this work, we connect the transient structure and rheological memory of a colloidal gel under cyclic shearing across a range of amplitudes via a generalized memory function using rheo-X-ray photon correlation spectroscopy (rheo-XPCS). Our rheo-XPCS data show that the nanometer scale aggregate-level structure recorrelates whenever the change in recoverable strain over some interval is zero. The macroscopic recoverable strain is therefore a measure of the nano-scale structural memory. We further show that yielding in disordered colloidal materials is strongly heterogeneous and that memories of prior deformation can exist even after the material has been subjected to flow.

Kamani, Krutarth M. [Univ. of Illinois at Urbana-C↗

Scattering-based structural inversion of soft materials via Kolmogorov–Arnold networks

Small-angle scattering techniques are indispensable tools for probing the structure of soft materials. However, traditional analytical models often face limitations in structural inversion for complex systems, primarily due to the absence of closed-form expressions of scattering functions. To address these challenges, we present a machine learning framework based on the Kolmogorov–Arnold Network (KAN) for directly extracting real-space structural information from scattering spectra in reciprocal space. This model-independent, data-driven approach provides a versatile solution for analyzing intricate configurations in soft matter. By applying the KAN to lyotropic lamellar phases and colloidal suspensions—two representative soft matter systems—we demonstrate its ability to accurately and efficiently resolve structural collectivity and complexity. Here, our findings highlight the transformative potential of machine learning in enhancing the quantitative analysis of soft materials, paving the way for robust structural inversion across diverse systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mill profiler machines soft materials accurately

Mill profiler machines bevels, slots, and grooves in soft materials, such as styrofoam phenolic-filled cores, to any desired thickness. A single operator can accurately control cutting depths in contour or straight line work.

Rauschl, J. A.↗

Quantum effects on the dynamics and properties of soft materials

The quantum effects of nuclear and electronic motion play an important role in the structure, dynamics, and function of soft materials, yet they are difficult to capture with conventional classical simulations or static electronic–structure methods. In this work several complementary approaches for treating quantum effects in polymeric and soft–matter systems are demonstrated, with a focus being on the hydrogen-bonded networks, ion and charge transport, and photoactive chromophores. The proton transfer, tunneling, and isotope effects are captured within the reduced-dimensionality models by implementing grid-based nuclear quantum dynamics in terms of the discrete variable and Fourier bases. The nuclear quantum dynamics is extended to larger systems by employing the quantum trajectories and quantum–thermal bath schemes combined with on-the-fly electronic structure, enabling the description of high-dimensional polymeric environments at feasible cost. The dynamics in the electronic degrees of freedom, simulating the optical response in large chromophores such as chlorophylls, is performed using the real-time time-dependent density functional theory implemented in the real-space multigrid (RMG) code. These approaches are demonstrated on case studies of the proton and hydroxide transport in hydrated polymer membranes, charge transfer in conjugated polymers, and the optical spectra of chlorophyll chromophores relevant to polymerized chlorophyll materials and chlorophyll–polymer hybrids. The reviewed methods and applications highlight practical routes of including quantum effects in simulations of soft functional materials.

Garashchuk, Sophya [Univ. of South Carolina, Colum↗

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a “user guide” for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure–property relationships in soft materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tutorial: Machine-Learning-Based CREASE-2D Analysis of 2D SAXS Profiles to Characterize Anisotropic Nanostructures in Soft Materials

We present a tutorial to guide users on how to extend the Computational Reverse Engineering Analysis of Scattering Experiments-2D (CREASE-2D) framework to interpret their experimental two-dimensional small-angle scattering (SAS) data from soft materials (e.g., polymers, peptide amphiphiles, biomolecular fibrils). Unlike most traditional SAS analysis approaches, which typically rely on azimuthally averaged onedimensional (1D) profiles, CREASE-2D utilizes the complete 2D scattering profile to reveal information about anisotropy in the structure. In past applications, CREASE has provided insights into complex structural features, including the cross-sectional shapes of assembled nanostructures and dispersity in these features, which are difficult to discern with existing analytical models. While (1D- ) CREASE has been applied to SANS and SAXS data, this tutorial shares the steps for implementing CREASE-2D using an example of a dipeptide solution system, for which we have SAXS data. We present details for these steps involved in using CREASE-2D to interpret SAXS profiles: how to preprocess SAXS data, define relevant structural features, generate three-dimensional real-space structures for specific values of these features, train a machine learning (ML) surrogate model to predict scattering profiles for given structural features, and optimize these features using genetic algorithms (GA). Then, we use these steps to interpret complex 2DSAXS data collected from dipeptide solutions that, in microscopy images, exhibit nanoscale structures that could be elliptical tubes/ flat tapes/cylinders or a combination of these cross sections. Open-source codes, computational hardware, and software requirements, as well as the strengths and limitations of this protocol, are also presented. We expect researchers working with (soft) biomaterials, peptide amphiphiles, amphiphilic polymer solutions, polymer nanocomposites, and blends of particles/polymers will find this CREASE-2D method and this tutorial of use.

CREASE↗

On the Prospect of Chemically Transferable Coarse-Grained Electronic Models for Soft Materials

Electronic coarse-graining (ECG) methods predict quantum-mechanical electronic properties directly from coarse-grained (CG) molecular configurations, enabling electronic predictions at mesoscale length scales. Here, we present a diagnostic assessment of the feasibility of chemically transferable ECG models across a broad polymer-relevant chemical space using all-atom, united-atom, and Martini-scale representations. While high-resolution ECG models achieve near-quantitative accuracy, we show that chemically transferable ECG at the Martini resolution fails because the CG force field does not sample the same configurational distribution of local molecular structure as that underlying the DFT-parameterized ECG model. We demonstrate that our proposed Element-Count-Label (ECL) representation, which augments Martini beads with explicit stoichiometric data, significantly improves chemical generalization across diverse polymer chemistries. However, we find that even with improved chemical resolution, the model cannot recover electronic property distributions that are absent from the configurational space sampled by the CG force field. These results demonstrate that chemically transferable ECG requires future Martini-like force fields to explicitly preserve quantum chemistry–compatible local molecular structure in addition to thermodynamic and structural fidelity.

Kidder, Katherine M [Department of Chemistry; Univ↗

Combining Hard with Soft Materials in Nanoscale Under High-Pressure High-Temperature Conditions

Nano-composites with a primary nanocrystalline ceramic matrix and a secondary nanocrystalline material (metal or semiconductor) were synthesized by infiltration of an appropriate liquid into ceramic compacts under pressures of up to 8 GPa and temperatures of up to 2000 K. The purpose of our work is to obtain nanocomposites which constitute homoger?ous mixtures of two phases, both forming nano- grains of about 10 nm in size. The high pressure is used to bring the porosity of the compacted powders down to the nano-scale and force a given liquid into the nano-sized pores. The advantage of the infiltration technique is that, in a single, continuous process, we start with a nanocrystalline powder, compress it to form the matrix of the composite, and crystallize and/or synthesize a second nanomaterial in the matrix pores. The key limitation of this technology is, that the pores in the matrix need to stay open during the entire process of infiltration. Thus the initial powder should form a rigid skeleton, otherwise the so-called self-stop process can limit cr block a further flow of the liquid phase and hinder the process of the composite formation. Therefore powders of only very hard ceramic materials like diamond, Sic, or Alz03, which can withstand a substantial external load without undesired deformation, can be used as the primary phase. With this technique, using diamond and S i c ceramic powders infiltrated by liquid metals (AI, Zn, Sn, Ag, Au) and semiconductors (Si, Ge, GaAs, CdTe), we obtained nano-composites with the grain size in the range of 10 - 30 nm. Our work addresses the key problem in manufacturing bulk nanocrystalline materials, i.e. preservation of nano-scale during the fabrication process. In this paper we discuss basic technical and methodological problems associated with nano-infiltration based on the results obtained for Zn-Sic composites.

Palosz, B.↗

Functional soft materials and methods of making and using thereof

Disclosed are functional materials for use in additive manufacturing (AM). The functional material can comprise an elastomeric composition (e.g., a silicone composite) for use in, for example, direct ink writing. The elastomeric composition can include an elastomeric resin, and a magnetic nanorod filler dispersed within the elastomeric resin. Nanorod characteristics (e.g., length, diameter, aspect ratio) can be selected to create 3D-printed constructs with desired mechanical properties along different axes. Furthermore, since nickel nanorods are ferromagnetic, the spatial distribution and orientation of nanorods within the continuous phase can be controlled with an external magnetic field. This level of control over the nanostructure of the material system offers another degree of freedom in the design of functional parts and components with anisotropic properties. Magnetic fields can be used to remotely sense compression of the constructs, or alternatively, control the stiffness of these materials.

Berkland, Cory↗

Tools made of ice facilitate forming of soft, sticky materials

Tools made of ice facilitate the forming or shaping of materials that are soft and sticky in the uncured state. The low-temperature of the ice slows the curing of the material, extending the working time available before setup. Handling problems are eliminated because the material does not adhere to the tool, and the melting ice serves as a lubricant.

Harris, J. E.↗

A large deformation multiphase continuum mechanics model for shock loading of soft porous materials

A large deformation, coupled finite-element (FE) model is developed to simulate the multiphase response of soft porous materials subjected to high strain-rate loading. The approach is based on the theory of porous media (TPM) at large deformations. Simplifications to the one-dimensional regime studied in the numerical simulations follow. An overview of several different time integration schemes is presented for the purpose of solving the nonlinear dynamic coupled balance of momenta (mixture and fluid) and balance of mass of the mixture equations. Numerical examples are presented for (i) verification against closed-form analytical solutions assuming small loads, (ii) demonstrating large deformation effects at high strain-rate, and (iii) showing differences in deformations between a single-phase elastodynamics model with occluded compressible pore fluid and a multiphase poroelastodynamics model at high strain-rate. The multiphase model shows that the relative motion of the pore fluid significantly dampens the deformation response of the solid skeleton as compared to the single-phase model, and makes it possible to extract quantitative values for the stresses of the different constituents, thereby allowing one to form preliminary conclusions about the onset of damage in the solid skeleton. The novelty of the current work is developing a multiphase, large deformation, mixture theory numerical model for high strain-rate loading of soft porous materials. It was discovered that explicit, adaptive time-stepping Runge–Kutta schemes offer high accuracy at relatively low cost when compared to traditional implicit or explicit central difference time-stepping schemes for shock-like loadings. Here, shock viscosity is added to the mixture momentum balance equation to regularize the shock front, and a stabilization term is added to the mixture mass balance equation to stabilize equal order interpolation finite elements for the coupled finite element solution of multiphase materials.

Engineering↗

Soft matter roadmap

Soft materials are usually defined as materials made of mesoscopic entities, often self-organised, sensitive to thermal fluctuations and to weak perturbations. Archetypal examples are colloids, polymers, amphiphiles, liquid crystals, foams. The importance of soft materials in everyday commodity products, as well as in technological applications, is enormous, and controlling or improving their properties is the focus of many efforts. From a fundamental perspective, the possibility of manipulating soft material properties, by tuning interactions between constituents and by applying external perturbations, gives rise to an almost unlimited variety in physical properties. Together with the relative ease to observe and characterise them, this renders soft matter systems powerful model systems to investigate statistical physics phenomena, many of them relevant as well to hard condensed matter systems. Understanding the emerging properties from mesoscale constituents still poses enormous challenges, which have stimulated a wealth of new experimental approaches, including the synthesis of new systems with, e.g. tailored self-assembling properties, or novel experimental techniques in imaging, scattering or rheology. Theoretical and numerical methods, and coarse-grained models, have become central to predict physical properties of soft materials, while computational approaches that also use machine learning tools are playing a progressively major role in many investigations. This Roadmap intends to give a broad overview of recent and possible future activities in the field of soft materials, with experts covering various developments and challenges in material synthesis and characterisation, instrumental, simulation and theoretical methods as well as general concepts.

36 MATERIALS SCIENCE↗

Hybrid epoxy–acrylate resins for wavelength-selective multimaterial 3D printing

Structures in nature have evolved to combine hard and soft materials in precise 3D arrangements, which imbues bulk properties and functionality that remain elusive to mimic synthetically. However, the potential for biomimetic analogs to seamlessly interface hard materials with soft surfaces for applications ranging from robotics and sealants to medical devices (e.g., prosthetics and wearable health monitors) has driven the demand for innovative chemistries and manufacturing approaches. Herein, we unveil a liquid resin for rapid, high resolution digital light processing (DLP) 3D printing of multimaterial objects with an unprecedented combination of strength, elasticity, and resistance to aging. Two enabling discoveries are the use of a covalently bound (hybrid) epoxy-acrylate monomer that precludes plasticization of soft domains and a wavelength-selective photosensitizer that accelerates cationic curing for hard domains. Using dual projection for multicolor DLP 3D printing (UV and violet light), several bioinspired metamaterial structures are fabricated, including one with hard springs embedded in a soft cylinder to adjust compressive behavior and a detailed knee joint featuring “bones” and “ligaments” for smooth motion. Lastly, the application of this system to facilitate selective stretching for electronic devices is demonstrated with a proof-of-concept device.

36 MATERIALS SCIENCE↗

Research Reactors Division Infrastructure Investment Plan for the High Flux Isotope Reactor

The High Flux Isotope Reactor (HFIR) is a unique national asset. Operational for nearly 60 years, continued investment into the aging infrastructure is necessary to ensure operation for another 6 decades. Additionally, growing missions require HFIR as well as important upgrades. Consequently, carefully integrated planning is required to ensure that infrastructure investments are timely executed to ensure long-term, reliable operation of HFIR. Concerns about challenges to the operational reliability of HFIR resulted in a recommendation from the 2023 Operations Review by the US Department of Energy (DOE) Office of Basic Energy Sciences that a HFIR management strategy be developed to address the infrastructure needs. This report defines the investment needs, which are evolving as new upgrade efforts are better defined. HFIR is part of the three-source strategy within the Neutron Sciences Directorate (NScD) and contributes to the five strategic science areas outlined in the NScD 10 Year Strategic Science Plan: quantum materials, soft matter, materials and engineering, chemistry, and biosciences. Fundamental to this strategy are three core values: operational excellence, responsible stewardship, and servant leadership. These values guide our mission of safe and reliable operation of the reactor and require a strong and just nuclear safety culture, a solemn respect for responsible care of the facility, good workforce development, robust procedures and processes, an effective communication strategy, world-class asset management, a determined customer focus, and a commitment to protecting the environment, the safety and health of the public and our people, and the quality of work performed within our facility. These principles are all essential to operate HFIR at a world-class level. The Research Reactors Division (RRD) will lead a new era of neutron science and isotope production at HFIR through responsible and purposeful leadership and unwavering support of the science community. The approach outlined in this plan highlights the direction leadership is taking to ensure that HFIR is ready to support the science challenges and national needs of the future and that the United States maintains world leadership in neutron sciences. The plan is in alignment with the DOE’s desire to continue operating HFIR and with the NScD strategic science goals for the future. HFIR is an aging facility with numerous infrastructure challenges and needs. It has an aging workforce in relation to the general population of Oak Ridge National Laboratory (ORNL), with many expected retirements over the next 5–10 years. With an increase in work scope caused by changing national priorities and science goals, several critical hires have been identified. To manage HFIR’s infrastructure needs, a prioritized list of equipment upgrades has been identified along with an analysis of future staffing requirements. A desire to operate HFIR at eight cycles per year will necessarily require some significant changes to procedures and processes currently in place as well as targeted staffing additions. Many of the equipment upgrades identified in this plan will significantly increase the reliability of the plant, thus contributing to the effort to reach the goal of safely operating eight cycles per year. A plan to attain eight-cycle operation is being prepared in parallel with the activities identified in this plan, although the actions identified to satisfy both plans will overlap. This plan identifies new infrastructure needs—for both plant equipment and staffing—thus necessitating formulation of future budget requests to fund the increased work scope and improvement activities. Some activities are currently being scheduled with the expectation that funding will be received. Any delays to funding or reductions of funding from the identified cost estimations will directly and negatively affect the plan’s implementation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Sectioning Coated Specimens Without Edge Rounding

New method devised for preparation of cross sections of coated specimens for scanning electron microscopy or energy-dispersive analysis without rounding edges of coatings. After cutting and polishing, specimen section remains smooth and flat so it can be examined under high magnification out to edge of coating. Sectioned blade first electroplated with hard nickel 0.003 in., then encapsulated in two layers of material: soft conductive material at bottom and 0.25 in. of hard diallyl phthalate at top. Nickel plate provides electrical path from surface of section to conductive material below.

Mckechnie, Timothy N.↗

ENVIRONMENTAL DEGRADATION OF HARD AND SOFT MAGNETIC MATERIALS IN GASEOUS AND SUPERCRITICAL CO2 ENVIRONMENTS

It may be beneficial to use hermetic designs for supercritical CO2 (sCO2) cycles machinery as they would eliminate CO2 leakage through shaft end seals. This would reduce CO2 emissions and operating costs for makeup of lost process fluid. Those designs may replace traditional oil-lubricated bearings with actively controlled magnetic bearings operating at high temperatures in the process fluid environment (to reduce the need for active cooling). This paper investigates the material degradation of various types of magnets in CO2. Included are several permanent and soft magnetic materials (Alnico 9C, Alnico 5-7C, and 18-T550 grade SmCo, and Hiperco 50) with or without coatings (nickel plating or C5 coating). The materials were exposed to: (1) flowing gaseous CO2 at 1,022 °F (550 °C) and atmospheric pressure in a furnace and (2) sCO2 at 842 °F (450 °C) and 1,500 psi (103 bar) in an autoclave. The preliminary mass change measured after total exposures of 1,000 hours and 2,000 hours are included.

supercritical CO2, magnetic material↗

Measuring surface-area-to-volume ratios in soft porous materials using laser-polarized xenon interphase exchange nuclear magnetic resonance

We demonstrate a minimally invasive nuclear magnetic resonance (NMR) technique that enables determination of the surface-area-to-volume ratio (S/V) of soft porous materials from measurements of the diffusive exchange of laser-polarized 129Xe between gas in the pore space and 129Xe dissolved in the solid phase. We apply this NMR technique to porous polymer samples and find approximate agreement with destructive stereological measurements of S/V obtained with optical confocal microscopy. Potential applications of laser-polarized xenon interphase exchange NMR include measurements of in vivo lung function in humans and characterization of gas chromatography columns.

Non-NASA Center↗