Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “chemical specificity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54

Feasibility Study for Cathodic Protection of Waste Tanks at Hanford

The Hanford Nuclear Reservation site contains approximately 211 million liters of radioactive and chemically hazardous waste arising from nuclear weapons production, beginning with World War II, and continuing through the Cold War. The waste is stored in 177 carbon-steel underground storage tanks, of which 149 are single-shell tanks (SSTs) and the remaining are double-shell tanks (DSTs). The mission of an ongoing River Protection Project is to retrieve the waste from the underground storage tanks and then treat and immobilize (i.e., vitrify) it for disposal. Waste from the older SSTs is being progressively retrieved into the newer DSTs for storage pending treatment, immobilization, and disposal. Waste chemistry controls are in place to mitigate general corrosion, pitting corrosion, and stress corrosion cracking (SCC) and minimize corrosion risks to the carbon steel tank liners of DST at the Hanford Site. The chemistry control program focuses on preserving liner integrity while balancing the need for caustic/nitrite additions that have large downstream impacts on vitrification. Some of the DSTs store salt cake or sludge waste layers contain out-of-specification interstitial liquids that contact the primary tank bottom or sidewall. Remediation of such layers through chemical additions is not practical. At the present time, the most significant leak integrity concern at Hanford is for corrosion of the tank bottoms of DSTs where the solids layer is out of specification because of hydroxide ion depletion and consequently, pH values that are less than 12. Cathodic protection (CP) has been proposed as a possible way to protect the liners of such tanks against corrosion. The objective of this project was to investigate the feasibility of applying CP to Hanford DSTs to mitigate internal corrosion of the carbon steel tank primary liners. The scope of the project included (1) a literature review on the application of CP to storage tank systems, in general, and to waste tanks at the Savannah River Site (SRS) and Hanford, (2) a review of the finite element analysis (FEA) model recently developed to evaluate potentials for a DST, and (3) the development of a boundary element analysis (BEA) model for CP for a DST. Tank AN-107, one of the Hanford DSTs, was selected for this work because (1) the bottommost waste layer in the tank is out-of-specification, and (2) electrochemical and resistivity data, based on recent waste sampling and testing, are available for this tank. The overarching conclusion of this study is that, based on the available information, it is feasible to apply CP to mitigate internal corrosion of the primary liners of the Hanford DSTs. However, significant additional information and work are required before a CP system can be designed. Recommendations for next steps in the design of the CP system will be presented.

WIERSMA, BRUCE↗

Nuclear Thermal Propulsion (NTP): A Proven Growth Technology for Human NEO/Mars Exploration Missions

The nuclear thermal rocket (NTR) represents the next "evolutionary step" in high performance rocket propulsion. Unlike conventional chemical rockets that produce their energy through combustion, the NTR derives its energy from fission of Uranium-235 atoms contained within fuel elements that comprise the engine s reactor core. Using an "expander" cycle for turbopump drive power, hydrogen propellant is raised to a high pressure and pumped through coolant channels in the fuel elements where it is superheated then expanded out a supersonic nozzle to generate high thrust. By using hydrogen for both the reactor coolant and propellant, the NTR can achieve specific impulse (Isp) values of ~900 seconds (s) or more - twice that of today s best chemical rockets. From 1955 - 1972, twenty rocket reactors were designed, built and ground tested in the Rover and NERVA (Nuclear Engine for Rocket Vehicle Applications) programs. These programs demonstrated: (1) high temperature carbide-based nuclear fuels; (2) a wide range of thrust levels; (3) sustained engine operation; (4) accumulated lifetime at full power; and (5) restart capability - all the requirements needed for a human Mars mission. Ceramic metal "cermet" fuel was pursued as well, as a backup option. The NTR also has significant "evolution and growth" capability. Configured as a "bimodal" system, it can generate its own electrical power to support spacecraft operational needs. Adding an oxygen "afterburner" nozzle introduces a variable thrust and Isp capability and allows bipropellant operation. In NASA s recent Mars Design Reference Architecture (DRA) 5.0 study, the NTR was selected as the preferred propulsion option because of its proven technology, higher performance, lower launch mass, versatile vehicle design, simple assembly, and growth potential. In contrast to other advanced propulsion options, no large technology scale-ups are required for NTP either. In fact, the smallest engine tested during the Rover program - the 25,000 lbf (25 klbf) "Pewee" engine is sufficient when used in a clustered engine arrangement. The "Copernicus" crewed spacecraft design developed in DRA 5.0 has significant capability and a human exploration strategy is outlined here that uses Copernicus and its key components for precursor near Earth object (NEO) and Mars orbital missions prior to a Mars landing mission. The paper also discusses NASA s current activities and future plans for NTP development that include system-level Technology Demonstrations - specifically ground testing a small, scalable NTR by 2020, with a flight test shortly thereafter.

Borowski, Stanley K.↗

Exploring Ligand-to-Metal Charge-Transfer States in the Photo-Ferrioxalate System Using Excited-State Specific Optimization

The photo-ferrioxalate system (PFS), [Fe(III)(C 2 O 4 )] 3– , more than an exact chemical actinometer, has been extensively applied in wastewater and environment treatment. Despite many experimental efforts to improve clarity, important aspects of the mechanism of ferrioxalate photolysis are still under debate. In this paper, we employ the recently developed WΓ-CASSCF to investigate the ligand-to-metal charge-transfer states that are key to ferrioxalate photolysis. This investigation provides a qualitative picture of these states and key potential energy surface features related to the photolysis. Furthermore, our theoretical results are consistent with the prompt charge-transfer picture seen in recent experiments and clarify some features that are not visible in experiments. Two ligand-to-metal charge-transfer states contribute to the photolysis of ferrioxalate, and the avoided crossing barrier between them is low compared with the initial photoexcitation energy. Our data also clarify that one Fe–O bond cleaves first, followed by the C–C bond and the other Fe–O bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep learning workflow for the inverse design of molecules with specific optoelectronic properties

The inverse design of novel molecules with a desirable optoelectronic property requires consideration of the vast chemical spaces associated with varying chemical composition and molecular size. First principles-based property predictions have become increasingly helpful for assisting the selection of promising candidate chemical species for subsequent experimental validation. However, a brute-force computational screening of the entire chemical space is decidedly impossible. To alleviate the computational burden and accelerate rational molecular design, we here present an iterative deep learning workflow that combines (i) the density-functional tight-binding method for dynamic generation of property training data, (ii) a graph convolutional neural network surrogate model for rapid and reliable predictions of chemical and physical properties, and (iii) a masked language model. As proof of principle, we employ our workflow in the iterative generation of novel molecules with a target energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO).

97 MATHEMATICS AND COMPUTING↗

Assessing the Origins of Aliphatic Amines in the Murchison Meteorite from their Compound-Specific Carbon Isotopic Ratios and Enantiomeric Composition

The study of meteoritic organic compounds provides a unique window into the chemical inventory of the early Solar System and prebiotic chemistry that may have been important for the origin of life on Earth. Multiple families of organic compounds have been extracted from the Murchison meteorite, which is one of the most thoroughly studied carbonaceous chondrites. The amino acids extracted from Murchison have been extensively analyzed, including measurements of non-terrestrial stable isotopic ratios and discoveries of L-enantiomeric excesses for alpha-dialkyl amino acids, notably isovaline. However, although the isotopic signatures of bulk amine-containing fractions have been measured, the isotopic ratios and enantiomeric composition of individual aliphatic amines, compounds that are chemically related to amino acids, remain unknown. Here, we report a novel method for the extraction, separation, identification and quantitation of aliphatic monoamines extracted from the Murchison meteorite. Our results show a complete suite of structural isomers, with a larger concentration of methylamine and ethylamine and decreasing amine concentrations with increasing carbon number. The carbon isotopic compositions of fourteen meteoritic aliphatic monoamines were measured, with delta C-13 values ranging from +21% to +129%, showing a decrease in C-13 with increasing carbon number, a relationship that may be consistent with the chain elongation mechanism under kinetic control previously proposed for meteoritic amino acids. We also found the enantiomeric composition of sec-butylamine, a structural analog to isovaline, was racemic within error, while the isovaline extracted from the same Murchison piece showed an L-enantiomeric excess of 9.7; this result suggested that processes leading to enantiomeric excess in the amino acid did not affect the amine. We used these collective data to assess the primordial synthetic origins of these meteoritic aliphatic amines and their potential linkage to meteoritic amino acids.

prebiotic chemistry↗

Pilot-Scale Pelleting Tests on High-Moisture Pine, Switchgrass, and Their Blends: Impact on Pellet Physical Properties, Chemical Composition, and Heating Values

In this study, we evaluated the pelleting characteristics of southern yellow pine (SYP), switchgrass (SG), and their blends for thermochemical conversion processes, such as pyrolysis and gasification. Using a pilot-scale ring-die pellet mill, we specifically assessed the impact of blend moisture, length-to-diameter (L/D) ratio in the pellet die, and ratio of pine to SG on the physico-chemical properties of the resulting pellets. We found that an increase in pine content by 25–50% marginally affected the bulk density; however, it also led to an increase in calorific value by 7% and a decrease in ash content by 72%. A moisture content of 25% (wet basis) and an L/D ratio of 5 resulted in poor pellet durability at <90% and bulk density values of <500 kg/m 3 , but increasing the L/D ratio to 9 and lowering the moisture content to 20% (w.b.) improved the pellet durability to >90% and the bulk density to >500 kg/m 3 . Blends with ≥50% pine content resulted in lower energy consumption, while a lower L/D ratio resulted in higher pelleting energy. Based on these findings, we successfully demonstrated the high-moisture pelleting of 2.5 ton of pine top residues blended with SG at 60:40 and 50:50 ratios. The quality of the pellets was monitored off-line and at-line by near infrared (NIR) spectroscopy. Multivariate models constructed by combining the NIR data and the pelleting process variables could successfully predict the pine content (R 2 = 0.99), higher heating value (R 2 = 0.98), ash (R 2 = 0.95), durability (R 2 = 0.94), and bulk density (R 2 = 0.86) of the pellets. Thus, we established how blending and densification of SYP and SG biomass could improve feedstock specifications and that NIR spectroscopy can effectively monitor the pellet properties during the high-moisture pelleting process.

09 BIOMASS FUELS↗

Macromolecular recognition: Structural aspects of the origin of the genetic system

Theoretical simulation of prebiotic chemical processes is an invaluable tool for probing the phenomenon of evolution of life. Using computational and modeling techniques and guided by analogies from present day systems we, seek to understand the emergence of genetic apparatus, enzymatic catalysis and protein synthesis under prebiotic conditions. In one possible scenario, the RNA enzymatic reaction plays a key role in the emergence of the self-replicating and offers a clue to the onset of enzymatic catalysis prior to the existence of the protein biosynthetic machinery. Our ultimate goal is to propose a simple RNA segment which contains the specificity and catalytic activity of the contemporary RNA enzyme and which could emerge in a primordial chemical environment. To understand the mechanism of ribozyme catalyzed reactions, ab initio and semi-empirical (ZINDO) programs were used to investigate the reaction path of transphosphorylation. A special emphasis was placed on the possible catalytic and structural roles played by the coordinated magnesium cation. Both the inline and adjacent mechanisms of transphosphorylation have been studied. Another important aspect of this reaction is the identity of the functional groups which are essential for the acid base catalysis. The structural characteristics of the target helices, particularly a possible role of G center dot T pair, is under examination by molecular dynamics (MD) simulation technique. Modeling of the ancestral aminoacyl-tRNA synthetases (aRS) may provide important clues to the emergence of the genetic code and the protein synthetic machinery. Assuming that the catalytic function evolved before the elements of specific recognition of a particular amino acid, we are exploring the minimal structural requirements for the catalysis of tRNA aminoacylation. The molecular modeling system SYBYL was used for this study based on the high resolution crystallographic structures of the present day tyrosyl-adenylate:tyrRS and tRNA(Gln): ATP:glnRS complexes. The trinucleotide CCA of the 3'-end tRNA is placed into the active site pocket of tyrRS, based on the scheme of interaction between tRNA(Gln) and glnRS, and upon the stereochemistry of the tyrRS:tRNA:Tyr-AMP transition state. This provides a model of the non-specific recognition of a tRNA's 3'-end by an aRS, which might be similar to that of the ancestral aRS's. In the next step, modeling of the rest of the acceptor stem of tRNA (Tyr) with tyrRS is carried out.

Rein, Robert↗

maslov-group/FUN-PROSE

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

Liu, Simon↗

FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

59 BASIC BIOLOGICAL SCIENCES↗

TChem-atm (v2.0.0): scalable performance-portable multiphase atmospheric chemistry

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high-performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. In a proof-of-concept integration with the particle-resolved model PartMC, TChem-atm reproduces the existing PartMC–CAMP implementation within solver tolerances and delivers substantial GPU speedups, especially for large particle populations. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. TChem-atm enables performance-portable execution across CPUs and GPUs, though optimal efficiency may require modest architecture-specific tuning (e.g., team and vector sizes), with up to a twofold improvement on the NVIDIA H100. It directly supports sectional and particle-resolved host models, while modal aerosol schemes require minor adaptation to provide particle-scale quantities such as representative diameters. By enabling chemically detailed, multiphase simulations with performance portability and host-model flexibility, TChem-atm facilitates the incorporation of advanced chemistry into atmospheric models.

Díaz-Ibarra, Oscar Homero [Sandia National Laborat↗

Intraspecific variability in plant and soil chemical properties in a common garden plantation of the energy crop Populus

Optimizing crops for synergistic soil carbon (C) sequestration can enhance CO 2 removal in food and bioenergy production systems. Yet, in bioenergy systems, we lack an understanding of how intraspecies variation in plant traits correlates with variation in soil biogeochemistry. This knowledge gap is exacerbated by both the heterogeneity and difficulty of measuring belowground traits. Here, we provide initial observations of C and nutrients in soil and root and stem tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes—established for aboveground biomass-to-biofuels research. Our goal was to explore the value of such field sites for evaluating genotype-specific effects on soil C, which ultimately informs the potential for optimizing bioenergy systems for both aboveground productivity and belowground C storage. To do this, we investigated variation in chemical traits at the scale of individual trees and genotypes and we explored correlations among stem, root, and soil samples. We observed substantial variation in soil chemical properties at the scale of individual trees and specific genotypes. While correlations among elements were observed both within and among sample types (soil, stem, root), above-belowground correlations were generally poor. We did not observe genotype-specific patterns in soil C in the top 10 cm, but we did observe genotype associations with soil acid-base chemistry (soil pH and base cations) and bulk density. Finally, a specific phenotype of interest (high vs low lignin) was unrelated to soil biogeochemistry. Our pilot study supports the usefulness of decade-old, genetically-variable, Populus bioenergy field test plots for understanding plant genotype effects on soil properties. Finally, this study contributes to the advancement of sampling methods and baseline data for Populus systems in the Pacific Northwest, USA. Further species- and region-specific efforts will enhance C predictability across scales in bioenergy systems and, ultimately, accelerate the identification of genotypes that optimize yield and carbon storage.

54 ENVIRONMENTAL SCIENCES↗

The nanosphere iron mineral(s) in Mars soil

A series of surface-modified clays containing nanophase (np) iron/oxyhydroxides of extremely small particle sizes, with total iron contents as high as found in Mars soil, were prepared by iron deposition on the clay surface from ferrous chloride solution. Comprehensive studies of the iron mineralogy in these 'Mars-soil analogs' were conducted using chemical extractions, solubility analyses, pH and redox, x ray and electron diffractometry, electron microscopic imaging specific surface area and particle size determinations, differential thermal analyses, magnetic properties characterization, spectral reflectance, and Viking biology simulation experiments. The clay matrix and the procedure used for synthesis produced nanophase iron oxides containing a certain proportion of divalent iron, which slowly converts to more stable, fully oxidized iron minerals. The noncrystalline nature of the iron compounds precipitated on the surface of the clay was verified by their complete extractability in oxalate. Lepidocrocite (gamma-FeOOH) was detected by selected area electron diffraction. It is formed from a double iron Fe(II)/Fe(III) hydroxyl mineral such as 'green rust', or ferrosic hydroxide. Magnetic measurements suggested that lepidocrocite converted to the more stable meaghemite (gamma-Fe203) by mild heat treatment and then to nanophase hematite (aplha-Fe203) by extensive heat treatment. Their chemical reactivity offers a plausible mechanism for the somewhat puzzling observations of the Viking biology experiments. Their unique chemical reactivities are attributed to the combined catalytic effects of the iron oxide/oxyhydroxide and silicate phase surfaces. The mode of formation of these (nanophase) iron oxides on Mars is still unknown.

Banin, A.↗

Aqueous Chemical Modeling of Sedimentation on Early Mars with Application to Surface-Atmosphere Evolution

This project was to investigate models for aqueous sedimentation on early Mars from fluid evaporation. Results focused on three specific areas: (1) First, a fluid evaporation model incorporating iron minerals was developed to compute the evaporation of a likely solution on early Mars derived from the weathering of mafic rock. (2) Second, the fluid evaporation model was applied to salts within Martian meteorites, specifically salts in the nakhlites and ALH84001. Evaporation models were found to be consistent with the mineralogy of salt assemblages-anhydrite, gypsum, Fe-Mg-Ca carbonates, halite, clays-- and the concentric chemical fractionation of Ca-to Mg-rich carbonate rosettes in ALH84001. We made progress in further developing our models of fluid concentration by contributing to updating the FREZCHEM model. (3) Third, theoretical investigation was done to determine the thermodynamics and kinetics involved in the formation of gray, crystalline hematite. This mineral, of probable ancient aqueous origin, has been observed in several areas on the surface of Mars by the Thermal Emission Spectrometer on Mars Global Surveyor. The "Opportunity" Mars Exploration Rover has also detected gray hematite at its landing site in Meridiani Planum. We investigated how gray hematite can be formed via atmospheric oxidation, aqueous precipitation and subsequent diagenesis, or hydrothermal processes. We also studied the geomorphology of the Aram Chaos hematite region using Mars Orbiter Camera (MOC) images.

Catling, David C.↗

Combined 1-MW Solar Electric and Chemical Propulsion for Crewed Mars Missions

The current Moon to Mars Architecture defines functional capabilities that are essential to achieving NASA’s specific exploration goals and objectives. The transportation system goals and objectives or functional capabilities do not prescribe a solution, leaving an open tradespace to be explored. NASA is working to identify power and propulsion technologies that enable feasible transportation options for crewed missions to Mars. During NASA’s Strategic Analysis Cycle 2021 (SAC21), nuclear enabled spacecraft concepts were analyzed for moderate duration 850-day Earth-Mars roundtrip mission2. During SAC22, the transportation tradespace was expanded to understand the feasibility of using different propulsion systems for crewed Mars missions using a moderate duration reference mission as a comparison point. This paper explores the mission analysis performed for a conceptual MW-class hybrid Solar Electric Propulsion (SEP)-chemical propulsion system (SEP-Chem) spacecraft optimized for an 850-day crewed Mars mission for the 2039 opportunity.

SEP-Chem↗

Ion‐Specific Interactions Engender Dynamic and Tailorable Properties in Biomimetic Cationic Polyelectrolytes

Abstract Biomaterials such as spider silk and mussel byssi are fabricated by the dynamic manipulation of intra‐ and intermolecular biopolymer interactions. Organisms modulate solution parameters, such as pH and ion co‐solute concentration, to effect these processes. These biofabrication schemes provide a conceptual framework to develop new dynamic and responsive abiotic soft material systems. Towards these ends, the chemical diversity of readily available ionic compounds offers a broad palette to manipulate the physicochemical properties of polyelectrolytes via ion‐specific interactions. In this study, we show for the first time that the ion‐specific interactions of biomimetic polyelectrolytes engenders a variety of phase separation behaviors, creating dynamic thermal‐ and ion‐responsive soft matter that exhibits a spectrum of physical properties, spanning viscous fluids to viscoelastic and viscoplastic solids. These ion‐dependent characteristics are further rendered general by the merger of lysine and phenylalanine into a single, amphiphilic vinyl monomer. The unprecedented breadth, precision, and dynamicity in the reported ion‐dependent phase behaviors thus introduce a broad array of opportunities for the future development of responsive soft matter; properties that are poised to drive developments in critical areas such as chemical sensing, soft robotics, and additive manufacturing.

Aubrecht, Filip J.↗

Lift-Off Acoustics Predictions for the Ares I Launch Pad

The vibroacoustic environment associated with large launch vehicles is of concern for the integrity of the launch complex and the vehicle itself. A large body of knowledge of this environment was developed during the early years of the missile and space flight, particularly during the Apollo program. Reference 1, prepared by Sutherland and others during that era, contains much of that knowledge. A specific process for predicting noise on and around the vehicle itself and the launcher is presented in Reference 2, prepared by Eldred, et al. Recent reviews of the process, e.g., Reference 3, have suggested some revised details but generally support the methodology in Reference 2.

Launch Pad↗

Resilient Hydrogels from the Nanoscale to the Macroscale

Biological systems illustrate how a material composed of fragile molecular components can collectively be highly resilient. While the average protein, cell, or even tissue may not last more than a few weeks, many animals and plants live for more than a century. Continual component regeneration and multiple systems to resist mechanical and chemical damage together make this longetivity possible. This project sought to develop biomimetic methods to enable a specific type of material, a hydrogel, to resist damage across multiple scales using distinct, modular damage protection mechanisms. Because hydrogels share many features with biological tissues, they are an ideal substrate for exploring biomimetic strategies for designing resilience and self-repair. We specifically focused in this study on DNA-crosslinked hydrogels, which contain DNA strands that can serve as material to link it together or to control its current state or properties. We investigated how new tools from dynamic DNA nanotechnology could make it possible to actively recover from damage by continually growing and forming a materials shape, or by identifying damage and directing an adaptive response to that damage involving chemical synthesis to reconstruct a structure. We developed embedded molecular sensors able to detect and strain of the gel before damage occurred and react to counteract damage. We also developed methods to continually create shapes and patterns using chemical processes that will allow those patterns to reform when they are damaged. The ability to design resilient materials capable of self-repair has important implications for materials engineering. Instead of designing a material to withstand the worst stresses it may encounter, we could instead design a material to survive under average conditions, but self-repair or reconfigure to resist impending damage. Resilient, self-repairing hydrogels will also have diverse applications such as sensors or actuators.

36 MATERIALS SCIENCE↗