Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “bio-inspired process”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Bio-inspired interlocking metasurfaces

Interlocking metasurfaces (ILMs) are patterned arrays of mating features that enable the joining of bodies by constraining motion and transmitting force. They offer an alternative to traditional joining solutions such as mechanical fasteners, welds, and adhesives. This study explores the development of bio-inspired ILMs using a problem-driven bioinspired design (BID) framework. We develop a taxonomy of attachment solutions that considers both biological and engineered systems and derive conventional design principles for ILM design. We conceptualize two engineering implementations to demonstrate concept development using the taxonomy and ILM conventional design principle through the BID framework: one for rapidly assembled bridge truss members and another for modular microrobots. These implementations highlight the potential of BID to enhance performance, functionality, and tunability in ILMs.

attachment↗
NASA NTRS2003

Concepts and Development of Bio-Inspired Distributed Embedded Wired/Wireless Sensor Array Architectures for Acoustic Wave Sensing in Integrated Aerospace Vehicles

This paper discusses the modeling of acoustic emissions in plate structures and their sensing by embedded or surface bonded piezoelectric sensor arrays. Three different modeling efforts for acoustic emission (AE) wave generation and propagation are discussed briefly along with their advantages and disadvantages. Continuous sensors placed at right angles on a plate are being discussed as a new approach to measure and locate the source of acoustic waves. Evolutionary novel signal processing algorithms and bio-inspired distributed sensor array systems are used on large structures and integrated aerospace vehicles for AE source localization and preliminary results are presented. These systems allow for a great reduction in the amount of data that needs to be processed and also reduce the chances of false alarms from ambient noises. It is envisioned that these biomimetic sensor arrays and signal processing techniques will be useful for both wireless and wired sensor arrays for real time health monitoring of large integrated aerospace vehicles and earth fixed civil structures. The sensor array architectures can also be used with other types of sensors and for other applications.

Ghoshal, Anindya↗
NASA NTRS2012

Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment

A novel cognitive computing architecture is conceptualized for processing multiple channels of multi-modal sensory data streams simultaneously, and fusing the information in real time to generate intelligent reaction sequences. This unique architecture is capable of assimilating parallel data streams that could be analog, digital, synchronous/asynchronous, and could be programmed to act as a knowledge synthesizer and/or an "intelligent perception" processor. In this architecture, the bio-inspired models of visual pathway and olfactory receptor processing are combined as processing components, to achieve the composite function of "searching for a source of food while avoiding the predator." The architecture is particularly suited for scene analysis from visual data and odorant.

Duong, Tuan A.↗
DOE OSTI2024

Mechanochemical topological defects in an active nematic

We propose a reaction-diffusion system that converts topological information of an active nematic into chemical signals. We show that a curvature-activated reaction dipole is sufficient for creating a system that dynamically senses topology by producing a concentration field possessing local extrema coinciding with ±$\frac{1}{2}$ defects. The enabling term is analogous to polarization charge density seen in dielectric materials. We demonstrate the ability of this system to identify defects in both passive and active nematics. Our results illustrate that a relatively simple feedback scheme, expressed as a system of partial differential equations, is capable of producing chemical signals in response to inherently nonlocal structures in anisotropic media. Here, we posit that such coarse-grained systems can help generate testable hypotheses for regulated processes in biological systems, such as morphogenesis, and motivate the creation of bio-inspired materials that utilize dynamic coupling between nematic structure and biochemistry.

42 ENGINEERING↗
DOE OSTI2025

Extending High-Level Synthesis with AI/ML Methods

Artificial Intelligence (AI) and Machine Learning (ML) methods provide significant opportunities of improving quality of results when performing high-level synthesis (HLS). For example, they can be used to model and predict metrics of the final design (e.g., area, considering aspects such as interconnect overhead for different device technologies), facilitating exploration when searching for the best design trade-offs. They can also enable identifying hidden correlations across the various phases of the synthesis and the various optimizations performed, identifying the most effective pipelines. Finally, in more general terms, bio-inspired heuristic algorithms can improve the design space exploration for the synthesis process in terms of time and quality of the result. This paper discusses opportunities and challenges to augment HLS with AI/ML using as example flow the SODA Synthesizer, an open-source hardware generation toolchain which includes SODA-OPT, a hardware/software partitioning and pre-optimization tool developed with the MLIR framework, and PandA-Bambu, a state-of-the art HLS tool. SODA interfaces with OpenROAD to provide a complete end-to-end toolchain.

artificial intelligence↗
DOE OSTI2026

Peptide‐Induced Ferroelectricity in Charge‐Transfer Supramolecular Materials

Organic ferroelectrics are of great interest in sustainable energy conversion, information storage, flexible electronics, and potential biomedical applications as soft implants, among many other applications. Despite their broad potential, the development of organic ferroelectrics has remained limited, with only a few known examples in solid-state systems, primarily due to the lack of well-established design strategies compared to inorganic systems. Bio-inspired supramolecular chemistry offers a path to create functional nanostructures that are water-processable and biocompatible. We report here on supramolecular charge transfer (CT) systems in which peptides are covalently linked to dyads of electron-donating and electron-accepting moieties, creating amphiphiles that self-assemble into nanoscale ribbons in water. The peptide chirality-induced symmetry breaking in these crystalline nanostructures not only results in second harmonic activity but also generates ferroelectric behavior across multiple CT systems, demonstrating a versatile supramolecular approach to the design of new organic ferroelectrics. Furthermore, culturing primary neuron cells on coatings of the ferroelectric materials promoted axonal growth and enhanced action potentials, indicating improved neuronal maturity facilitated by the polar structure of the ferroelectric nanomaterials. The supramolecular strategy used here holds promise to create new water-processable ferroelectric biomaterials, opening avenues for innovative applications in cell charge transfer, neuronal axon growth, peptide symmetry breaking, self-assembling peptides, supramolecular ferroelectrics, proliferation, and bioelectronics.

charge transfer↗
DOE OSTI2026

Mapping Interfacial Solution Forces that Drive Fluorescent Nanoparticle Incorporation into Crystals

Interfacial solution structure governs processes ranging from catalytic and electrochemical reactions to particle aggregation and crystallization. Here, we design bio-inspired nanocomposites by mapping interfacial forces and controlling nanoparticle incorporation during crystal growth. Our analytical model contains measured kinetic barriers for surface approaches and equilibrium binding constants with the crystal surface. We validate this model using fluorescent silica nanoparticles and calcite. Our results show that surface chemistry dictates incorporation pathways: methoxy groups are least favorable, hydroxyls reduce kinetic barriers by interacting favorably with hydration layers, carboxylates bind strongly but must overcome a kinetic barrier, and amines outperform all kinetically and thermodynamically. This framework resolves the interplay between interfacial solution structures, particle forces and dynamics, and growth kinetics, enabling predicative control of nanocomposite formation and multiplexed mixed-particle systems.

Zhang, Mingyi [Pacific Northwest National Laborato↗
NASA NTRS2009

Bio-Inspired Neural Model for Learning Dynamic Models

A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

Duong, Tuan↗
NASA NTRS2012

Shape and Color Features for Object Recognition Search

A bio-inspired shape feature of an object of interest emulates the integration of the saccadic eye movement and horizontal layer in vertebrate retina for object recognition search where a single object can be used one at a time. The optimal computational model for shape-extraction-based principal component analysis (PCA) was also developed to reduce processing time and enable the real-time adaptive system capability. A color feature of the object is employed as color segmentation to empower the shape feature recognition to solve the object recognition in the heterogeneous environment where a single technique - shape or color - may expose its difficulties. To enable the effective system, an adaptive architecture and autonomous mechanism were developed to recognize and adapt the shape and color feature of the moving object. The bio-inspired object recognition based on bio-inspired shape and color can be effective to recognize a person of interest in the heterogeneous environment where the single technique exposed its difficulties to perform effective recognition. Moreover, this work also demonstrates the mechanism and architecture of the autonomous adaptive system to enable the realistic system for the practical use in the future.

Duong, Tuan A.↗
NASA NTRS2012

Materials, Structures and Manufacturing: An Integrated Approach to Develop Expandable Structures

Membrane dominated space structures are lightweight and package efficiently for launch; however, they must be expanded (deployed) in-orbit to achieve the desired geometry. These expandable structural systems include solar sails, solar power arrays, antennas, and numerous other large aperture devices that are used to collect, reflect and/or transmit electromagnetic radiation. In this work, an integrated approach to development of thin-film damage tolerant membranes is explored using advanced manufacturing. Bio-inspired hierarchical structures were printed on films using additive manufacturing to achieve improved tear resistance and to facilitate membrane deployment. High precision, robust expandable structures can be realized using materials that are both space durable and processable using additive manufacturing. Test results show this initial work produced higher tear resistance than neat film of equivalent mass. Future research and development opportunities for expandable structural systems designed using an integrated approach to structural design, manufacturing, and materials selection are discussed.

Belvin, W. Keith↗
DOE OSTI2025

Reversible self-assembly of small molecules for recyclable solid-state battery electrolytes

Performance often overshadows recyclability in contemporary battery designs, leading to sustainability challenges. Preemptive strategies integrating recyclable chemistry from the outset are thus increasingly critical for addressing the complexities in conventional recycling. Here we harness bio-inspired molecular self-assembly to create inherently recyclable battery materials. We use aramid amphiphiles that self-assemble in water through strong, collective hydrogen bonding and π–π stacking, forming air-stable, high-aspect-ratio nanoribbons with gigapascal-level stiffness. When processed into bulk solid-state electrolytes, these nanoribbons retain their ordered molecular arrangement and exhibit total conductivities of 1.6 × 10 −4 S cm −1 at 50 °C, Young’s moduli of 70 MPa and toughness values of 1 MJ m −3 , despite being stabilized solely by reversible non-covalent bonds. We further demonstrate clean separation of battery components by exposing used cells to an organic solvent, which disrupts the non-covalent cohesion and reverts all battery components to their original forms. Furthermore, this study underscores the potential of molecular self-assembly for specialized recyclable designs in energy storage applications.

Batteries↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2013

Microgravity Fluids for Biology, Workshop

Microgravity Fluids for Biology represents an intersection of biology and fluid physics that present exciting research challenges to the Space Life and Physical Sciences Division. Solving and managing the transport processes and fluid mechanics in physiological and biological systems and processes are essential for future space exploration and colonization of space by humans. Adequate understanding of the underlying fluid physics and transport mechanisms will provide new, necessary insights and technologies for analyzing and designing biological systems critical to NASAs mission. To enable this mission, the fluid physics discipline needs to work to enhance the understanding of the influence of gravity on the scales and types of fluids (i.e., non-Newtonian) important to biology and life sciences. In turn, biomimetic, bio-inspired and synthetic biology applications based on physiology and biology can enrich the fluid mechanics and transport phenomena capabilities of the microgravity fluid physics community.

biology↗
NASA NTRS2004

Development of Biomorphic Flyers

Biomorphic flyers have recently been demonstrated that utilize the approach described earlier in "Bio-Inspired Engineering of Exploration Systems" (NPO-21142), NASA Tech Briefs, Vol. 27, No. 5 (May 2003), page 54, to distill the principles found in successful, nature-tested mechanisms of flight control. Two types of flyers are being built, corresponding to the imaging and shepherding flyers for a biomorphic mission described earlier in "Cooperative Lander- Surface/Aerial Microflyer Missions for Mars Exploration" (NPO-30286), NASA Tech Briefs, Vol. 28, No. 5 (May 2004), page 36. The common features of these two types of flyers are that both are delta-wing airplanes incorporating bio-inspired capabilities of control, navigation, and visual search for exploration. The delta-wing design is robust to approx.40 G axial load and offers ease of stowing and packaging. The prototype that we have built recently is shown in the figure. Such levels of miniaturization and autonomous navigation are essential to enable biomorphic microflyers (<1 kg) that can be deployed in large numbers for distributed measurements and exploration of difficult terrain while avoiding hazards. Individual bio-inspired sensors that will be incorporated in a biomorphic flyer have been demonstrated recently. These sensors include a robust, lightweight (~6 g), and low-power (~40 mW) horizon sensor for flight stabilization. It integrates successfully the principles of the dragonfly ocelli. The ocelli are small eyes on the dorsal and forward regions of the heads of many insects. The ocelli are distinct from the compound eyes that are most commonly associated with insect vision. In many insects, the ocelli are little more than single-point detectors of short-wavelength light and behavioral responses to ocelli stimuli are hard to observe. The notable exception is found in dragonflies, where flight control is notably degraded by any interference with the ocellar system. Our team has discovered recently that the ocelli are a dedicated horizon sensor, with substantial optical processing and multiple spectral sensitivity. To our knowledge, this is the world s first demonstrated use of a "biomorphic ocellus" as a flight-stabilization system. The advantage of the ocelli over a similarly sized system of rate gyroscopes is that both attitude control and rate damping can be realized in one device. A full inertial unit and significant processing would otherwise be required to achieve the same effect. As a prelude to full autonomy, substantial stability augmentation is provided to the pilot at very low cost in terms of space, power, and mass. The sensor is about 40 times lighter than a comparable inertial attitude reference system. Other significant features of the biomorphic flyer shown in the figure include its ability to fly at high angles of attack ~30 and a deep wing chord which allows scaling to small size and low Reynold s number situations. Furthermore, the placement of the propulsion system near the center of gravity allows continued control authority at low speeds. These attributes make such biomorphic flyers uniquely suited to planetary and terrestrial exploration where small size and autonomous airborne operation are required.

Thakoor, Sarita↗
DOE OSTI2025

Nature-inspired lotus-shaped fins combined with hybrid nanoparticles and metal foam for high-performance latent heat thermal energy storage

Latent heat thermal energy storage (LHTES) systems play a critical role in renewable energy integration by providing high energy density and nearly isothermal operation during phase transitions. However, their performance is often limited by slow melting/charging rates, which motivates the search for enhanced heat transfer designs. This study investigates the melting behavior of RT-82 phase change material (PCM) using novel lotus-shaped fins combined with copper metal foam and conductive graphene nanoparticles and carbon nanotubes. A two-dimensional enthalpy-porosity model in ANSYS Fluent was developed to simulate the charging/melting process, capturing non-thermal equilibrium between the foam and PCM/nano-PCM. In this study, effects of fin geometry, nanoparticle concentration, and foam porosity on melting dynamics and cost-performance trade-offs were investigated. Results showed that natural convection accelerated melting by ~12% compared to conduction-only scenarios. Optimized lotus-shaped fins with higher fin density (T3F4 and T3F10) achieved up to 63% faster melting relative to sparse configurations. Graphene nanoparticles improved thermal conductivity, with a 6% volume fraction, by reducing melting time by ~6.9%, while their combination with 75% porosity foam achieved a maximum reduction in the melting time of ~51% compared to pure PCM. Cost-performance analysis identified T3F4 as the most balanced design, offering rapid thermal response without excessive material costs, while moderate-density designs like T3S6 provided economical alternatives with acceptable performance. These results highlight the performance enhancement that can be achieved by integrating bio-inspired fins, nanoparticles, and foams, into compact and efficient LHTES for solar heating, building thermal management, and industrial waste-heat recovery applications.

25 ENERGY STORAGE↗
DOE OSTI2025

Closed-Loop Control of Active Nematic Flows

Stabilizing and shaping autonomous flows of active fluids is a fundamental challenge and a prerequisite for applications. We embed a light-responsive microtubule-based nematic in a proportional-integral control loop that adjusts the applied light intensity in response to real-time measurements of the spatially averaged flow speed. The self-regulating hardware-software-wetware system maintains a target flow speed against external or internal perturbations, including protein aging and aggregation, sample-to-sample variability, and temperature variation. Varying the controller’s gains reveals antagonistic roles between feedback and intrinsic processes, leading to nontrivial dynamics observed in fluctuation spectra. In particular, oscillations emerge from the interplay between the controller, motor binding kinetics, and active hydrodynamic relaxation. Accounting for the underlying binding timescale, our coarse-grained model and nematohydrodynamics simulations corroborate these observations. This work provides insight into the coupled dynamics of controlled active matter, laying the foundation for spatiotemporal patterning of active stress to generate and stabilize new dynamical configurations.

Active nematics↗
DOE OSTI2025

Morphogenic Growth 3D Printing

Inspired by nature's morphogenesis, a new 3D printing process –growth printing (GP)– takes advantage of a self‐propagating curing front to produce 3D polymeric parts following a growth‐like development plan. The propagation of the curing front is driven by the exothermic polymerization of dicyclopentadiene (DCPD), which transforms the liquid resin into a stiff polymer as it propagates at 1 mm s −1 . GP is triggered when a heated initiator contacts the uncured liquid resin in an open container. The initiator nucleates the frontal polymerization reaction and the isotropic radial propagation of the growth front. Simultaneously, the initiator is moved up across the free surface of the resin, pulling the cured object out of the uncured resin. The motion trajectory of the initiator with respect to the free resin surface controls the growth morphology of the 3D part. An inverse design algorithm is developed to produce 3D parts by modeling the reaction‐diffusion‐driven solidification process. This process has substantial energy savings and high printing speeds.

3D printing↗
NASA NTRS2004

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Alena, Richard I.↗