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Results for “biologically inspired”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Confinement Controls the Bend Instability of Three-Dimensional Active Liquid Crystals

Spontaneous growth of long-wavelength deformations is a defining feature of active liquid crystals. We investigate the effect of confinement on the instability of 3D active liquid crystals in the isotropic phase composed of extensile microtubule bundles and kinesin molecular motors. When shear aligned, such fluids exhibit finite-wavelength self-amplifying bend deformations. By systematically changing the channel size we elucidate how the instability wavelength and its growth rate depend on the channel dimensions. Experimental findings are qualitatively consistent with a minimal hydrodynamic model, where the fastest growing deformation is set by a balance of active driving and elastic relaxation. Furthermore, our results demonstrate that confinement determines the structure and dynamics of active fluids on all experimentally accessible length scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Fusion Intelligence: A Paradigm for Merging Natural and Artificial Intelligence

Here, this article presents fusion intelligence (FI), a bio-inspired paradigm that synergistically integrates the intrinsic capabilities of intelligent biological organisms with the advanced potential of artificial intelligence (AI)-driven systems. FI harnesses the unique intelligence, sensing, actuation, and mobility attributes of living organisms, such as honeybees, blending these with the sophisticated data-driven problem-solving functionalities of AI. By bridging the gap between natural intelligence (NI) and AI, FI can transform how humans interact with and harness the capabilities of both natural and artificial systems. This article presents the model of FI and its application to solve practical problems, discusses the challenges and future directions of FI research, emphasizing a generalized approach to solve complex problems, where AI can observe/control NI in a closed-loop system. We demonstrate the potential for FI to enhance the performance of an agricultural IoT system via a simulated case study, which achieves 50% improvement in the efficacy of insect pollination (entomophily).

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Nanomaterials and Sustainability

Nanostructuring adds a tremendous degree of tunability to the optical, electronic, magnetic, tribological, and chemical properties of matter. As a result, nanostructured materials already play major roles in the many technologies and industries that provide the comfort and convenience of our everyday lives. Although there are examples of nanostructured materials that currently enhance sustainable technologies, such as for batteries and electrolyzers, the potential impact of nanoscale materials on sustainability has likely not nearly been realized when one considers that the nanostructure–property–composition exploration phase space is almost infinite. We can find inspiration from nature, which builds and assembles nanostructured materials into hierarchical biological structures to perform the enormously complex functions of life, all the while doing so with a relatively small set of elements that are sustainably sourced. This contrasts with current technology, where performance demands often require a greater and greater diversity of elements from the periodic table, some of which are very challenging to be sustainably sourced or recycled.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning

Spiking Neural Networks (SNNs) are computational models inspired by the event-driven communication and connectivity patterns of biological neural circuits. They enable high energy efficiency and natural support for diverse architectures ranging from layered networks to small-world and graphstructured topologies. In this work, we introduce NeuroCoreX, an open-source, FPGA-based spiking neural network emulator that provides real-time, on-chip learning and flexible network organization. NeuroCoreX supports both feedforward sensory inputs streamed directly from sensors or PCs via UART and recurrent on-chip connectivity, enabling simultaneous processing and learning from external stimuli and internal network dynamics-capabilities rarely available in existing FPGA SNN platforms. The system implements a Leaky Integrate-and-Fire (LIF) neuron model with current-based synapses and supports pair-based STDP learning on both feedforward and recurrent synapses. A lightweight Python interface enables interactive configuration, live monitoring, weight read-back, and experiment control. Importantly, NeuroCoreX is tightly integrated with the SuperNeuroMAT simulator, allowing SNN models to be transferred seamlessly from software to hardware for hardware-in-the-loop development. By combining real-time plasticity, flexible connectivity, and an open-source VHDL implementation, NeuroCoreX provides an extensible and accessible platform for neuromorphic research, algorithm-hardware co-design, and energy-efficient edge intelligence.

Gautam, Ashish [ORNL]↗
DOE OSTI2020

Design of Chiral Domains by Surface Confinement of Liquid Crystals

Chirality, or absence of mirror symmetry, is a fascinating attribute of inanimate and living objects, which inspires artists and fascinates scientists in various disciplines, from physics to mathematics, biology to chemistry and crystallography. Producing and controlling the sense of handedness in systems formed by mirror-symmetric elements or containing an equal amount of left- and right-twisted elements is usually a nontrivial task. In this issue of ACS Central Science, Geonhyeong Park et al [1] demonstrate that a slab of a lyotropic chromonic liquid crystal (LCLC), formed by achiral molecules dispersed in water, can produce a periodic array of domains with left- and right-handed twists of the orientation of molecular aggregates. The twist develops over macroscopic regions of tens of microns in size and is caused by a balance of two facets of the orientational order pertinent to liquid crystals: the elastic response to deformations of orientation and anisotropy of surface interactions at confining boundaries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Vitamin-Mediated Glucose Flow Cell for Sustainable Power Generation

Glucose as biofuel asserts unique advantages, including low-temperature electricity generation, easy accessibility, low storage cost, and flexible application for on-demand power generation. Riboflavin, also known as Vitamin B 2 , is a critical component in biological systems and is involved in many metabolic reactions as enzyme cofactors. Inspired by these metabolic reactions, we demonstrate a flow cell for electrochemical glucose oxidation reaction (GOR), using riboflavin as an environmentally friendly mediator to replace traditional noble metal catalysts. When paired with O 2 under alkaline conditions, the glucose flow cell achieves a peak power density of 13 mW/cm 2 , 20 times higher than the previous report in alkaline conditions. The demonstrated vitamin-mediated engineered biofuel flow cell delivered high peak power density at room temperature/ambient pressure while maintaining low cost and environmental friendliness, eliminating the need for a noble metal catalyst.

electrolytes↗
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 OSTI2023

Electrochemical Characterization of Biomolecular Electron Transfer at Conductive Polymer Interfaces

Bio-electrochemical systems (BESs) are promising for renewable energy generation but remain hindered by inefficient electron transfer at electrode surfaces. As the toolbox of bio-anode materials increases, rigorous electrochemical characterization of emerging materials is needed. Here, we holistically characterize the electrochemical interaction of flavin mononucleotide (FMN), an electron shuttle in biological systems and a cofactor for oxidoreductase enzymes, with the bio-inspired mixed conducting polymer poly{3-[6'-(N-methylimidazolium)hexyl]thiophene} (P3HT-Im + ). The behavior of this polymer is compared to the equivalent polymer without the histidine-like imidazolium. We find improved conductivity and charge storage in imidazolium-containing polymers beyond what is explained by differences in the electroactive area. The P3HT-Im + further shows internal charge storage but with negligible faradaic contribution, indicating that charge storage capacity may translate to improved biocatalysis non-intuitive ways. Finally, one-electron transfer is observed between FMN and glassy carbon, while a bio-similar two-electron transfer is observed for the P3HT-Im + . To our knowledge, this is the first example of a concerted two-electron transfer between FMN and an electrode interface, which we attribute to the bio-inspired, histidine-like imidazolium functional groups in the polymer. These studies demonstrate the importance of bio-relevant materials characterization when such materials are deployed in BESs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The Architectural Dynamics of the Bacterial Flagellar Motor Switch

The rotary bacterial flagellar motor is remarkable in biochemistry for its highly synchronized operation and amplification during switching of rotation sense. The motor is part of the flagellar basal body, a complex multi-protein assembly. Sensory and energy transduction depends on a core of six proteins that are adapted in different species to adjust torque and produce diverse switches. Motor response to chemotactic and environmental stimuli is driven by interactions of the core with small signal proteins. The initial protein interactions are propagated across a multi-subunit cytoplasmic ring to switch torque. Torque reversal triggers structural transitions in the flagellar filament to change motile behavior. Subtle variations in the core components invert or block switch operation. The mechanics of the flagellar switch have been studied with multiple approaches, from protein dynamics to single molecule and cell biophysics. The architecture, driven by recent advances in electron cryo-microscopy, is available for several species. Computational methods have correlated structure with genetic and biochemical databases. The design principles underlying the basis of switch ultra-sensitivity and its dependence on motor torque remain elusive, but tantalizing clues have emerged. This review aims to consolidate recent knowledge into a unified platform that can inspire new research strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Boost of the Bio-memristor Performance for Artificial Electronic Synapses by Surface Reconstruction

Biomaterial-based memristors (bio-memristors) are often adopted to emulate biological synapse functions and applied to construct neural computing networks in brain-inspired chip systems. However, the randomness of conductive filament formation in bio-memristors inhibits their switching performance by causing the dispersion of the device-switching parameters. In this case, a facile porous silk fibroin (p-SF) memristor was obtained through a protein surface reconstruction strategy, in which the size of the hole can be adjusted by the density of hybrid nanoseeds. Here, the porous SF memristors exhibit greatly enhanced electrical characteristics, including uniform I-V cycles, centralized distribution of the switching voltages, and both high and low resistances, compared to devices without pores. The results of three-dimensional (3D) simulations based on classical density functional theory (cDFT) suggest that the reconstructed pores in the SF layers guide the formation and fracture of Ag filaments under an electric field and enhance the overall conductivity by separating Ag + ion and electron diffusion pathways. Ag + ions are predicted to preferentially diffuse through pores, whereas electrons diffuse through the SF network. Interestingly, the device conductance can be bidirectionally modulated gradually by positive and negative voltages, can faithfully simulate short-term and long-term plasticity, and can even realize the triplet-spike-timing-dependent plasticity (triplet-STDP) rule, which can be used for pattern recognition in biological systems. The simulation results reveal that a memristor network of this type has an accuracy of ~95.78% in memory learning and the capability of pattern learning. This work provides a facile technology route to improve the performance of bionic-material memristors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probabilistic measures for biological adaptation and resilience

This paper introduces an approach to quantifying ecological resilience in biological systems, particularly focusing on noisy systems responding to episodic disturbances with sudden adaptations. Incorporating concepts from nonequilibrium statistical mechanics, we propose a measure termed “ecological resilience through adaptation,” specifically tailored to noisy, forced systems that undergo physiological adaptation in the face of stressful environmental changes. Randomness plays a key role, accounting for model uncertainty and the inherent variability in the dynamical response among components of biological systems. Our measure of resilience is rooted in the probabilistic description of states within these systems and is defined in terms of the dynamics of the ensemble average of a model-specific observable quantifying success or well-being. Our approach utilizes stochastic linear response theory to compute how the expected success of a system, originally in statistical equilibrium, dynamically changes in response to a environmental perturbation and a subsequent adaptation. Importantly, the resulting mathematical derivations allow for the estimation of resilience in terms of ensemble averages of simulated or experimental data. Finally, through a simple but clear conceptual example, we illustrate how our resilience measure can be interpreted and compared to other existing frameworks in the literature. The methodology is general but inspired by applications in plant systems, with the potential for broader application to complex biological processes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Dendritic Computing with Multigate Ferroelectric Field-Effect Transistors

Although inspired by neuronal systems in the brain, artificial neural networks generally employ point-neurons, which offer computational complexity far less than that of their biological counterparts. Neurons have dendritic arbors that connect to different sets of synapses and offer local nonlinear accumulation – playing a pivotal role in processing and learning. Inspired by this, we propose a novel neuron design based on a multigate ferroelectric field-effect transistor that mimics dendrites. It leverages ferroelectric nonlinearity for local computations within dendritic branches while utilizing the transistor action to generate the neuronal output. The branched architecture enables smaller crossbar arrays in hardware integration, improving efficiency. Using an experimentally calibrated device-circuit-algorithm cosimulation framework, we demonstrate that networks incorporating our dendritic neurons achieve superior performance compared to much larger networks without dendrites (∼ 17× fewer trainable weight parameters). These findings suggest that dendritic hardware can significantly improve computational efficiency and learning capacity of neuromorphic systems optimized for edge applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Comprehensive Evaluation of Agrivoltaics Research: Breadth, Depth, and Insights for Future Research

Agrivoltaics integrates agricultural production with solar energy generation to address challenges related to land use, food security, and renewable energy development. This study provides the most comprehensive evaluation to date of global agrivoltaic research, aiming to classify the literature, identify strengths and gaps, and guide future work. We systematically screened over 3000 English-language publications through 2023 for relevant agrivoltaic publications. A total of 670 studies were categorized in the InSPIRE Data Portal across five agrivoltaic activities and multiple hierarchical themes, including physical, biological, technological, social, and crosscutting domains. We found that research was concentrated on crop production, microclimate dynamics, and PV performance, with gaps in areas like human health, wildlife, policy, and standardized methodologies. Although the U.S. emphasizes animal grazing and habitat-based systems in practice, most U.S.-based studies focused disproportionately on crop production. The analysis revealed uneven geographic and topical representation and highlighted a lack of integrated, interdisciplinary approaches. This study concludes that while agrivoltaic research has grown rapidly, more coordinated efforts could support standardized data collection, address overlooked ecological and social impacts, and align research focus with real-world system implementation, ultimately improving the scalability and successful deployment of agrivoltaic systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Adaptive nonequilibrium design of actin-based metamaterials: Fundamental and practical limits of control

The adaptive and surprising emergent properties of biological materials self-assembled in far-from-equilibrium environments serve as an inspiration for efforts to design nanomaterials. In particular, controlling the conditions of self-assembly can modulate material properties, but there is no systematic understanding of either how to parameterize external control or how controllable a given material can be. Here, we demonstrate that branched actin networks can be encoded with metamaterial properties by dynamically controlling the applied force under which they grow and that the protocols can be selected using multi-task reinforcement learning. These actin networks have tunable responses over a large dynamic range depending on the chosen external protocol, providing a pathway to encoding “memory” within these structures. Interestingly, we obtain a bound that relates the dissipation rate and the rate of “encoding” that gives insight into the constraints on control—both physical and information theoretical. Taken together, these results emphasize the utility and necessity of nonequilibrium control for designing self-assembled nanostructures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Decoupling copolymer, lipid and carbon nanotube interactions in hybrid, biomimetic vesicles

Bilayer vesicles that mimic a real biological cell can be tailored to carry out a specific function by manipulating the molecular composition of the amphiphiles. These bio-inspired and bio-mimetic structures are increasingly being employed for a number of applications from drug delivery to water purification and beyond. Complex hybrid bilayers are the key building blocks for fully synthetic vesicles that can mimic biological cell membranes, which often contain a wide variety of molecular species. While the assembly and morpholgy of pure phospholid bilayer vesicles is well understood, the functionality and structure dramaticlly changes when copolymer and/or carbon nanotube porins (CNTP) are added. The aim of this study is to understand how the collective molecular interactions within hybrid vesicles affect their nanoscale structure and properties. In situ small and wide angle X-ray scattering (SAXS/WAXS) and molecular dynamics simulations (MD) are used to investigate the morphological effect of molecular interactions between polybutadiene polyethylene oxide, lipids and carbon nanotubes (CNT) within the hybrid vesicle bilayer. Within the lipid/copolymer system, the hybrid bilayer morphology transitions from phase separated lipid and compressed copolymer at low copolymer loadings to a mixed bilayer where opposing lipids are mostly separated from the inner region. This transition begins between 60 wt% and 70 wt%, with full homogenization observed by 80 wt% copolymer. The incorporation of CNT into the hybrid vesicles increases the bilayer thickness and enhances the bilayer symmetry. Analysis of the WAXS and MD indicate that the CNT–dioleoyl interactions are much stronger than the CNT–polybutadiene.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Making the most of your electrons: Challenges and opportunities in characterizing hybrid interfaces with STEM

Inspired by the unique architectures composed of hard and soft materials in natural and biological systems, synthetic hybrid structures and associated hard-soft interfaces have recently evoked significant interest. Soft matter is typically dominated by structural fluctuations even at room temperature, while hard matter is governed by rigid mechanical behavior. This dichotomy offers considerable opportunities to leverage the disparate properties offered by these components across a wide spectrum spanning from basic science to engineering insights with significant technological overtones. Such hybrid structures, which include polymer nanocomposites, DNA functionalized nanoparticle superlattices, and metal organic frameworks to name a few, have delivered promising insights into the technologically relevant applications such as catalysis, environmental remediation, optoelectronics, and medicine. The interfacial structure between the hard and soft phases demonstrates features across a variety of length scales and often strongly influence the functionality of hybrid systems. While scanning/transmission electron microscopy (S/TEM) has proven to be a valuable tool for acquiring intricate molecular and nanoscale details of these interfaces, the unusual nature of hybrid composites presents a suite of challenges that make assessing or establishing structure–property relationships especially difficult. There are additional considerations at all stages of sample analysis from preparing electron-transparent samples to obtaining sufficient contrast to resolve the interface between dissimilar materials given the dose sensitivity of soft materials. Here, we discuss each of these challenges and supplement a review of recent developments in the field with additional experimental investigations and simulations to present solutions for attaining a nano or molecular-level understanding of these interfaces. These solutions present a host of opportunities for investigating the role interfaces play in this unique class of functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Pectin methylesterase selectively softens the onion epidermal wall yet reduces acid-induced creep

De-esterification of homogalacturonan (HG) is thought to stiffen pectin gels and primary cell walls by increasing calcium cross-linking between HG chains. Contrary to this idea, recent studies found that HG de-esterification correlated with reduced stiffness of living tissues, measured by surface indentation. The physical basis of such apparent wall softening is unclear, but possibly involves complex biological responses to HG modification. To assess the direct physical consequences of HG de-esterification on wall mechanics without such complications, we treated isolated onion (Allium cepa) epidermal walls with pectin methylesterase (PME) and assessed wall biomechanics with indentation and tensile tests. In nanoindentation assays, PME action softened the wall (reduced the indentation modulus). In tensile force/extension assays, PME increased plasticity, but not elasticity. These softening effects are attributed, at least in part, to increased electrostatic repulsion and swelling of the wall after PME treatment. Despite softening and swelling upon HG de-esterification, PME treatment alone failed to induce cell wall creep. Instead, acid-induced creep, mediated by endogenous α-expansin, was reduced. We conclude that HG de-esterification physically softens the onion wall, yet reduces expansin-mediated wall extensibility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Bioinspired energy absorbing material designs using additive manufacturing

Nature provides many biological materials and structures with exceptional energy absorption capabilities. Few, relatively simple molecular building blocks (e.g., calcium carbonate), which have unremarkable intrinsic mechanical properties individually, are used to produce biopolymer-bioceramic composites with unique hierarchical architectures, thus producing biomaterial-architectures with extraordinary mechanical properties. Several biomaterials have inspired the design and manufacture of novel material architectures to address various engineering problems requiring high energy absorption capabilities. For example, the microarchitecture of seashell nacre has inspired multi-material 3D printed architectures that outperform the energy absorption capabilities of monolithic materials. Using the hierarchical architectural features of biological materials, iterative design approaches using simulation and experimentation are advancing the field of bioinspired material design. However, bioinspired architectures are still challenging to manufacture because of the size scale and architectural hierarchical complexity. Notwithstanding, additive manufacturing technologies are advancing rapidly, continually providing researchers improved abilities to fabricate sophisticated bioinspired, hierarchical designs using multiple materials. This review describes the use of additive manufacturing for producing innovative synthetic materials specifically for energy absorption applications inspired by nacre, conch shell, shrimp shell, horns, hooves, and beetle wings. Potential applications include athletic prosthetics, protective head gear, and automobile crush zones.

36 MATERIALS SCIENCE↗