Magneto-Capillary Particle Dynamics at Curved Interfaces: Time-Varying Fields and Drop Mixing
Not provided.
catalysis (homogeneous), solar (photovoltaic), bio↗
SEARCH · Engineering Papers
Results for “BiO”
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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In Liquid Infrared Scattering Scanning Near-Field Optical Microscopy for Chemical and Biological Nanoimaging
Imaging biological systems with simultaneous intrinsic chemical specificity and nanometer spatial resolution in their typical native liquid environment has remained a long-standing challenge. In this paper we demonstrate a general approach of chemical nanoimaging in liquid based on infrared scattering scanning near-field optical microscopy (IR $s$-SNOM). It is enabled by combining AFM operation in a fluid cell with evanescent IR illumination via total internal reflection, which provides spatially confined excitation for minimized IR water absorption, reduced far-field background, and enhanced directional signal emission and sensitivity. We demonstrate in-liquid IR $s$-SNOM vibrational nanoimaging and conformational identification of catalase nano-crystals and spatio-spectral analysis of biomimetic peptoid sheets with monolayer sensitivity and chemical specificity at the few zeptomole level. This work establishes the principles of in-liquid and in-situ IR $s$-SNOM spectroscopic chemical nano-imaging and its general applicability to biomolecular, cellular, catalytic, electrochemical, or other interfaces and nano-systems in liquids or solutions.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
3D Temperature-Controlled Interchangeable Pattern for Size-Selective Nanoparticle Capture
Patterned surfaces with distinct regularity and structured arrangements have attracted great interest due to their extensive promising applications. Although colloidal patterning has conventionally been used to create such surfaces, herein, we introduce a novel 3D patterned poly(N-isopropylacrylamide) (PNIPAM) surface, synthesized by using a combination of colloidal templating and surface-initiated photoinduced electron transfer-reversible addition–fragmentation chain transfer (SI-PET-RAFT) polymerization. In order to investigate the temperature-driven 3D morphological variations at a lower critical solution temperature (LCST) of ~32 °C, multifaceted characterization techniques were employed. Atomic force microscopy confirmed the morphological transformations at 20 and 40 °C, while water contact angle measurements, upon heating, revealed distinct trends, offering insights into the correlation between surface wettability and topography adaptations. Moreover, quartz crystal microbalance with dissipation monitoring and electrochemical measurements were employed to detect the topographical adjustments of the unique hollow capsule structure within the LCST. Tests using different sizes of PSNPs shed light on the size-selective capture–release potential of the patterned PNIPAM, accentuating its biomimetic open–close behavior. Notably, our approach negates the necessity for expensive proteins, harnessing temperature adjustments to facilitate the noninvasive and efficient reversible capture and release of nanostructures. Finally, this advancement hopes to pave the way for future innovative cellular analysis platforms.
36 MATERIALS SCIENCE↗
Semiconductor Quantum Dots Are Efficient and Recyclable Photocatalysts for Aqueous PET-RAFT Polymerization
This Letter describes the use of CdSe quantum dots (QDs) as photocatalysts for photoinduced electron transfer reversible addition–fragmentation chain transfer (PET-RAFT) polymerization of a series of aqueous acrylamides and acrylates. In this work, the high colloidal solubility and photostability of these QDs allowed polymerization to occur with high efficiency (>90% conversion in 2.5 h), low dispersity (PDI < 1.1), and ultralow catalyst loading (<0.5 ppm). The use of protein concentrators enabled the removal of the photocatalyst from the polymer and monomer with tolerable metal contamination (8.41 ug/g). These isolated QDs could be recycled for four separate polymerizations without a significant decrease in efficiency. By changing the pore size of the protein concentrators, the QDs and polymer could be separated from the remaining monomer, allowing for the synthesis of block copolymers using a single batch of QDs with minimal purification steps and demonstrating the fidelity of chain ends.
36 MATERIALS SCIENCE↗
Predictive Theoretical Framework for Dynamic Control of Bioinspired Hybrid Nanoparticle Self-Assembly
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Synthesis of Butyl-Exchanged Polyoxymethylene Ethers as Renewable Diesel Blendstocks with Improved Fuel Properties
Methyl-terminated polyoxymethylene ethers (MM-POMEs), having the formula CH3O–(CH2O)n–CH3 (n = 3–5), are a high-cetane, low-sooting group of oxygenates that have recently attracted attention as potential diesel blendstocks. Despite these attractive fuel properties, MM-POMEs have shortcomings due to their low energy density and high water solubility. Guided by a computational fuel property assessment for POMEs with longer end-groups, the most promising improvements in the desired compression ignition fuel properties were observed for butyl-terminated POMEs. Here, an acid-catalyzed transacetalization reaction was developed to exchange the methyl end-groups of MM-POMEs (n = 3–6) with butyl end-groups. The reaction utilizes an ion-exchange resin as the acid catalyst at mild reaction conditions of 60 °C and atmospheric pressure. Approximately 100 mL of butyl-exchanged POMEs in the diesel boiling range were produced, enabling laboratory-scale fuel property testing. The butyl-terminated POME mixture possesses the advantaged fuel properties of the parent MM-POMEs (low-soot, high-cetane) while exhibiting improved energy density (lower heating value (LHV) of 30 MJ/kg) and substantially reduced water solubility (7.3 g/L) compared to the parent MM-POME mixture (LHV of 19 MJ/kg , water solubility of 258 g/L).
09 BIOMASS FUELS↗
Predicting Catalytic Pyrolysis Aromatic Selectivity from Pyrolysis Vapor Composition Using Mass Spectra Coupled with Statistical Analysis
The behavior of fast pyrolysis (FP) and catalytic FP (CFP) of 20 renewable feedstocks was studied in a microscale reactor with molecular beam mass spectral analysis of products generated. A partial least-squares (PLS) model was constructed based on the FP vapor spectra that predicts the aromatic selectivity when upgrading over a ZSM-5 catalyst. Additionally, principal component analysis of both FP and CFP spectra was performed for comprehensive spectral analysis. This work highlighted the value of vapor-phase mass spectral screening to predict the subsequent feedstock performance and demonstrated that the quantity of coke deposited on the catalyst is not a reliable measure of catalyst deactivation when the feedstock type is varied.
09 BIOMASS FUELS↗
Counterintuitive Compatibilization of Poly(-Valerolactone) and Poly(L-Lactic Acid) by Statistical Copolymers toward Compostable and Recyclable Packaging
Poly(δ-valerolactone) (PVL) and poly(l-lactic acid) (PLLA) are bioderivable, compostable, and chemically recyclable plastics with synergistic properties for addressing plastic waste accumulation in receiving environments. Though recyclable-by-design polymers often fall short of competing with incumbent materials, blending affords a means to leverage individual component strengths toward ideal tunable properties. Polymer blends are often immiscible, but a range of methodologies are available to promote mixing. Here, we report on the compatibilization of 9 immiscible PVL and PLLA blends with three different compatibilization agents: thermoplastic starch, synthesized PVL-co-PLLA statistical copolymers (SCPs), and synthesized PVL-b-PLLA block-type copolymers. Resulting degrees of compatibilization are observed through scanning electron microscopy, corroborated by thermal and mechanical analyses monitoring performance as a function of microdomain size. Small-angle and wide-angle X-ray scattering experiments are conducted to observe the influence of compatibilizers on individual crystalline phases to further elucidate material behavior. Molecular dynamics simulations provide key insights into the interfacial interactions between homopolymers and compatibilizers. Finally, a suite of end-of-life avenues is established by biodegradation in industrial composting conditions, chemical recycling by deconstruction to hydroxymethyl esters, and direct chemical depolymerization to lactone precursors in mixed feed. Overall, we highlight several promising blends and the counterintuitive SCP compatibilization phenomenon toward high-performance, sustainable materials.
Compatibilization, copolymer compatibilizer, bio-b↗
Advances in Multiscale Modeling of Lignocellulosic Biomass
Applications and associated processing technologies of lignocellulosic biomass are becoming more important as we endeavor to meet societal demand for fuels, chemicals, and materials from renewable resources. Meanwhile, the rapidly expanding availability and capabilities of high-performance computing present an unprecedented opportunity to accelerate development of technologies surrounding lignocellulose utilization. In order to realize this potential, suitable modeling frameworks must be constructed that effectively capture the multiscale complexity and tremendous variety exhibited by lignocellulosic materials. In our assessment of previous endeavors towards this goal, several important shortcomings have been identified: (1) the lack of multiscale integration strategies that capture emergent properties and behaviors spanning different length scales, and (2) the inability of many modeling approaches to effectively capture the variability and diversity of lignocellulose that arise from both natural and process-induced sources. In this perspective, we survey previous modeling approaches for lignocellulose and simulations processes involving its chemical and mechanical transformation, and suggest opportunities for future development to enhance the utility of computational tools to address barriers to widespread adoption of a renewable bioeconomy.
09 BIOMASS FUELS↗
A Telomerase-Activated Magnetic Resonance Imaging Probe for Consecutively Monitoring Tumor Growth Kinetics and In Situ Screening Inhibitors
Telomerase has long been considered as a biomarker for cancer diagnosis and a therapeutic target for drug discovery. Detecting telomerase activity in vivo could provide more direct information of tumor progression and response to drug treatment, which, however, is hampered by the lack of an effective probe that can generate an output signal without a tissue penetration depth limit. Here in this study, using the principle of distance-dependent magnetic resonance tuning, we constructed a telomerase-activated magnetic resonance imaging probe (TAMP) by connecting superparamagnetic ferroferric oxide nanoparticles (SPFONs) and paramagnetic Gd-DOTA (Gd(III) 1,4,7,10- tetraazacyclododecane-1,4,7,10-tetraazacyclododecane-1,4,7,10-tet-raacetic acid) complexes via telomerase-responsive DNA motifs. Upon telomerase-catalyzed extension of the primer in TAMP, Gd-DOTA-conjugated oligonucleotides can be liberated from the surface of SPFONs through a DNA strand displacement reaction, restoring the T 1 signal of the Gd-DOTA for a direct readout of the telomerase activity. Here we show that, by tracking telomerase activity, this probe provides consistent monitoring of tumor growth kinetics during progression and in response to drug treatment and enables in situ screening of telomerase inhibitors in whole-animal models. This study provides an alternative toolkit for cancer diagnosis, treatment response assessment, and anticancer drug screening.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Multivalent Cation-Induced Actuation of DNA-Mediated Colloidal Superlattices
Nanoparticles functionalized with DNA can assemble into ordered superlattices with defined crystal habits through programmable DNA “bonds”. Here, we examine the interactions of multivalent cations with these DNA bonds as a chemical approach for actuating colloidal superlattices. Multivalent cations alter DNA structure on the molecular scale, enabling the DNA “bond length” to be reversibly altered between 17 and 3 nm, ultimately leading to changes in the overall dimensions of the micrometer-sized superlattice. The identity, charge, and concentration of the cations each control the extent of actuation, with Ni2+ capable of inducing a remarkable >65% reversible change in crystal volume. In addition, these cations can increase “bond strength”, as evidenced by superlattice thermal stability enhancements of >60 °C relative to systems without multivalent cations. Molecular dynamics simulations provide insight into the conformational changes in DNA structure as the bond length approaches 3 nm and show that cations that screen the negative charge on the DNA backbone more effectively cause greater crystal contraction. Finally, taken together, the use of multivalent cations represents a powerful strategy to alter superlattice structure and stability, which can impact diverse applications through dynamic control of material properties, including the optical, magnetic, and mechanical properties.
59 BASIC BIOLOGICAL SCIENCES↗
JAX-CanVeg: A Differentiable Land Surface Model
Land surface models consider the exchange of water, energy, and carbon along the soil-canopy-atmosphere continuum, which is challenging to model due to their complex interdependency and associated challenges in representing and parameterizing them. Differentiable modeling provides a new opportunity to capture these complex interactions by seamlessly hybridizing process-based models with deep neural networks (DNNs), benefiting both worlds, that is, the physical interpretation of process-based models and the learning power of DNNs. Here, we developed a differentiable land model, JAX-CanVeg. The new model builds on the legacy CanVeg by incorporating advanced functionalities through JAX in the graphic processing unit support, automatic differentiation, and integration with DNNs. We demonstrated JAX-CanVeg's hybrid modeling capability by applying the model at four flux tower sites with varying aridity. To this end, we developed a hybrid version of the Ball-Berry equation that emulates the water stress impact on stomatal closure to explore the capability of the hybrid model in (a) improving the simulations of latent heat fluxes (LE) and net ecosystem exchange (NEE), (b) improving the optimization trade-off when learning observations of both LE and NEE, and (c) benefiting a multi-layer canopy model setup. Our results show that the proposed hybrid model improved the simulations of LE and NEE at all sites, with an improved optimization trade-off over the process-based model. Additionally, the multi-layer canopy set benefited hybrid modeling at some sites. Anchored in differentiable modeling, our study provides a new avenue for modeling land-atmosphere interactions by leveraging the benefits of both data-driven learning and process-based modeling.
54 ENVIRONMENTAL SCIENCES↗
Engineering microbial consortia for mixed plastic upcycling
Recent studies in developing processes using ‘single’ plastic waste for microbial conversion have demonstrated great promise in advancing a circular economy. However, chemical complexity and compositional variability of post-consumer ‘mixed’ plastic waste pose huge challenges to using it as a feedstock for biomanufacturing. Here, we present a process leveraging a synthetic microbial consortium, comprising Rhodococcus jostii strain PET and Acinetobacter baylyi ADP1, enabled by engineering the division of labor. The robust consortium synergistically and stably consumes diverse mixtures of oxygenated compounds, derived from the depolymerization of post-consumer, mixed plastic waste, regardless of the fluctuating plastic waste compositions. We evaluate the upcycling potential of the stable consortium by applying rational metabolic engineering to both specialists, enabling the funneling of these oxygenates into lycopene and lipids. This work highlights the potential of stable microbial consortia to valorize untapped, mixed plastic waste for sustainable biomanufacturing, offering a promising solution to global plastic pollution.
60 APPLIED LIFE SCIENCES↗
Biologically-informed excitatory and inhibitory ratio for robust spiking neural network training
Spiking neural networks drawing inspiration from biological constraints of the brain promise an energy-efficient paradigm for artificial intelligence. However, challenges exist in identifying guiding principles to train these networks in a robust fashion. In addition, training becomes an even more difficult problem when incorporating biological constraints of excitatory and inhibitory connections. In this work, we identify several key factors, such as low initial firing rates and diverse inhibitory spiking patterns, that determine the overall ability to train in the context of spiking networks with various ratios of excitatory to inhibitory neurons. The results indicate networks with biologically-realistic excitatory:inhibitory ratios can reliably train at low activity levels and in noisy environments. Additionally, the Van Rossum distance, a measure of spike train synchrony, provides insight into the importance of inhibitory neurons to increase network robustness to noise. This work supports further biologically-informed large-scale networks and energy efficient hardware implementations.
bio-inspired computing↗
Neuromorphic spintronics
Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial neurons and synapses are, however, currently limited by the energy and area requirements of these components. Spintronic nanodevices, which exploit both the magnetic and electrical properties of electrons, can increase the energy efficiency and decrease the area of these circuits, and magnetic tunnel junctions are of particular interest as neuromorphic computing elements because they are compatible with standard integrated circuits and can support multiple functionalities. Here, we review the development of spintronic devices for neuromorphic computing. We examine how magnetic tunnel junctions can serve as synapses and neurons, and how magnetic textures, such as domain walls and skyrmions, can function as neurons. We also explore spintronics-based implementations of neuromorphic computing tasks, such as pattern recognition in an associative memory, and discuss the challenges that exist in scaling up these systems.
42 ENGINEERING↗
Carbon conversion on biophotonic leaf
A photodiode can trigger bias-free redox reactions but is often hindered by thermodynamic barriers. Now, a bacteria-conjugated silicon biophotochemical diode allows simultaneous conversion of various carbon molecules with high efficacy.
60 APPLIED LIFE SCIENCES↗