Investigation of Room Temperature Formation of the Ultra-Hard Nanocarbons Diamond and Lonsdaleite
Abstract not provided
McCulloch, Dougal G.↗
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Toward Standardized Microscale Tensile Testing for Two‐Photon Polymerization‐Fabricated Materials in Liquid
Two-photon polymerization (TPP) enables the fabrication of intricate 3D microstructures with submicron precision, offering significant potential in biomedical applications like tissue engineering. In such applications, to print materials and structures with defined mechanics, it is crucial to understand how TPP printing parameters impact the material properties in a physiologically relevant liquid environment. Herein, an experimental approach utilizing microscale tensile testing (μTT) for the systematic measurement of TPP-fabricated microfibers submerged in liquid as a function of printing parameters is introduced. Using a diurethane dimethacrylate-based resin, the influence of printing parameters on microfiber geometry is first explored, demonstrating cross-sectional areas ranging from 1 to 36 μm 2 . Tensile testing reveals Young's moduli between 0.5 and 1.5 GPa and yield strengths from 10 to 60 MPa. The experimental data show an excellent fit with the Ogden hyperelastic polymer model, which enables a detailed analysis of how variations in writing speed, laser power, and printing path influence the mechanical properties of TPP microfibers. The μTT method is also showcased for evaluating multiple commercial resins and for performing cyclic loading experiments. Collectively, this study builds a foundation toward a standardized microscale tensile testing framework to characterize the mechanical properties of TPP printed structures.
mechanical characterization↗
Risk Assessment of Industrial Microbes Using a Terrestrial Mesocosm Platform
Abstract Industrial microbes and bio-derived products have emerged as an integral component of the bioeconomy, with an array of agricultural, bioenergy, and biomedical applications. However, the rapid development of microbial biotechnology raises concerns related to environmental escape of laboratory microbes, detection and tracking thereof, and resultant impact upon native ecosystems. Indeed, though wild-type and genetically modified microbes are actively deployed in industrial bioprocesses, an understanding of microbial interactivity and impact upon the environment is severely lacking. In particular, the persistence and sustained ecosystem impact of industrial microbes following laboratory release or unintentional laboratory escape remains largely unexplored. Herein, we investigate the applicability of soil-sorghum mesocosms for the ecological risk assessment of the industrial microbe, Saccharomyces cerevisiae . We developed and applied a suite of diagnostic and bioinformatic analyses, including digital droplet PCR, microscopy, and phylogenomic analyses to assess the impacts of a terrestrial ecosystem perturbation event over a 30-day time course. The platform enables reproducible, high-sensitivity tracking of S. cerevisiae in a complex soil microbiome and analysis of the impact upon abiotic soil characteristics and soil microbiome population dynamics and diversity. The resultant data indicate that even though S. cerevisiae is relatively short-lived in the soil, a single perturbation event can have sustained impact upon mesocosm soil composition and underlying microbial populations in our system, underscoring the necessity for more comprehensive risk assessment and development of mitigation and biocontainment strategies in industrial bioprocesses.
09 BIOMASS FUELS↗
Analysis of the Ion Conversion Mechanisms in the Effluent of Atmospheric Pressure Plasma Jets in Ar with Admixtures of O 2 , H 2 O and Air
Ionic species in atmospheric pressure plasma jets (APPJs) play an important role in plasmasurface and plasma-liquid interactions, nonetheless, they have not received the same attention as their neutral reactive species counterparts. In this work, a molecular beam mass spectrometer (MBMS) was used to characterize the ion compositions in the effluent of an APPJ operating in ambient air for different feed gases including Ar + O 2 , Ar + air and Ar + H 2 O mixtures inspired by gas compositions used for biomedical applications. Changes in compositions of positive and negative ions as a function of nozzle-to-substrate distance along the plasma plume were analyzed and compared with a pseudo-1D plug flow model. Positive and negative ions were detected up to distances of 12 mm from the visible plasma plume tip. The measurements enable to follow the ion conversion pathways in the effluent of the APPJs as a function of distance from the nozzle. The trends in ion yield obtained from a pseudo-1D plug flow model showed generally a good agreement with the experimentally observed trends after addition of ionic reactions to the previously reported reaction set but also some distinctive differences were observed. The dominant positive ions in the far effluent are water ion clusters, the most stable ion for all gas mixtures investigated, while a large variety of negative ions was found for different gas mixtures.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Thermochemistry of sodium rare earth ternary fluorides, NaREF 4
Sodium rare earth fluorides, NaREF 4 (RE = rare earth), are used as luminescent materials for light emission and biomedical applications and are important compositions for extracting and separating RE elements. Solution calorimetric measurements of a series of β-structured NaREF 4 (Na 1.5 RE 1.5 F 6 ) phases with various RE elements determined their heats of formation. Though the lattice contracts from light to heavy RE elements, NaREF 4 compounds show more exothermic enthalpies of formation from binary components with the decrease of RE 3+ radii, contrary to behavior seen in most RE oxide ternary compounds. Furthermore, by constructing Born–Haber cycles, the different slopes of lines relating lattice energies to lattice parameters in binary and ternary fluorides appear to be the reason for this reverse trend, which can be associated with changes in the coordination number of RE cations. These trends and the metastability of sodium light RE fluorides not only reveal the key role of ionic radius in RE compound stability, but also are significant for the design and synthesis of new materials and motivate the more effective utilization of RE.
36 MATERIALS SCIENCE↗
Understanding interactions between biomolecules and two-dimensional nanomaterials using in silico microscopes
We report two-dimensional (2D) nanomaterials such as graphene are increasingly used in research and industry for various biomedical applications. Extensive experimental and theoretical studies have revealed that 2D nanomaterials are promising drug delivery vehicles, yet certain materials exhibit toxicity under biological conditions. So far, it is known that 2D nanomaterials possess strong adsorption propensities for biomolecules. To mitigate potential toxicity and retain favorable physical and chemical properties of 2D nanomaterials, it is necessary to explore the underlying mechanisms of interactions between biomolecules and nanomaterials for the subsequent design of biocompatible 2D nanomaterials for nanomedicine. The purpose of this review is to integrate experimental findings with theoretical observations and facilitate the study of 2D nanomaterial interaction with biomolecules at the molecular level. We discuss the current understanding and progress of 2D nanomaterial interaction with proteins, lipid membranes, and DNA based on molecular dynamics (MD) simulation. In this review, we focus on the 2D graphene nanosheet and briefly discuss other 2D nanomaterials. With the ever-growing computing power, we can image nanoscale processes using MD simulation that are otherwise not observable in experiment. We expect that molecular characterization of the complex behavior between 2D nanomaterials and biomolecules will help fulfill the goal of designing effective 2D nanomaterials as drug delivery platforms.
2D nanomaterials↗
Fe-carbide/Fe-oxide-based nanocomposites synthesized as magnetic nanomaterials via laser ablation synthesis in solution (LASiS)
Magnetic nanostructured materials (MNMs) have gained prominence in materials technology developments owing to their potential biomedical applications for hyperthermia cancer treatment, and transplant organ cryopreservation. Herein, we report the facile and cost-effective synthesis of Fe-based composite MNMs, comprising both Fe@Fe 2 O 3 and Fe 3 C@C core-shell nanoparticles (NPs), via Laser Ablation Synthesis in Solution (LASiS) using Fe targets ablated under acetone and toluene. Detailed materials characterizations using electron microscopy-based imaging, diffraction studies, and spectroscopic analyses - including Raman and Mössbauer spectroscopy - relate the structure-composition properties for different Fe-oxide/carbide phases in the aforesaid MNMs to their respective magnetic responses. Specifically, we confirm the presence of ultra-small (2–10 nm) amorphous Fe-oxide NPs, as well as Fe@Fe 2 O 3 core-shell NPs (20–40 nm) in the samples synthesized by ablating Fe under acetone. In contrast, samples synthesized under toluene indicate a higher concentration of Fe 3 C@C core-shell NPs (20–40 nm) with a relatively low concentration of Fe 2 O 3 NPs (2–10 nm). Furthermore, the crystallinity of the metallic phases and carbonaceous shell coatings are systematically increased by carrying out LASiS under heated toluene (up to ~95 °C). Importantly, mössbauer spectroscopy results indicate that the elevation in toluene temperature leads to an increase in the concentrations of Fe 3 C@C NPs from ~40 % to ~53 % (at.).
36 MATERIALS SCIENCE↗
Structural properties of optically clear bacterial cellulose produced by Komagataeibacter hansenii using arabitol
Here, bacterial cellulose (BC) exhibits beneficial properties for use in biomedical applications but is limited by its lack of tunable transparency capabilities. To overcome this deficiency, a novel method to synthesize transparent BC materials using an alternative carbon source, namely arabitol, was developed. Characterization of the BC pellicles was performed for yield, transparency, surface morphology, and molecular assembly. Transparent BC was produced using mixtures of glucose and arabitol. Zero percent arabitol pellicles exhibited 25% light transmittance, which increased with increasing arabitol concentration through to 75% light transmittance. While transparency increased, overall BC yield was maintained indicating that the altered transparency may be induced on a micro-scale rather than a macro-scale. Significant differences in fiber diameter and the presence of aromatic signatures were observed. Overall, this research outlines methods for producing BC with tunable optical transparency, while also bringing new insight to insoluble components of exopolymers produced by Komagataeibacter hansenii.
59 BASIC BIOLOGICAL SCIENCES↗
Statistical 3D morphology characterization of vaterite microspheres produced by engineered Escherichia coli
Hollow vaterite microspheres are important materials for biomedical applications such as drug delivery and regenerative medicine owing to their biocompatibility, high specific surface area, and ability to encapsulate a large number of bioactive molecules and compounds. We demonstrated that hollow vaterite microspheres are produced by an Escherichia coli strain engineered with a urease gene cluster from the ureolytic bacteria Sporosarcina pasteurii in the presence of bovine serum albumin. We characterized the 3D nanoscale morphology of five biogenic hollow vaterite microspheres using 3D high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) tomography. Using automated high-throughput HAADF-STEM imaging across several sample tilt orientations, we show that the microspheres evolved from a smaller more ellipsoidal shape to a larger more spherical shape while the internal hollow core increased in size and remained relatively spherical, indicating that the microspheres produced by this engineered strain likely do not contain the bacteria. The statistical 3D morphology information demonstrates the potential for using biogenic calcium carbonate mineralization to produce hollow vaterite microspheres with controlled morphologies.
3D morphology↗
Machine learning assisted phase and size-controlled synthesis of iron oxide particles
Synthesis of iron oxides with specific phases and particle sizes is a crucial challenge in various fields, including materials science, energy storage, biomedical applications, environmental science, and earth science. However, despite significant advances in this area, much of the current palette of particle outcomes has been based on time-consuming trial-and-error exploration of synthesis conditions. The present study was designed to explore a very different approach to 1) predict the outcome of synthesis from specified reaction parameters based on using machine learning (ML) techniques, and 2) correlate sets of parameters to obtain products with desired outcomes by a newly designed recommendation algorithm. To achieve this, four ML algorithms were tested, namely random forest, logistic regression, support vector machine, and k-nearest neighbor. Among the models, random forest outperformed the others, attaining 96% and 81% accuracy when predicting the phase and size of iron oxide particles in the test dataset. Surprisingly, the permutation feature importance analysis revealed that volume, which may strongly relate to pressure, was one of the important features, along with precursor concentration, pH, temperature, and time, influencing the phase and size of iron oxide particles during synthesis. To verify the robustness of the random forest models, prediction and experimental results were compared based on 24 randomly generated methods in additive and non-additive systems not included in the datasets. The predictions of product phase and particle size from the models agreed well with the experimental results. Furthermore, a searching and ranking algorithm was developed to recommend potential synthesis parameters for obtaining iron oxide products with the desired phase and particle size from previous studies in the dataset. Furthermore, this study lays the foundation for a closed-loop approach in materials synthesis and preparation, beginning with suggesting potential reaction parameters from the dataset and predicting potential outcomes, followed by conducting experiments and analyses, and ultimately enriching the dataset.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A combined machine learning and density functional theory study of binary Ti-Nb and Ti-Zr alloys: Stability and Young’s modulus
The multicomponent Ti alloys, specifically the -phase, have experienced a strong growth over the last decades, due to their outstanding properties of ultra-high strength and low Young’s modulus. These properties play a significant role in many aerospace and biomedical applications. Selection and optimization of multicomponent alloys is challenging due to the vast chemical and compositional space. Here we investigate the use of machine learning techniques informed by density functional calculations to guide the selection of Nb- and Zr-based Ti binary alloys. From the cubic structures obtained from high throughput calculations and literature, we identify several structures with Young’s moduli below 40 GPa. The multivariant decision tree methods provide efficient surrogate models to identify structure variables have high influences on the energetic stability and Young’s modulus. Furthermore, we implement a workflow of incorporating DFT provided results and machine learning method to explore the chemical and composition space of other binary and multicomponent alloys, to eventually accelerate the material design via taking advantages of identified key variables.
36 MATERIALS SCIENCE↗
Medium controlled aggregative growth as a key step in mesoporous silica nanoparticle formation
Near monodisperse mesoporous silica nanoparticles (MSN) represent a promising and rapidly developing type of mesoporous silica materials; however, the vast data on their synthesis remains unorganized and ill-understood. We systematically studied the formation of MSN under basic and neutral conditions using various temperatures, CTAB concentrations, hydrolyzing agents (triethanolamine, ammonia, phosphate buffers), and media with different colloidal stabilization properties (with ethanol as a cosolvent and monovalent salts). In the typical conditions for the preparation of stable MSN colloids, the particle size was controlled by colloidal stabilization by the medium (solvent type, ionic strength, and surfactant concentration) in agreement with the “aggregative growth” mechanism, rather than by solely the hydrolysis and condensation rates conventionally used for data interpretation in the classical nucleation theory. Medium properties (pH, ion types and concentration, polarity) also defined the efficiency of silica-surfactant cooperative self-assembly, which directly affected the porosity, mesopore size and pore wall thickness. Interestingly, this traditional silica-surfactant route showed a limited effect on the particle size, emphasizing the dominating role of colloidal stabilization in the studied reaction conditions. In situ pH measurements showed that every reaction medium has unique pH evolution profiles depending on the buffer capacity, hydrolysis and condensation rates. Reaction systems that fail to maintain the working pH can lead to non-porous products or undesired particle morphology and size distribution. The established particle formation mechanism allowed us to formulate comprehensive guidelines for preparing relatively concentrated colloids of near monodisperse (PDI 5–15%) mesoporous 30–700 nm silica spheres with variable porosity and mesopore size. Here, these findings will be particularly useful in designing new mesoporous silica-containing materials for biomedical applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The influence of hydrothermal synthesis temperature on the electronic structure and luminescence property of Cr-doped ZnGa 2 O 4 nanoparticles
Cr-doped ZnGa 2 O 4 (CZGO) is a near-infrared-emitting material with long-lasting persistent luminescence. This unique property makes it a great candidate in optical imaging and sensing for various biomedical applications. Nanosized CZGO can be synthesized via a hydrothermal approach, but the reaction temperatures reported in existing literature vary from 120°C to 220°C, approaching the highest temperature allowed for a standard autoclave vessel. The reason for choosing a particular hydrothermal synthesis temperature has rarely been discussed, and it is unclear whether the resulting CZGO possess the same optical properties. This work compares CZGO nanoparticles synthesized at temperatures from the lowest reported 120°C and to as high as 220°C. We find that although all the synthesized CZGO are light emitting, they exhibit different luminescence intensities and respond differently to the change of excitation energy. X-ray absorption fine structure (XAFS) analysis is employed to investigate the local chemical environment around Zn, Ga and Cr, respectively. We found synthesis temperature strongly influences the Ga species formed in these particles. The energy transfer mechanism is further elucidated using X-ray excited optical luminescence (XEOL) in combination with element-specific XAFS. Two energy transfer paths are identified, which explains the different excitation energy dependencies of the observed photoluminescence.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Advanced magnetic X-ray spectro-microscopies to characterize mesoscopic magnetic materials
Here, this article provides a brief overview of advanced magnetic X-ray spectro-microscopies that are widely used in characterizing mesoscopic magnetic materials. Common to those techniques are various X-ray magnetic dichroism effects that are used as magnetic contrast mechanism. A particular interest is to use those techniques to image the underlying microscopic spin structures in magnetic materials with high spatial resolution and to ultimately resolve their full 3D mesoscale characteristics with elemental sensitivity, as well as their ultrafast dynamics upon excitations with field and current pulses. Recent research examples using various magnetic X-ray spectro-microscopies are presented to showcase their specific features with a focus on imaging novel topological spin textures, such as vortices, skyrmions and Hopfions, which are considered as potential building blocks towards low power, high-speed and high-density magnetic devices that could transform information technologies and potentially be used in biomedical applications. Future developments with magnetic X-ray spectro-microscopies harness the full coherence of next generation X-ray sources and could open the path towards single shot imaging with spatial and temporal resolutions down to fundamental magnetic length and time scales.
36 MATERIALS SCIENCE↗
Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale
The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.
36 MATERIALS SCIENCE↗
Buffer concentration dramatically affects the stability of S-nitrosothiols in aqueous solutions
S-nitrosothiols (RSNOs) are an important group of nitric oxide (NO)-donating compounds with low toxicity and wide biomedical applications. In this paper, we, for the first time, demonstrate that the concentration of buffer remarkably affects the stability of RSNOs including naturally occurring S-nitrosoglutathione (GSNO) and synthetic S-nitroso-N-acetylpenicillamine (SNAP). For a solution with a high concentration of GSNO (e.g., 50 mM) and an initial near-neutral pH, the optimal buffer concentration is close to the GSNO concentration under our experimental conditions. A lower buffer concentration does not have adequate buffer capacity to resist the pH drop caused by GSNO decomposition. The decreased solution pH further accelerates GSNO decomposition because GSNO is most stable at near-neutral pH according to our density functional theory (DFT) calculations. A higher-than-optimal buffer concentration also reduces the GSNO stability because buffer ingredients including phosphate, Tris base, and HEPES consume NO/N 2 O 3 . In contrast to GSNO, the highest SNAP stability is obtained when the starting solution at a neutral pH does not contain buffer species, and the stability decreases as the buffer concentration increases. Furthermore, this is because SNAP is more stable at mildly acidic pH and the SNAP decomposition-induced pH drop stabilizes the donor. When the RSNO concentration is low (e.g., 1 mM), the buffer concentration also matters because any excess buffer accelerates the donor decomposition. Since the effect of buffer concentration was previously overlooked and suboptimal buffer concentrations were often used, this paper will aid in the formulation of RSNO solutions to obtain the maximum stability for prolonged storage and sustained NO release.
59 BASIC BIOLOGICAL SCIENCES↗
Influence of calcium nitrate timing on the structural and textural characteristics of mesoporous SiO 2 -CaO nanoparticles
Mesoporous bioactive glass nanoparticles (MBGNPs) are promising materials for drug delivery due to their high pore volume and specific surface area. This study investigates how the timing of calcium nitrate addition affects the structural and textural characteristics of MBGNPs synthesized via a microemulsion-assisted sol-gel method. Delayed calcium nitrate addition reduced calcium incorporation from 14.2 to 9.5 mol% and increased particle size from 178 ± 51 nm to 256 ± 30 nm. The specific surface area values increased with the delayed addition of calcium nitrate, as observed through BET and USAXS/SAXS measurements. The proportion of Q Si n units slightly changed, but no cytotoxicity was observed in osteoblast-like cells. These findings provide valuable insights into optimizing MBGNP synthesis for biomedical applications.
Calcium nitrate tetrahydrate↗
Drug discovery efforts at George Mason University
With over 39,000 students, and research expenditures in excess of $200 million, George Mason University (GMU) is the largest R1 (Carnegie Classification of very high research activity) university in Virginia. Mason scientists have been involved in the discovery and development of novel diagnostics and therapeutics in areas as diverse as infectious diseases and cancer. Below are highlights of the efforts being led by Mason researchers in the drug discovery arena. To enable targeted cellular delivery, and non-biomedical applications, Veneziano and colleagues have developed a synthesis strategy that enables the design of self-assembling DNA nanoparticles (DNA origami) with prescribed shape and size in the 10 to 100 nm range. The nanoparticles can be loaded with molecules of interest such as drugs, proteins and peptides, and are a promising new addition to the drug delivery platforms currently in use. The investigators also recently used the DNA origami nanoparticles to fine tune the spatial presentation of immunogens to study the impact on B cell activation. These studies are an important step towards the rational design of vaccines for a variety of infectious agents. To elucidate the parameters for optimizing the delivery efficiency of lipid nanoparticles (LNPs), Buschmann, Paige and colleagues have devised methods for predicting and experimentally validating the pKa of LNPs based on the structure of the ionizable lipids used to formulate the LNPs. These studies may pave the way for the development of new LNP delivery vehicles that have reduced systemic distribution and improved endosomal release of their cargo post administration. To better understand protein-protein interactions and identify potential drug targets that disrupt such interactions, Luchini and colleagues have developed a methodology that identifies contact points between proteins using small molecule dyes. The dye molecules noncovalently bind to the accessible surfaces of a protein complex with very high affinity, but are excluded from contact regions. When the complex is denatured and digested with trypsin, the exposed regions covered by the dye do not get cleaved by the enzyme, whereas the contact points are digested. The resulting fragments can then be identified using mass spectrometry. The data generated can serve as the basis for designing small molecules and peptides that can disrupt the formation of protein complexes involved in disease processes. For example, using peptides based on the interleukin 1 receptor accessory protein (IL-1RAcP), Luchini, Liotta, Paige and colleagues disrupted the formation of IL-1/IL-R/IL-1RAcP complex and demonstrated that the inhibition of complex formation reduced the inflammatory response to IL-1B. Working on the discovery of novel antimicrobial agents, Bishop, van Hoek and colleagues have discovered a number of antimicrobial peptides from reptiles and other species. DRGN-1, is a synthetic peptide based on a histone H1-derived peptide that they had identified from Komodo Dragon plasma. DRGN-1 was shown to disrupt bacterial biofilms and promote wound healing in an animal model. The peptide, along with others, is being developed and tested in preclinical studies. Other research by van Hoek and colleagues focuses on in silico antimicrobial peptide discovery, screening of small molecules for antibacterial properties, as well as assessment of diffusible signal factors (DFS) as future therapeutics. The above examples provide insight into the cutting-edge studies undertaken by GMU scientists to develop novel methodologies and platform technologies important to drug discovery.
59 BASIC BIOLOGICAL SCIENCES↗