Adrenocortical control of epinephrine synthesis
Adrenal medulla biochemistry and morphology, discussing epinephrine synthesis control by glucocorticoid hormones
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Adrenal medulla biochemistry and morphology, discussing epinephrine synthesis control by glucocorticoid hormones
Industrial separations require enormous amounts of energy, accounting for approximately half the industrial energy use and 10–15% of the total energy consumption. Distillation alone accounts for about half the energy demand for industrial separations. If these processes could be replaced by an energy-efficient membrane separation process, this energy demand could be reduced by 90%. However, although some membrane processes have made inroads into thermal distillation, for membrane-based separations to replace the distillation process to a far more significant and practical level, new membranes with higher robustness, selectivity, and flux still need be developed. In this membrane development program, we leveraged Temple University’s prior work in spiroligomers to develop robust membrane structures. These structures can be formed into atomically precise pores by controlling the chemical synthesis and the oligomer building blocks to first build precisely controlled macrocycles and then subsequently crosslinking these macrocycles to produce a membrane. Furthermore, through the highly controllable chemistry of our molecular building blocks, not only can we integrate pores with highly controllable and reproducible size and morphology, but we can also target internal functionalization. By using a range of scalable membrane synthesis approaches, combined with control of each and every pores internal chemistry and molecular conformation we can achieve membrane structures that can display the ultimate in high selectivity and permeance. The Mainstream-Temple University membranes can be designed to achieve ultra-selective separations based on the key factors of molecular size, shape, and functionality. In our approach to fabricate scalable atomically precise membranes, we used our molecular Lego nanostructures. We demonstrated an approach to create atomically precise pores within the membrane with pores that are the dimensions of the molecule we are trying to separate. Moreover, in addition to controlling the morphology of the membrane structure by controlling the size of every pore, we can also decorate every pore with precisely targeted and placed functional groups. These accurately placed functional groups can provide selective binding to molecules and provide enhanced selectivity via a facilitated transport mechanism. In Phase II, the Mainstream-Temple University team demonstrated the scalable synthesis of oligomers and the ability to control the pore internal and external functionality, or chemistry, to allow the fabrication of a thin-film membrane. The initial steps of the spiroligomer synthesis to produce the two key bis-amino enantiomer building blocks were scaled from the gram scale to the kilogram scale, obtaining 25 kg of the materials by transferring the procedure to a toll manufacturer. Finally, we successfully optimized the fabrication of these macrocycles into robust membranes. We successfully transitioned from a laboratory based, hard-to-scale Langmuir trough synthesis to a highly scalable, roll-to-roll applicable, interfacial polymerization process. During this Phase II program, we established a platform of atomically precise membranes where our highly controllable, atomically precise macrocycles served as a scaffold with precisely and uniformly controlled pores. Furthermore, this layer can be tailored to accommodate a diverse range of functional groups, which both further controlled the pore size to enhance the sieving effect as well as imparting precisely controlled targeted selectivity through biomimetic molecular interactions. In this Phase II, we established and scaled up a platform approach to both tune the pore size and chemistry as well as scale it to produce membranes that can be applied to a wide range of industries. In future development, the project team expects to scale up both the macrocycle building block production and interfacial polymerization process to produce the atomically precise membrane with targeted pore sizes and pore chemistries.
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Polymerization-induced phase separation enables fine control over thermoset network morphologies, yielding heterogeneous structures with domain sizes tunable over 1-100 nm. However, the controlled chain-growth polymerization techniques exclusively employed to regulate morphology at these length scales are unsuitable for most thermoset materials typically formed through step-growth mechanisms. By employing binary mixtures in place of the classic constituents of phase-separating thermosets—resin, curing agent, and secondary polymer—facile tunability over morphology can be achieved through a single compositional parameter. Indeed, this method yields morphologies spanning nano-scale to macro-scale, controlled by the relative reactivities and thermodynamic compatibility of the network components. Due to the connection between chain dynamics and microstructure in these materials, the tunable morphology enables exquisite control over glass transition and other physical and mechanical properties.
Lithium (Li)-morphology and solid electrolyte interphase (SEI) are among the most significant performance regulators in Li-metal batteries (LMBs). While both Li-morphology and SEI composition play key roles in the cyclability of LMBs, less is understood about the individual contributions of each factor to overall Li reversibility, particularly at a practical current density (1 mA cm −2 ) at which the kinetics of both factors are not naturally separated. Herein, an interface engineering approach is introduced to deconvolute the impacts of Li-morphology and SEI composition on battery performance. By using interfacial nanofilms with differing resistivity (resistive HfO 2 versus conductive ZnO), the morphology of Li is varied, and by virtue of similar acidic character of the nanofilms, the formation of anion-rich SEIs is maintained. It is established that although the surface acidity of the thin films enables preformation of a more anion-rich SEI, it is not preserved after Li plating. It is further shown that resistance-controlled, low-surface-area Li-morphology exhibits up to threefold increase in stable cycle life when tested in multiple electrolytes. Overall, these findings explain why Li-morphological control is more advantageous for performance improvement than preformed SEI modulation due to the inherent challenges in SEI preservation.
Nature-inspired synthetic dissipative self-assemblies have attracted much attention recently. However, it remains a major challenge to achieve precise control over dissipative supramolecular assembly structures and functions of self-contained systems. Here we combine light and electricity as two clean, and spatiotemporally addressable fuels to provide precise control over the morphology for dissipative self-assembly of a perylene bisimide glycine (PBIg) building block in a self-contained solution. In this design, electrochemical oxidation provides the positive fuel to activate PBIg self-assembly while photoreduction supplies the negative fuel to deactivate the system for disassembly. Further, through programming the two counteracting fuels, we demonstrated the control of PBIg self-assembly into a variety of assembly morphologies in a self-contained system. In addition, by exerting light and electrical dual fuels simultaneously, we could create an active homeostasis exhibiting dynamic instability, leading to morphological change to asymmetric assemblies with curvatures. Such precise control over self-assembly of self-contained systems may find future applications in programming complex active materials as well as formulating pharmaceutical reagents with desired morphologies.
A new, rapid and inexpensive synthesis method for monodispersed triaminotrinitrobenzene (TATB) microparticles based on micelle-confined precipitation that enables control of microscopic morphology. The morphology of the TATB microparticles can be tuned between quasi-spherical and faceted by controlling the speed of recrystallization. The method enables improved performance and production consistency of TATB explosives for military grade explosives and propellants
The major purpose of this spaceflight project was to investigate the starch-statolith hypothesis for gravity perception, and a secondary goal was to study plant growth and development under spaceflight conditions. This research was based on our ground studies of gravity perception in the wild type and three starch-deficient (one starchless and two reduced starch) mutants of Arabidopsis thaliana (L.) Heynh. Dark-grown seedlings that developed in microgravity were given one of several (30 min, 60 min, or 90 min) 1-g stimuli by an on-board centrifuge, and additional controls for seedling development also were performed. These latter control experiments included a morphological study of plants that developed in space in microgravity (F microg), in space on a centrifuge (F 1g), on the ground (G 1g), and on a rotating clinostat on the ground. Since elevated levels of ethylene were reported in the spacecraft atmosphere, additional controls for morphology and gravitropism with added ethylene also were performed. While exogenous ethylene reduced the absolute magnitude of the response in all four strains of Arabidopsis, this gas did not appear to change the relative graviresponsiveness among the strains. The relative response of hypocotyls of microgravity-grown seedlings to the stimuli provided by the in-flight centrifuge was: wild type > starch-deficient mutants. Although the protoplast pressure model for gravity perception cannot be excluded, these results are consistent with a statolith-based model for perception in plants.
In order to build massive multi-agent systems, considered as complex and dynamic systems, one needs a method to analyze and control the system. We suggest an approach using morphology to represent and control the state of large organizations composed of a great number of light software agents. Morphology is understood as representing the state of the multi-agent system as shapes in an abstract geometrical space, this notion is close to the notion of phase space in physics.
High-entropy alloys (HEAs) provide uniquely tunable structural and electronic properties that enable robust electrocatalysis. While compositional manipulation of HEAs is well-known, systematically controlling the crystalline phase and morphology remains a challenge that could provide new avenues for controlling reactive sites and physical properties. Here, we show the preferential stabilization of mixed fcc/bcc to fcc phases by controlling the Au content in quinary AuPdFeCoNi HEA nanoparticles. This systematic structural and compositional control, when investigated with an ensemble of electronic, X-ray synchrotron, and surface techniques, allows us to identify the critical short- (few-Å) and medium- (6–10 Å) range structural motifs that deliver exceptional hydrogen evolution reaction (HER) catalysis. Specifically, these HEAs exhibit both outstanding durability (240 h) and high mass activity (50 A/mg PGM ) normalized to noble metal content, outperforming commercial Pt/C (3.18 A/mg PGM ). This structural control over HEA morphology, and its direct association with changes in specific metallic oxidation states and pair–pair atomic structural features, provides new means and strategies for finely designing robust and sustainable electrocatalysts with a majority nonprecious metal composition.
Control over colloidal nanocrystal morphology (size, size distribution, and shape) is important for tailoring the functionality of individual nanocrystals and their ensemble behavior. Despite this, traditional methods to quantify nanocrystal morphology are laborious. New developments in automated morphology classification will accelerate these analyses but the assessment of machine learning models is limited by human accuracy for ground truth, causing even unsupervised machine learning models to have inherent bias. Herein, we introduce synthetic image rendering to solve the ground truth problem of nanocrystal morphology classification. By simulating 2D images of nanocrystal shapes via a function of high-dimensional parameter space, we trained a convolutional neural network to link unique morphologies to their simulated parameters, defining nanocrystal morphology quantitatively rather than qualitatively. An automated pipeline then processes, quantitatively defines, and classifies nanocrystal morphology from experimental transmission electron microscopy (TEM) images. Using improved computer vision techniques, 42,650 nanocrystals were identified, assessed, and labeled with quantitative parameters, offering a 600-fold improvement in efficiency over best-practice manual measurements. Further, a classification algorithm was trained with a prediction accuracy of 99.5%, which can successfully analyze a range of concave, convex, and irregular nanocrystal shapes. The resulting pipeline was applied to differentiating two syntheses of nominally cuboidal CsPbBr 3 nanocrystals and uniquely classifying binary nickel sulfide nanocrystal phase based on morphology. This pipeline provides a simple, efficient, and unbiased method to quantify nanocrystal morphology and represents a practical route to construct large datasets with an absolute ground truth for training unbiased morphology-based machine learning algorithms.
Low-temperature electrochemical cells reducing iron oxides to metal in alkaline electrolytes can support fully electrified steelmaking processes. Previous studies on these cells have primarily focused on high-surface-area hematite, Fe 2 O 3 , reactants whereas attempts to reduce suspensions of magnetite, Fe 3 O 4 —one of the two feedstocks for existing ironmaking reactors—have generally been limited to low rates of reaction (<30 mA cm −2 ). Here, in this study, we control the crystalline domain size of Fe 2 O 3 and Fe 3 O 4 particles in 10 M NaOH electrolytes to study how the nanoscale morphology of oxides controls the rate of electrochemical ironmaking. Rotating-ring disk electrode measurements of Fe 2+ , in situ Raman spectroscopy of the electrode surface, and ex situ electron microscopy were consistent with a hypothesized passivation process at Fe 3 O 4 surfaces that may prevent the continuous formation of soluble intermediates. Sufficiently small (<100 nm diameter) oxide particles yielded Fe partial current densities >160 mA cm −2 , a fivefold increase relative to previously reported rates for Fe 3 O 4 suspensions and comparable to active Fe 2 O 3 . Electron microscopy revealed that electrodeposited films were composed of micron-scale crystalline Fe domains with a porous film of Fe 3 O 4 nanoparticles and supports a model where Fe is grown primarily from soluble Fe 2+ intermediates. Based on these insights, inactive blast-furnace-grade iron-oxides were transformed into high surface area nanoparticles (1.6 to 229.2 m 2 g −1 ) via reprecipitation, leading to a ninefold enhancement in faradaic efficiency and an Fe partial current density of 120 mA cm −2 . When integrated with chlor-iron cells producing reagents for reprecipitation, this approach could lead to a cost-competitive process for electrochemical ironmaking from industrially relevant feedstocks.
We report postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario.
Postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario
A lithium and manganese rich nickel-manganese-cobalt oxide (LMR-NMC) cathode is a promising candidate for next-generation batteries due to its high specific capacity, low cost, and low cobalt content. However, the material suffers from poor rate capability due to the diffusion limitations of lithium in the cathode particles. Understanding the material performance requires careful control of the morphology of the cathode particles, taking into account the primary and agglomerated diffusion pathways and the presence of pores, some of which could be closed from electrolyte infiltration. Here, in this study, we use a microstructure-based mathematical model combined with experimental data to understand the role of the complex cathode particle morphology in the rate performance of the material. Scanning electron microscopy images of cathodes made under different synthesis conditions, which results in different agglomerate morphologies, serve as the input into the mathematical model. The model is then compared to rate data to understand the controlling parameters. The presence of intra-agglomerate closed pores results in a large agglomerate diffusion length in comparison to the ideal condition, where the primary particles are agglomerated in an open and dispersed manner such that the entire interfacial area is available for electrochemical reaction. Smaller primary and agglomerate diffusion lengths result in better electrochemical performance. This points us toward designing the morphology of the cathode particles to compensate for the diffusion limitation of LMR-NMC while maximizing the density.
Here we present that materials with van der Waals bonding show exotic physics and may have applications in a variety of areas including new optoelectronic devices, spintronic devices, and as quantum materials. To date, control over the morphology and surface orientation of thin films of these materials without substrate pretreatment has been difficult. In this paper, the authors report the growth of Bi 2 Se 3 on GaAs (001) substrates. By controlling the growth conditions and adatom mobility, the authors are able to obtain epitaxial growth in the (0015) orientation without substrate prepatterning. Although the growth window is small, this demonstration opens the door for future control of the orientation of van der Waals materials through control of parameters during growth and via interaction with the substrate.
One strategy for addressing the climate crisis caused by CO 2 emissions is to efficiently convert CO 2 to advanced materials suited for green and clean energy technology applications. Porous carbon is widely used as an advanced energy storage material because of its enhanced energy storage capabilities as an anode. Herein, we report electrochemical CO 2 upcycling to solid carbon with a controlled microstructure and porosity in a ternary molten carbonate melt at 450 °C. Controlling the electrochemical parameters (voltage, temperature, cathode material) enabled the conversion of CO 2 to porous carbon with a tunable morphology and porosity for the first time at such a low temperature. Additionally, a well-controlled morphology and porosity are beneficial for reversible energy storage. In fact, these carbon materials delivered high specific capacity, stable cycling performances, and exceptional rate capability even under extremely fast charging conditions when integrated as an anode in lithium-ion batteries (LIBs). In conclusion, the present approach not only demonstrated efficient upcycling of CO 2 into porous carbon suitable for enhanced energy storage but can also contribute to a clean and green energy technology that can reduce carbon emissions to achieve sustainable energy goals.
In analogy to supramolecular assemblies, which are pursued because of properties above and beyond those of the individual molecules, self-standing monolithic three-dimensional assemblies of nanoparticles also have unique properties attributed to their structure. For example, ultra low-density 3-D assemblies of silica nanoparticles, known as silica aerogels, are characterized by large internal void space, high surface area and very low thermal conductivity. Aerogels, however, are also extremely fragile materials, limiting their application to a few specialized environments, e.g., in nuclear reactors as Cerenkov radiation detectors, in space (refer to NASA's Stardust Program) and aboard certain planetary vehicles (thermal insulators on Mars Rovers in 1997 and 2004). The fragility problem is traced to well-defined weak points in the aerogel skeletal framework, the interparticle necks. Using the surface functionality of the nanoparticle building blocks as a focal point, we have directed attachment of a conformal polymer coating over the entire framework, rendering all necks wider. Thus, although the bulk density may increase only by 3x, the mesoporosity (pores in the range 2-50 nm) remains unchanged, while the strength of the material increases by up to 300... Having addressed the fragility problem, aerogels are now robust materials, and a variety of applications, ranging from thermal/acoustic insulators to catalyst supports, to platform for sensors, and dielectrics are all within reach. Our approach employs molecular science to manipulate nanoscopic matter for achieving useful macroscopic properties, and in our view it resides at the core of what defines nanotechnology. In that spirit, this technology is expandable in three directions. Thus, we have already crosslinked successfully amine-modified silica, and we anticipate that more rich chemistry will be realized by been creative with the nanoparticle surface modifiers. On the other hand, although we do not expect orders-of-magnitude increase in strength, nevertheless, by varying the polymer we expect to impart other properties such as hydrophobicity, thermal stability and perhaps electrical conductivity. Besides polymers, crosslinkers will include metals and ceramics (e.g., through POSS precursors). Finally, network morphology directs load dissipation, and of approximately 30 different crosslinked oxide aerogels, vanadia, whose structure is fibrous rather than particulate, yields a much stronger (by 4..) material than silica of the same density. It seems imperative to implement control of network morphology, even through templating.