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This presentation provides an overview of the aerospace supply chain and how the AAM Supply Chain Working Group will help to make it more sustainable and resilient. The urgent needs are building a tiered system, a modeling and simulation platform, and an electronic exchange platform.
Groundwater acidification co-occurring with nitrate pollution is a common, global environmental health hazard. Denitrifying bacteria have been leveraged for the in situ removal of nitrate in groundwater. However, co-existing stressors—such as low pH—reduce the efficacy of biological removal processes. Castellaniella sp. str. MT123 is a complete denitrifier that was isolated from acidic, nitrate-contaminated groundwater. The strain grows robustly by nitrate respiration at pH < 6.0, completely reducing nitrate to dinitrogen gas. Genomic analyses of MT123 revealed few previously characterized acid tolerance genes. Thus, we utilized a combination of proteomics, metabolomics, and competitive mutant fitness to characterize the genetic mechanisms of MT123 acclimation to growth under mildly acidic conditions. We found that glutamate accumulation is critical in the acid acclimation of MT123, possibly through consumption of intracellular protons via glutamate decarboxylation to GABA. This is despite the fact that MT123 lacks the canonical glutamate decarboxylase-glutamate/GABA antiporter system implicated in acid tolerance in other bacteria. In contrast, branched-chain amino acid (BCAA) accumulation was detrimental to cell growth at lower pHs, possibly through indirect mechanisms impacting the cellular glutamate pool. Genetic analysis previously linked MT123 to a population of Castellaniella that bloomed—concurrent to nitrate removal—during a biostimulation effort to reduce groundwater nitrate concentrations at MT123’s location of origin. Thus, our analyses provide novel insight into mechanisms of acclimation to acidic conditions in a strain with significant potential for nitrate bioremediation.
The COVID-19 pandemic exposed important flaws in the inbound supply chain for vaccines. NIIMBL and CESMII are working with key stakeholders to develop a means for vaccine manufacturers and suppliers to share information securely for improved supply chain tracking, resilience, and optimization.
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A systematic analysis is presented of the algorithm for converting a virtual-bond chain, defined by the coordinates of the alpha-carbons of a given protein, into a complete polypeptide backbone. An alternative algorithm, based upon the same set of geometric parameters used in the Purisima-Scheraga algorithm but with a different "linkage map" of the algorithmic procedures, is proposed. The global virtual-bond chain geometric constraints are more easily separable from the loal peptide geometric and energetic constraints derived from, for example, the Ramachandran criterion, within the framework of this approach.
Poly(4–4′-oxydiphenylene-pyromellitimide)-based polyimides─trade name Kapton─have wide-ranging engineering applications owing to their thermal and mechanical stability, but little is known about underlying chain-level characteristics. While theoretical models have conceptualized Kapton as inflexible polycyclic rods separated by freely rotating diphenyl ether hinge groups, the model’s core predictions remain untested and subtleties of the relaxation behavior are missed, which atomistic modeling can resolve. To these ends, we examine all-atom Kapton structures in crystalline and glassy amorphous configurations using a DFT-validated class II force field. Constructing amorphous configurations is challenging, as the fused-ring-containing backbone has slow relaxation dynamics and scaling suggestive of entanglements even in oligomers. In conclusion, we find larger backbone rearrangements of the linear polycyclic segments about ether groups that are consistent with the rod-hinge picture on the monomer scale, whereas a ring rotation analysis suggests partially flexible rod-like segments and involves multiple facile rotational relaxation modes.
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Crystalline absorption of polymer single crystals
We present an experimental study of the dynamics of isolated chains made of super-paramagnetic particles under the influence of a magnetic field. The motivation of this work is to understand if the chain fluctuations exist and, if it does, how does the fluctuation affect chain aggregation. We find that single chains strongly fluctuate and that the characteristic frequency of their fluctuations is inversely proportional to the magnetic field strength. The higher the field the lower the characteristic frequency of the chain fluctuations. In the high magnetic field limit, chains behave like rigid rods without any internal motions. In this work, we used ferrofluid particles suspended in water. These particles do not have any intrinsic magnetization. Once a magnetic field is applied, a dipole moment is induced in each particle, proportional to the magnetic field. A dipolar magnetic interaction then occurs between particles. If dipole-dipole magnetic energy is higher than the thermal energy, the result is a structure change inside the dipolar fluid. The ratio of these two energies is expressed by a coupling constant lambda as: lambda = (pi(a(exp 3))(chi(exp 2))(mu(sub 0))(H(sub 0))(exp 2))/18kT Where a is the particle radius, mu(sub 0) is the vacuum magnetic permeability, H(sub 0) the applied magnetic field, k the Boltzmann constant and T the absolute temperature. If lambda > 1, magnetic particles form chains along the field direction. The lateral coalescence of several chains may form bigger aggregates especially if the particle volume fraction is high. While many studies and applications deal with the rheological properties and the structural changes of these dipolar fluids, this work focuses on the understanding of the chain dynamics. In order to probe the chain dynamics, we used dynamic light scattering (DLS) in self-beating mode as our experimental technique. The experimental geometry is such that the scattering plane is perpendicular to the magnetic field. Therefore, only motions in this plane are probed. A very dilute sample of a ferrofluid emulsion with a particle volume fraction of 10(exp -5) is used in this experiment. We chose such a low volume fraction to avoid multiple light scattering as well as lateral chain-chain aggregation. DLS measures the dynamic structure factor S(q,t) of the sample (q is the scattering wave vector, t is the time). In the absence of the magnetic field, identical particles of ferrofluid droplets are randomly distributed and S(q,t) reduces to exp(-q(exp 2)2D(sub 0)t). D(sub 0)=(kT/(6(pi)(eta)(a)) is the diffusion coefficient of Brownian particles (where Xi = (6(pi)(eta)(a)) is the Stokes frictional coefficient of a spherical particle in a fluid of viscosity eta). If interactions or polydispersity can not be ignored, an effective diffusion coefficient is introduced. Formally, D(sub eff) is defined as: D(sub eff) = - q(exp -2) partial derivative of (ln(S(q,t)) with respect to time, as t goes to 0. D(sub eff) reduces to D(sub 0) if no interactions and only a few particles size are present. Therefore, we can use DLS to measure particle size. The particle radius was found to be a=0.23 mu m with 7% of polydispersity. In this case, if we vary the scattering angle theta (and so q) we do not have any change in the measured diffusion coefficient: it is q-independent. When a magnetic field is applied, particles aggregate into chains if lambda > 1. We first studied the kinetics of the chain formation when lambda = 406. At a fixed scattering angle, we measured diffusion coefficient D(sub eff) as a function of time. Experimentally, we find that D(sub eff) decreases monotonously with time. Physically, this means that chains are becoming longer and longer. Since we are only sensitive to motions in the scattering plane and since chains have their main axis perpendicular to this plane, the measured diffusion coefficient is the trans-verse diffusion coefficient. We can relate D(sub eff) to the mean number of particles per chain N(t) at a given time and to the diffusion coefficient of an isolated particle D(sub 0) as D(sub eff)=f(N(t))D(sub 0). Since f(N) is known from other recent work, N can be expressed as a function of the time. We found a square root dependency: N(t) proportional to the square root of t. As expected for very low volume fraction, this behavior is characteristic of a diffusion-limited aggregation as suggested by several authors and by our previous work. In this study, we focus on the dependence of the effective diffusion coefficient on the scattering angle and the magnetic field strength. After the magnetic field is applied (lambda = 406) for a long time, typically 6 hours, kinetics of chain formation becomes very slow. Chain size does not vary much over the next hour period. Thus, we can perform different interesting experiments. First, at a fixed magnetic field, we measure the effective diffusion coefficient as a function of the scattering angle (from 5 to 130 deg). Our results show that the measured diffusion coefficient increases linearly with the scattering angle: D(sub eff) proportional to q. If we do the same experiment for different lambda values, D(sub eff) depends on lambda as D(sub eff) proportional to lambda(exp -1/2). We also find for different lambda values that the same asymptotic D(sub eff) value is obtained when q approaches zero. The angle dependency of D(sub eff) suggests that an additional motion exists besides chain drifting. Chain size is constant during experiment, which was verified by measuring the same diffusion coefficient at the beginning and at the end of the angle switching. If chains are rigid, D(sub eff) is independent of q. Therefore, we found that D(sub eff) not only measures the motion of the entire chain but also its internal fluctuations. These internal motions are the fluctuations of the particles in the chain. To understand the q dependency of D(sub eff), let us look at the probing length used. In our study, the characteristic length scale probed is l=2pi/q which is in the range of 0.9<l/a<20. When l is much larger than the particle radius (l/a going to infinity) we are mainly sensitive to the center of mass diffusion of the chain. D(sub eff) is then the diffusion of the entire chain and depends only on N but not on q and lambda. The value D(sub eff) allows us to obtain the number of particles per chain N. In the opposite limit (i.e. l/a < 1), we are sensitive to motions on the size of individual particles. The main contributions to the measured diffusion coefficient come from internal motions of the chains (i.e. particles' fluctuations inside the chain). We investigated also the effect of the chain size on D(sub eff). For the same value of the magnetic interaction lambda and different chain sizes, we found that the slope of D(sub eff) versus q decreases when N increases as a power law D(sub eff) proportional to N(exp -0.7). This is an important behavior because this means that the longer the chain the slower its internal fluctuations besides the whole chain motion.
Magnetorheological (MR) suspensions are composed of colloidal particles which acquire dipole moments when subjected to an external magnetic field. At sufficient field strengths and concentrations, the dipolar particles rapidly aggregate to form long chains. Subsequent lateral cross-linking of the dipolar chains is responsible for a rapid liquid-to-solid-like rheological transition. The unique, magnetically-activated rheological properties of MR suspensions make them ideal for interfacing mechanical systems to electronic controls. Additionally, the ability to experimentally probe colloidal suspensions interacting through tunable anisotropic potentials is of fundamental interest. Our current experimental work has focused on understanding the fluctuations of dipolar chains. It has been proposed by Halsey and Toor (HT) that the strong Landau-Peierls thermal fluctuations of dipolar chains could be responsible for long-range attractions between chains. Such interactions will govern the long-time relaxation of MR suspensions. We have synthesized monodisperse neutrally buoyant MR suspensions by density matching stabilized ferrofluid emulsion droplets with D2O. This allows us to probe the dynamics of the dipolar chains using light scattering without gravitational, interfacial, and polydispersity effects to resolve the short-wavelength dynamics of the dipolar chains. We used diffusing wave spectroscopy to measure these dynamics. The particle displacements at short times that show an independence to the field strength, but at long times exhibit a constrained, sub-diffusive motion that slows as the dipole strength is increased. The experiments are in good qualitative agreement with Brownian dynamics simulations of dipolar chains. Although there have been several important and detailed studies of the structure and interactions in MR suspensions, there has not been conclusive evidence that supports or contradicts the HT model prediction that long-range interactions exist between fluctuating chains of dipolar particles. Resolving this issue would contribute greatly to the understanding of these interesting and important materials. We have begun to test the predictions of the HT model by both examining the dynamics of individual chains and by measuring the forces between dipolar chains directly to accurately and quantitatively assess the interactions that they experience. To do so, we employ optical trapping techniques and video-microscopy to manipulate and observe our samples on the microscopic level. With these techniques, it is possible to observe chains that are fluctuating freely in three-dimensions, independent of interfacial effects. More importantly, we are able to controllably observe the interactions of two chains at various separations to measure the force-distance profile. The techniques also allow us to study the mechanical properties of individual chains and chain clusters. Our work to this point has focused on reversibly-formed dipolar chains due to field induced dipoles where the combination of this chaining, the dipolar forces, and the hydrodynamic interactions that dictate the rheology of the suspensions. One can envision, however, many situations where optical, electronic, or rheological behavior may be optimized with magneto-responsive anisotropic particles. Chains of polarizable particles may have the best properties as they can coil and flex in the absence of a field and stiffen and orient when a field is applied. We have recently demonstrated a synthesis of stable, permanent paramagnetic chains by both covalently and physically linking paramagnetic colloidal particles. The method employed allows us to create monodisperse chains of controlled length. We observed the stability, field-alignment, and rigidity of this new class of materials. The chains may exhibit unique rheological properties in an applied magnetic field over isotropic suspensions of paramagnetic particles. They are also useful rheological models as bead-spring systems. These chains form the basis for our current experiments with optical traps.
Prominent crater chains on Ganymede and Callisto are most likely the impact scars of comets tidally disrupted by Jupiter and are not secondary crater chains. We have examined the morphology of these chains in detail in order to place constraints on the properties of the comets that formed them and the disruption process. In these chains, intercrater spacing varies by no more than a factor of 2 and the craters within a given chain show almost no deviation from linearity (although the chains themselves are on gently curved small circles). All of these crater chains occur on or very near the Jupiter-facing hemisphere. For a given chain, the estimated masses of the fragments that formed each crater vary by no more than an order of magnitude. The mean fragment masses for all the chains vary by over four orders of magnitude (W. B. McKinnon and P. M. Schenk 1995, Geophys. Res. Lett. 13, 1829-1832), however. The mass of the parent comet for each crater chain is not correlated with the number of fragments produced during disruption but is correlated with the mean mass of the fragments produced in a given disruption event. Also, the larger fragments are located near the center of each chain. All of these characteristics are consistent with those predicted by disruption simulations based on the rubble pile cometary nucleus model (in which nuclei are composed on numerous small fragments weakly bound by self-gravity), and with those observed in Comet D/Shoemaker-Levy 9. Similar crater chains have not been found on the other icy satellites, but the impact record of disrupted comets on Callisto and Ganymede indicates that disruption events occur within the Jupiter system roughly once every 200 to 400 years.
Due to the dramatic reduction in MOS size, there appear many unwanted effects. In these small devices, the number of dopant atoms in the channel is not macroscopic and electrons may suffer significantly different scattering from device to device since the spatial distribution of dopant atoms is no longer regarded as continuous. This prohibits integration, while it is impossible to control such dopant positions within atomic scale. A fundamental solution is to create electronics with simple but atomically precise structures, which could be fabricated with recent atom manipulation technology. All the constituent atoms are placed as planned, and then the device characteristics are deviation-free, which is mandatory for integration. Atomic chain electronics belongs to this category. Foreign atom chains or arrays form devices, and they are placed on the atomically flat substrate surface. We can design the band structure and the resultant Fermi energy of these structures by manipulating the lattice constant. Using the tight-binding theory with universal parameters, it has been predicted that isolated Si chains and arrays are metallic, Mg chains are insulating, and Mg arrays have metallic and insulating phases [1]. The transport properties along a metallic chain have been studied, emphasizing the role of the contact to electrodes [2]. For electronic applications, it is essential to establish a method to dope a semiconducting chain, which is to control the Fermi energy position without altering the original band structure. If we replace some of the chain atoms with dopant atoms randomly, the electrons will see random potential along die chain and will be localized strongly in space (Anderson localization). However, if we replace periodically, although the electrons can spread over the chain, there will generally appear new bands and band gaps reflecting the new periodicity of dopant atoms. This will change the original band structure significantly. In order to overcome this dilemma, we may place a dopant atom beside the chain at every N lattice periods (N > 1). Because of the periodic arrangement of pant atoms, we can avoid the unwanted Anderson localization. Moreover, since the dopant atoms do not constitute the chain, the overlap interaction between them is minimized, and the band structure modification can be made smallest. Some tight-binding results will be discussed to demonstrate the present idea.
This paper will present a Supply Chain Readiness Level (SCRL) model that can be used to evaluate and configure adaptable and sustainable program and mission supply chains at an enterprise level. It will also show that using SCRL in conjunction with Technology Readiness Levels (TRLs), Manufacturing Readiness Levels (MRLs) and National Aeronautics Space Administrations (NASA s) Project Lifecycle Process will provide a more complete means of developing and evaluating a robust sustainable supply chain that encompasses the entire product, system and mission lifecycle. In addition, it will be shown that by implementing the SCRL model, NASA can additionally define supplier requirements to enable effective supply chain management (SCM). Developing and evaluating overall supply chain readiness for any product, system and mission lifecycle is critical for mission success. Readiness levels are presently being used to evaluate the maturity of technology and manufacturing capability during development and deployment phases of products and systems. For example, TRLs are used to support the assessment of the maturity of a particular technology and compare maturity of different types of technologies. MRLs are designed to assess the maturity and risk of a given technology from a manufacturing perspective. In addition, when these measurement systems are used collectively they can offer a more comprehensive view of the maturity of the system. While some aspects of the supply chain and supply chain planning are considered in these familiar metric systems, certain characteristics of an effective supply chain, when evaluated in more detail, will provide an improved insight into the readiness and risk throughout the supply chain. Therefore, a system that concentrates particularly on supply chain attributes is required to better assess enterprise supply chain readiness.
Chain inflation is an alternative to slow-roll inflation in which the inflaton tunnels along a large number of consecutive minima in its potential. In this work we perform the first comprehensive calculation of the gravitational wave (GW) spectrum of chain inflation. In contrast to slow-roll inflation the latter does not stem from quantum fluctuations of the gravitational field during inflation, but rather from the bubble collisions during the first-order phase transitions associated with vacuum tunneling. Our calculation is performed within an effective theory of chain inflation which builds on an expansion of the tunneling rate capturing most of the available model space. The effective theory can be seen as chain inflation’s analog of the slow-roll expansion in rolling models of inflation. The near scale-invariance of the scalar power spectrum translates to a quasiperiodic shape of the inflaton potential in chain inflation, with the tunneling rate changing very slowly during the e-folds leading to cosmic microwave background observables. We show that chain inflation produces a very characteristic double-peak GW spectrum: a faint high-frequency peak associated with the gravitational radiation emitted during inflation, and a strong low-frequency peak associated with the graceful exit from chain inflation (marking the transition to the radiation-dominated epoch). There exist very exciting prospects to test the gravitational wave signal from chain inflation at the aLIGO-aVIRGO-KAGRA network, at LISA and /or at pulsar timing array experiments. A particularly intriguing possibility we point out is that chain inflation could be the source of the stochastic gravitational wave background recently detected by NANOGrav, PPTA, EPTA, and CPTA. We also show that the gravitational wave signal of chain inflation is often accompanied by running/ higher running of the scalar spectral index to be tested at future cosmic microwave background experiments. Published by the American Physical Society 2024
Due to the rapid progress in atom manipulation technology, atomic chain electronics would not be a dream, where foreign atoms are placed on a substrate to form a chain, and its electronic properties are designed by controlling the lattice constant d. It has been shown theoretically that a Si atomic chain is metallic regardless of d and that a Mg atomic chain is semiconducting or insulating with a band gap modified with d. For electronic applications, it is essential to establish a method to dope a semiconducting chain, which is to control the Fermi energy position without altering the original band structure. If we replace some of the chain atoms with dopant atoms randomly, the electrons will see random potential along the chain and will be localized strongly in space (Anderson localization). However, if we replace periodically, although the electrons can spread over the chain, there will generally appear new bands and band gaps reflecting the new periodicity of dopant atoms. This will change the original band structure significantly. In order to overcome this dilemma, we may place a dopant atom beside the chain at every N lattice periods (N > 1). Because of the periodic arrangement of dopant atoms, we can avoid the unwanted Anderson localization. Moreover, since the dopant atoms do not constitute the chain, the overlap interaction between them is minimized, and the band structure modification can be made smallest. Some tight-binding results will be discussed to demonstrate the present idea.
Atomic chains, precise structures of adatoms created on an atomically regulated surface, are candidates for constituent elements in future electronics. It was predicted that Si chains were metallic and Mg chains were semiconducting, and a doping method was also discussed. The substrate was assumed to work as a non-interacting template holding the adatoms. However, this scheme requires a low-temperature environment so that the adatoms will not displace from their ideal positions due to unwanted thermal agitation. For better structural stability, we may seek a scheme to allow the adatoms to form chemical bonding with the substrate atoms and secure their positions. The chemical bonding has two major effects on the chain electronic properties. First, only the remaining s and p orbitals in an adatom not used for the chemical bonding can decide chain band structures, rather than the full set of orbitals previously assumed. Second, because of a possible HOMO energy difference between adatom and substrate atom, semiconducting chains are unintentionally doped. These effects are studied with a self-consistent tight-binding method with universal parameters. With one adatom per unit cell, adatom chains are semiconducting: (1) if adatoms are of group III and form one chemical bond per adatom, or (2) if adatoms are of group IV and form two chemical bonds. 'Me previous result [I I of realizing semiconducting chains by group II adatoms without chemical bonds is consistent with this picture. When the HOMO energy in an adatom is shallower than that in a substrate atom, the entire chain is positively polarized, unintentionally achieving p-type doping. When deeper, the chain is negatively charged, achieving n-type doping.
This paper will present a model that uses the Supply-Chain Operations Reference (SCOR) model as a foundation for a framework to illustrate the information needed throughout a product lifecycle to support a healthy supply chain management function and the subsequent contract requirements to enable it. It will also show where in the supply chain the information must be extracted. The ongoing case study used to exemplify the model is NASA's (National Aeronautics and Space Administration) Ares I program for human spaceflight. Effective supply chain management and contract requirements are ongoing opportunities for continuous improvement within government agencies, specifically development of systems for human spaceflight operations. Multiple reports from the Government Accountability Office (GAO) reinforce this importance. The SCOR model is a framework for describing a supply chain with process building blocks and business activities. It provides a set of metrics for measuring supply chain performance and best practices for continuously improving. This paper expands the application of the SCOR to also provide the framework for defining information needed from different levels of the supply chain and at different phases of the lifecycle. These needs can be incorporated into contracts to enable more effective supply chain management. Depending on the phase of the lifecycle, effective supply chain management will require involvement from different levels of the organization and different levels of the supply chain.
Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.