Safety of the next-generation space flight vehicles requires development of an in-flight Failure Detection and Prognostic (FD&P) system. Development of such system is challenging task that involves analysis of many hard hitting engineering problems across the board. In this paper we report progress in the development of FD&P for the re-contact fault between upper stage nozzle and the inter-stage caused by the first stage and upper stage separation failure. A high-fidelity models and analytical estimations are applied to analyze the following sequence of events: (i) structural dynamics of the nozzle extension during the impact; (ii) structural stability of the deformed nozzle in the presence of the pressure and temperature loads induced by the hot gas flow during engine start up; and (iii) the fault induced thrust changes in the steady burning regime. The diagnostic is based on the measurements of the impact torque. The prognostic is based on the analysis of the correlation between the actuator signal and fault-induced changes in the nozzle structural stability and thrust.

We use all-atom molecular dynamics simulations to investigate ionic conduction in a short, charged, single-wall carbon nanotube. They reveal ionic Coulomb blockade (ICB) oscillations in the current as a function of the fixed charge on the wall, and an associated occupancy staircase. Current peaks related to fluctuations around the 2 → 1 and 1 → 0 steps in occupancy are clearly resolved, in agreement with ICB theory. Current peaks were also observed at constant occupancy. These unpredicted secondary peaks are attributed to edge effects involving a remote knock-on mechanism; they are attenuated, or absent, for certain choices of model parameters. The key parameters of the system that underlie the current oscillations are estimated using ICB theory and the potential of the mean force. Future perspectives opened up by these observations are discussed.

Using a statistical linear response theory, we present a complex phase structure describing ionic conduction through a nanopore as a function of pore structure. This picture sheds light on the permeation mechanism, and selectivity between ions of alike and differing charge; and is calculated explicitly from first principles via the statistical properties including particle number fluctuations. We therefore expect the theory to be applicable to the functionalisation and design of highly selective nanopores.

We study selective ionic diffusion in a single-walled carbon nanotube (CNT). The wall is charged so as to mimic the structure of the selectivity filters in biological ion channels. We use all-atom molecular dynamics simulations to demonstrate that a charged CNT can closely reproduce many of the selectivity and conductivity properties of the KcsA biological channel. A K + /Na + selectivity ratio ≳150 and a conduction current Ftable ≳50 pA are demonstrated. It is shown that ionic Coulomb blockade is the key phenomenon underlying the CNT conduction properties. Coulomb blockade theory is used to estimate the excess chemical potential of the ions in the channel and the channel capacitance.

Nonlinear shrinkage of the metal part during manufacturing by bound metal deposition, both on the ground and under microgravity, is considered. A multi-scale physics-based approach is developed to address the problem. It spans timescales from atomistic dynamics on the order of nanoseconds to full-part shrinkage on the order of hours. This approach enables estimation of the key parameters of the problem, including the widths of grain boundaries, the coefficient of surface diffusion, the initial redistribution of particles during the debinding stage, the evolution of the microstructure from round particles to densely-packed grains, the corresponding changes in the total and chemical free energies, and the sintering stress. The method has been used to predict shrinkage at the levels of two particles, of the filament cross-section, of the sub-model, and of the whole green, brown, and metal parts.

Most analytic theories describing electrostatically driven ion transport through water-filled nanopores assume that the corresponding permeation barriers are bias-independent. While this assumption may hold for sufficiently wide pores under infinitely small bias, transport through subnanometer pores under finite bias is difficult to interpret analytically. Given recent advances in subnanometer pore fabrication and the rapid progress in detailed computer simulations, it is important to identify and understand the specific field-induced phenomena arising during ion transport. Here we consider an atomistic model of electrostatically driven ion permeation through subnanoporous C2N membranes. We analyze probability distributions of ionic escape trajectories and show that the optimal escape path switches between two different configurations depending on the bias magnitude. We identify two distinct mechanisms contributing to field-induced changes in transport-opposing barriers: a weak one arising from field-induced ion dehydration and a strong one due to the field-induced asymmetry of the hydration shells. The simulated current–voltage characteristics are compared with the solution of the 1D Nernst–Planck model. Finally, we show that the deviation of simulated currents from analytic estimates for large fields is consistent with the field-induced barriers and the observed changes in the optimal ion escape path.

In order to permeate a nanopore, an ion must overcome a dehydration energy barrier caused by the redistribution of surrounding water molecules. The redistribution is inhomogeneous, anisotropic and strongly position-dependent, resulting in complex patterns that are routinely observed in molecular dynamics simulations. Here, we study the physical origin of these patterns and of how they can be predicted and controlled. We introduce an analytic model able to predict the patterns in a graphene nanopore in terms of experimentally accessible radial distribution functions, giving results that agree well with molecular dynamics simulations. The patterns are attributable to a complex interplay of ionic hydration shells with water layers adjacent to the graphene membrane and with the hydration cloud of the nanopore rim atoms, and we discuss ways of controlling them. Our findings pave the way to designing required transport properties into nanoionic devices by optimising the structure of the hydration patterns. The redistribution of water molecules when an ion passes through a nanopore is known to create complex patterns. Here, an analytical model accurately predicts the patterns when an ion passes through a graphene nanopore, and reveals the physical origins of the patterns.

Biological ion channels are fundamental to maintaining life. In this manuscript we apply our recently developed statistical and linear response theory to investigate Na+ conduction through the prokaryotic Na+ channel NaChBac. This work is extended theoretically by the derivation of ionic conductivity and current in an electrochemical gradient, thus enabling us to compare to a range of whole-cell data sets performed on this channel. Furthermore, we also compare the magnitudes of the currents and populations at each binding site to previously published single-channel recordings and molecular dynamics simulations respectively. In doing so, we find excellent agreement between theory and data, with predicted energy barriers at each of the four binding sites of ∼4,2.9,3.6, and 4kT.

We introduce a statistical and linear response theory of selective conduction in biological ion channels with multiple binding sites and possible point mutation. We derive an effective grand-canonical ensemble and generalized Einstein relations for the selectivity filter, assuming strongly coordinated ionic motion, and allowing for ionic Coulomb blockade. The theory agrees well with data from the KcsA K^{+} channel and a mutant. We show that the Eisenman relations for thermodynamic selectivity follow from the condition for fast conduction and find that maximum conduction requires the binding sites to be nearly identical.

“There is plenty of room at the bottom” [...]

We propose a method to describe analytically the ionic hydration patterns near sub-nanopores. It agrees well with molecular dynamics simulations, predicts the locations of the trapped water molecules, and captures the intrinsic and extrinsic features of the nanopores. Our method would open the way to designing and optimising controllable nanoionic devices with on-demand selective and conductive properties, finding applications in water desalination, energy harvesting, and DNA sequencing.

Mutation-induced transformations of conductivity and selectivity in NaChBac bacterial channels are studied experimentally and interpreted within the framework of ionic Coulomb blockade (ICB), while also taking account of resonant quantised dehydration (QD) and site protonation. Site-directed mutagenesis and whole-cell patch-clamp experiments are used to investigate how the fixed charge Qf at the selectivity filter (SF) affects both valence selectivity and same-charge selectivity. The new ICB/QD model predicts that increasing ∣Qf∣ should lead to a shift in selectivity sequences toward larger ion sizes, in agreement with the present experiments and with earlier work. Comparison of the model with experimental data leads to the introduction of an effective charge Qf∗ at the SF, which was found to differ between Aspartate and Glutamate charged rings, and also to depend on position within the SF. It is suggested that protonation of the residues within the restricted space of the SF is important in significantly reducing the effective charge of the EEEE ring. Values of Qf∗ derived from experiments on divalent blockade agree well with expectations based on the ICB/QD model and have led to the first demonstration of ICB oscillations in Ca2+ conduction as a function of the fixed charge. Preliminary studies of the dependence of Ca2+ conduction on pH are qualitatively consistent with the predictions of the model.

We consider an atomistic model of thermal welding at the polymer-polymer interface of a polyetherimide/polycarbonate blend, motivated by applications to 3D manufacturing in space. We follow diffusion of semiflexible chains at the interface and analyze strengthening of the samples as a function of the welding time t(w) by simulating the strain-stress and shear viscosity curves. The time scales for initial wetting, and for fast and slow diffusion, are revealed. It is shown that each component of the polymer blend has its own characteristic time of slow diffusion at the interface. Analysis of strain-stress demonstrates saturation of the Young's modulus at t(w) = 240 ns, while the tensile strength continues to increase. The shear viscosity is found to have a very weak dependence on the welding time for t(w) > 60 ns. It is shown that both strain-stress and shear viscosity curves agree with experimental data. Welding dynamics and strengthening of the interface in the polyetherimide blend are analyzed using molecular dynamics. Time scales for initial welding of blend components are revealed. The strengthening is characterized by the strain-stress and shear viscosity curves obtained at different welding times. A way to control welding time in 3D manufacturing is proposed. The revealed features of the dynamics of semiflexible polymer chains are of importance for theoretical developments and practical applications.

Selective permeation through graphene nanopores is attracting increasing interest as an efficient and cost-effective technique for water desalination and purification. In this work, using umbrella sampling and molecular dynamics simulations with constant electric field, we analyze the influence of pore charge on potassium and chloride ion permeation. As pore charge is increased, the barrier of the potential of mean force (PMF) gradually decreases until it turns into a well split in two subminima. While in the case of K+ this pattern can be explained as an increasing electrostatic compensation of the desolvation cost, in the case of Cl- the pattern can be attributed to the accumulation of a concentration polarization layer of potassium ions screening pore charge. The analysis of potassium PMFs in terms of forces revealed a conflicting influence on permeation of van der Waals and electrostatic forces that both undergo an inversion of their direction as pore charge is increased. Even if the most important transition involves the interplay between the electrostatic forces exerted by graphene and water, the simulations also revealed an important role of the changing distribution of potassium and chloride ions. The influence of pore charge on the orientation of water molecules was also found to affect the van der Waals forces they exert on potassium.

In this article we apply our multi-component statistical and linear response theory to the process of mixed-valence ionic transport in a biological sodium ion channel. We analyse the free energy spectra, and statistical fluctuations (which are proportional to the conductivity) to investigate conditions and optimal parameters required for selectivity.

The rising number of small unmanned aerial vehicles (UAVs) expected in the next decade will enable a new series of commercial, service, and military operations in low altitude airspace as well as above densely populated areas. These operations may include on-demand delivery, medical transportation services, law enforcement operations, traffic surveillance and many more. Such unprecedented scenarios create the need for robust, efficient ways to monitor the UAV state in time to guarantee safety and mitigate contingencies throughout the operations. This work proposes a generalized monitoring and prediction methodology that utilizes realtime measurements of an autonomous UAV following a series of way-points. Two different methods, based on sinusoidal acceleration profiles and high-order splines, are utilized to generate the predicted path. The monitoring approach includes dynamic trajectory re-planning in the event of unexpected detour or hovering of the UAV during flight. It can be further extended to different vehicle types, to quantify uncertainty affecting the state variables, e.g., aerodynamic and other environmental effects, and can also be implemented to prognosticate safety-critical metrics which depend on the estimated flight path and required thrust. The proposed framework is implemented on a simplified, scalable UAV modeling and control system traversing 3D trajectories. Results presented include examples of real-time predictions of the UAV trajectories during flight and a critical analysis of the proposed scenarios under uncertainty constraints.

We analyze selective ionic conduction through an artificial nanopore in a single graphene sheet, using molecular dynamics simulations and the prehistory probability distribution. We assess position-dependent changes in the number and orientation of water molecules in the first and second hydration shells of the ion as it crosses the nanopore. We reveal coupling between an ionic double layer near the sheet to the statistical properties of the hydration shells.

We study a molecular dynamics model of a polymer-polymer interface for a polyetherimide/polycarbonate blend, including its thermodynamic properties, its chain reptation, and its corresponding welding characteristics. The strength of the sample is analyzed by measuring strain-stress curves in simulations of uni-axial elongation. The work is motivated by potential applications to 3D manufacturing in space.