Magnitude Reduction Research Articles

Suppression of the Petermann noise factor in a chiral optical mode converter without encircling an exceptional point

The engineering of exceptional points (EP) in gain-loss-assisted optical systems has recently garnered considerable attention for the development of unconventional photonic components. Moreover, the substantial noise associated with EPs poses a significant challenge to realizing their full potential in applications. There is a gap in the exploration of asymmetric mode conversion phenomena in the close proximity of the dynamical encirclement around an EP. In response, we propose the design of a fabrication-feasible dual-mode optical planar waveguide. Non-Hermiticity, in terms of a customized gain-loss profile, is introduced to modulate the interaction between the coupled modes. Contrary to previous assumptions, we establish that the dynamical encirclement of an EP is not a prerequisite for achieving asymmetric mode conversion. Furthermore, we calculate the Petermann factor (K) near the EP and demonstrate a significant two orders of magnitude reduction in the Petermann noise factor when we do not dynamically encircle the EP. Hence, we propose a new scheme to reduce the inherent noise.

Fast neural network inverse model to maximize throughput in ultra-wideband WDM systems

Ultra-wideband systems expand the optical bandwidth in wavelength-division multiplexed (WDM) systems to provide increased capacity using the existing fiber infrastructure. In ultra-wideband transmission, power is transferred from shorter-wavelength WDM channels to longer-wavelength WDM channels due to inelastic inter-channel stimulated Raman scattering. Thus, managing launch power is necessary to improve the overall data throughput. While the launch power optimization problem can be solved by the particle swarm optimization method it is sensitive to the objective value and requires intensive objective calculations. Hence, we first propose a fast and accurate data-driven deep neural network-based physical layer in this paper which can achieve 99%−100% throughput compared to the semi-analytical approach with more than 2 orders of magnitude improvement in computational time. To further reduce the computational time, we propose an iterative greedy algorithm enabled by the inverse model to well approximate a sub-optimal solution with less than 6% performance degradation but almost 3 orders of magnitude reduction in computational time.

In-situ CrFeCoNi medium entropy alloying coating via electrospark powder deposition

Medium or high-entropy alloys have led to widespread interest in their preparation, property control, and applications. The ability to apply these new alloys as coatings on conventional materials allows alternative surface treatment methods. This study used electrospark deposition with powder feedstock, to form MEA coating with fine-tuned compositions on steel substrate. Single-phase CrFeCoNi MEA using optimized ESD parameters and powder formulation. The phase and composition of MEA coatings and their hardness were also characterized. The coating showed two orders of magnitude reduction in specific wear rate coefficient compared with that of bare A516 steel substrate. This study demonstrates that the powder-based ESD technique can be used to create in-situ M/HEA coatings for applications requiring improved properties.

An end-to-end framework for the prediction of protein structure and fitness from single sequence

Significant research progress has been made in the field of protein structure and fitness prediction. Particularly, single-sequence-based structure prediction methods like ESMFold and OmegaFold achieve a balance between inference speed and prediction accuracy, showing promise for many downstream prediction tasks. Here, we propose SPIRED, a single-sequence-based structure prediction model that exhibits comparable performance to the state-of-the-art methods but with approximately 5-fold acceleration in inference and at least one order of magnitude reduction in training consumption. By integrating SPIRED with downstream neural networks, we compose an end-to-end framework named SPIRED-Fitness for the rapid prediction of both protein structure and fitness from single sequence with satisfactory accuracy. Moreover, SPIRED-Stab, the derivative of SPIRED-Fitness, achieves state-of-the-art performance in predicting the mutational effects on protein stability.

A combinatorial model reduction method for the finite element analysis of wind instruments

AbstractA high‐fidelity finite element model is proposed for the complete simulation of the time‐harmonic acoustic propagation in wind instruments. The challenge is to meet the extremely high accuracy required by professional musicians, in a complex domain, for all fingerings and over a wide frequency range, within an affordable computational time. Several modelling assumptions are made to limit the numerical complexity of the problem while preserving all relevant physics. A dedicated high‐performance solution strategy is also proposed, based on partitioning, condensation and model order reduction, exploiting the combinatorial nature of wind instrument fingerings. Finally, the proposed approach is applied to the simulation of an alto saxophone. An order of magnitude reduction in memory and computational cost is achieved.

Plasma-enhanced atomic layer deposition as a technique for controlling the composition and properties of indium-based transparent conductive oxides

Indium oxide and doped indium oxide films were successfully grown utilizing a plasma-enhanced atomic layer deposition supercycling process, which was found to be an effective means of controlling films’ composition and, hence, their properties. Using trimethylindium and oxygen plasma as an indium precursor and a co-reactant, respectively, a growth rate of approximately 1.26 Å per cycle was obtained based on thickness measurements by spectroscopic ellipsometry. Three distinct dopants, Sn, Ti, and Mo, have been incorporated into indium oxide. The effects of dopant type, cycle ratio of dopant to indium oxide, and thermal annealing on the structural, electrical, and optical properties were studied. The deposited films consisted of polycrystalline columnar grains perpendicular to the substrate with a cubic bixbyite structure and [111] as the favored growth direction. Thermal annealing had a significant effect on the film characteristics, resulting in an order of magnitude reduction in resistivity, as well as changes in transmittance in the near-infrared (NIR) and ultraviolet (UV) regions. The lowest resistivities achieved for Sn-doped, Ti-doped, and Mo-doped were 2.8 × 10−4, 4.2 × 10−4, and 6.1 × 10−4 Ω cm, respectively. The changes are attributed to dopant activation, as the UV shift between the differently doped samples may be linked to the Moss–Burstein effect and the NIR behavior can be explained by an increase in charge carrier density, as predicted by the Drude model. The three dopants primarily provide a trade-off between electrical resistance and NIR transparency. Mo-doped films exhibited the highest near-infrared transparency, while Sn-doped films offered the lowest sheet resistance.

Analysis of the effect of citrate on radionuclide retention on portlandite

We analysed how citrate (CIT), a chelating agent potentially present in radioactive waste disposals, affects the mobility of four radionuclides (RN): 63Ni, 233U, 152Eu, 238Pu in portlandite, an important hydrated phase of cement, a commonly used material for waste isolation.Portlandite was synthetized in the laboratory and showed high purity and grain size of few μm. This solid, buffers the pH to 12.5 and shows high adsorption capability for the studied RNs: 152Eu and 238Pu exhibited the highest adsorption (Kd ∼1·105 mL g−1) and 233U the lowest (Kd ∼8·102 mL g−1). CIT adsorption was also experimentally evaluated by batch sorption experiments and electrophoretic (ζ-potential) measurements: a non-lineal sorption behaviour was observed, with Kd values decreasing (from ∼1·103 mL g−1) as CIT concentration increased up to 1·10−2 M, according to portlandite sorption sites saturation.In the presence of CIT, a marginal decrease for 233U adsorption in portlandite was observed, one order of magnitude reduction for 63Ni, while 238Pu and 152Eu adsorption decreased significantly. The calculated sorption reduction factors (SRF) for the four RN in the presence of CIT at a concentration of 5·10−3 M were: 2.4, 9.7, 37 and 50.9 for 233U, 63Ni, 238Pu, and 152Eu, respectively.According to the available thermodynamic databases, low complexation between CIT and RN is predicted at pH = 12.5, thus the RN adsorption decrease in the presence of CIT must be attributed to the organic adsorption on portlandite. However, current thermodynamic are still incomplete for this ligand and this pH range and this limits a precise interpretation of the experimental data.

Revealing the intensification effect of circulating hydrothermal pretreatment: A sustainable route for biorefinery

Hydrothermal pretreatment (HTP) has received huge progress in converting biomass waste into available products at a large scale, but challenges in massive water input and wastewater output still block sustainable biorefinery future. Herein, a circulating hydrothermal technique was proposed by reusing the process wastewater into the next HTP process to enhance energy efficiency and suppress the environmental burdens. During hydrothermal liquid (HL) recycling, the variation of lignin chemical structure, cellulose accessibility, and soluble components were investigated for an in-depth understanding of what happened to lignocellulose. An enhanced hemicellulose dissolution (from 78.1 % to ∼ 85 %) was achieved by the aqueous phase recycling. The reactions of dehydration and polymerization occurred during the circulating HTP process, which contributed to the generation of pseudo-lignin on the cellulose surface, causing a slight weakening of cellulose accessibility. Meanwhile, the organic acid-catalyzed hydrothermal process can facilitate the cleavage of lignin β-O-4 ether linkage and condensation reaction, endowing its potential amphiphilic properties. An in-depth analysis of the evolution of HL components substantiated the potential intensification effect on biomass deconstruction by the generation of hemicellulose-derived organic acids. Life cycle assessment revealed that the circulating HTP technique resulted in about a 29 % reduction in primary energy depletion and an order of magnitude reduction in CO2 emissions as opposed to that of the conventional one. This work unveils the structure evolutions of lignocellulose clearly during the HL recycled process, and also highlights a feasible route for the sustainable biorefinery.

Scalable polyolefin-based all-organic dielectrics with superior high-temperature capacitive energy storage performance

Polymer dielectrics capable of efficient and stable operation at elevated temperatures (>150 °C) are urgently needed to meet the stringent requirements of capacitive energy storage in harsh environments. However, the current leading commercially available polymer dielectric, biaxially oriented polypropylene (BOPP), can only sustain continuous operation at temperatures below 85 °C due to its limited thermal stability and significant increase in electrical conduction at high temperatures. Here, we present an all-organic polymer composite comprising nonpolar polyolefin and organic semiconductor that demonstrates superior dielectric and capacitive energy storage performance at 150 °C. Notably, the dielectric properties of the polymer composite remain stable across a broad temperature range, exhibiting an ultralow dissipation factor at elevated temperatures. Benefiting from the deep trap energy levels introduced by the organic semiconductor, the composite film achieves one order of magnitude reduction in electrical conductivity. As a result, the composite film attains discharged energy densities of 7.1 J/cm3 and 5.5 J/cm3 with a charge-discharge efficiency of 90 % at 25 °C and 150 °C, respectively. Furthermore, the composite film maintains stable capacitive performance over extended charge-discharge cycles (50,000 cycles) in harsh environments (500 MV/m and 150 °C), along with excellent breakdown self-healing capability. These remarkable performances, coupled with the potential for large-scale production using commercially available raw materials, highlight the practically viability of the composite film for high-temperature capacitive energy storage applications.

Soret-Effect Induced Phase-Change in a Chromium Nitride Semiconductor Film.

Phase-change materials such as Ge-Sb-Te (GST) exhibiting amorphous and crystalline phases can be used for phase-change random-access memory (PCRAM). GST-based PCRAM has been applied as a storage-class memory; however, its relatively low ON/OFF ratio and the large Joule heating energy required for the RESET process (amorphization) significantly limit the storage density. This study proposes a phase-change nitride, CrN, with a much wider programming window (ON/OFF ratio more than 105) and lower RESET energy (one order of magnitude reduction from GST). High-resolution transmission electron microscopy revealed a phase-change from the low-resistance cubic CrN phase into the highly resistive hexagonal CrN2 phase induced by the Soret-effect. The proposed phase-change nitride could greatly expand the scope of conventional phase-change chalcogenides and offer a strategy for the next-generation of PCRAM, enabling a large ON/OFF ratio (∼105), low switching energy (∼100 pJ), and fast operation (∼30 ns).

Development of a New Dry Powder Aerosol Synthetic Lung Surfactant Product for Neonatal Respiratory Distress Syndrome (RDS) – Part I: In Vitro Testing and Characterization

PurposeImproving the deep lung delivery of aerosol surfactant therapy (AST) with a dry powder formulation may enable significant reductions in dose while providing improved efficacy. The objective of Part I of this two-part study was to present the development of a new dry powder aerosol synthetic lung surfactant (SLS) product and to characterize performance based on aerosol formation and realistic in vitro airway testing leading to aerosol delivery recommendations for subsequent in vivo animal model experiments.MethodsA new micrometer-sized SLS excipient enhanced growth (EEG) dry powder formulation was produced via spray drying and aerosolized using a positive-pressure air-jet dry powder inhaler (DPI) intended for aerosol delivery directly to intubated infants with respiratory distress syndrome (RDS) or infant-size test animals.ResultsThe best-case design (D2) of the air-jet DPI was capable of high emitted dose (> 80% of loaded) and formed a < 2 µm mass median aerodynamic diameter (MMAD) aerosol, but was limited to ≤ 20 mg mass loadings. Testing with a realistic in vitro rabbit model indicated that over half of the loaded dose could penetrate into the lower lung regions. Using the characterization data, a dose delivery protocol was designed in which a 60 mg total loaded dose would be administered and deliver an approximate lung dose of 14.7–17.7 mg phospholipids/kg with a total aerosol delivery period < 5 min.ConclusionsA high-efficiency aerosol SLS product was designed and tested that may enable an order of magnitude reduction in administered phospholipid dose, and provide rapid aerosol administration to infants with RDS.

Design and characteristics of a fiber laser powered repetitive micro-plasma jet triggered gas switch.

To satisfy the need for low jitter in gas switches at repetition rate and enhance insulation reliability during high voltage operation of the trigger, we propose a micro-jet triggering system. This system requires less energy and can use a laser power supply as an energy source. It effectively improves the insulation stability of the trigger when working at high potentials and achieves a good triggering effect with low jitter at low working coefficients. The breakdown characteristics were tested by double-pulse experiments. Ensuring the same operating conditions for both pulses, the pulse interval was varied to obtain the breakdown voltage dispersion at different repetition rates. The results indicate that the dispersion of the breakdown voltages can reach 0.16% at a frequency of 50Hz with a pulse front of 30 μs, representing an order of magnitude reduction compared to the 1.45% at switching self-breakdown, and decreases further as the air pressure rises. In addition, the size of the microcapillary has an impact on the dispersion of breakdown voltage. It was found that for a range of lengths from 2 to 6mm and aperture sizes from 80 to 400μm, the trigger jitter was lower when the length was larger and the aperture was smaller. Furthermore, a trigger life test was performed on the ceramic capillary, and after one million triggers, the system remained stable with no degradation in trigger performance.

Advancing marine post-combustion soot control: Diesel engine particles and soot capture through electrostatic-enhanced filtration

Marine post-combustion soot emission has become a critical issue due to its detrimental effects on global warming and accelerated glacier melting. In this study, a high-efficiency and low-resistance marine soot control method through electrostatic-enhanced filtration (EC-PF) was adopted. The effectiveness of EC-PF on diesel engine particles of different sizes and soot emissions under various engine loads and filtration temperatures was evaluated. EC-PF exhibited the best concentration enhancement effect at 25 % engine load, with an 82.2 % reduction in the number concentration of particles below 9.2 nm compared to PF, leading to an order of magnitude reduction in the total number concentration. As for the effect on pressure drop, under high engine loads at 373 K, EC-PF could even reduce the pressure drop rather than increase it by generating plasma to oxidize particles deposited in PF, reaching 40 % of the PF’s pressure drop. As the filtration temperature increased, EC-PF could still reduce the pressure drop increase by 26.3 % under full load conditions at 573 K. In addition, EC-PF could reduce the soot emission concentration to below 0.5 mg/m3 at different engine loads and temperatures, with a soot collection efficiency reaching 99 %, an over 3 % improvement over PF. During the long-term operation of EC-PF, it was necessary to reduce the operating voltage and perform purging of the electrostatic charger to prevent breakdown, which could fail pressure drop reduction. These findings hold significant implications for developing methods and legislation governing marine soot emissions control.

Mixed low‐dimensional metal halide perovskite single crystal for low‐detection‐limit x‐ray detection via oriented ion migration

AbstractLow‐dimensional metal halide perovskites exhibit exceptional photoelectronic properties and intrinsic stability, positioning them as a promising class of semiconductor materials for light‐emitting devices and photodetectors. In this work, we present a millimeter‐scale single crystal of mixed low‐dimensional (one‐dimensional–zero‐dimensional [1D–0D]) organic lead iodide with well‐defined crystallinity. The fabricated single‐crystal devices demonstrate high‐sensitivity photoresponse and x‐ray detection performance. By spatially isolating organic molecules to form the mixed 1D–0D crystal structure, ion migrations is effectively suppressed, resulting in a remarkable three orders of magnitude reduction in the dark current (56.4 pA @200 V) of the single‐crystal devices. Furthermore, by enhancing the background characteristics, we achieved an impressive low x‐ray detection limit of 154.5 nGys−1 in the single‐crystal device. These findings highlight that the mixed 1D–0D organic lead iodide configuration efficiently controls ion migration within the crystal structure, offering a promising avenue for realizing high‐performance perovskite‐based photodetectors and x‐ray detectors.image

A Method to Calculate the Maturity Time for Low Neutron Source Nuclear Reactor Startup Simulations

An approximate method for determining the maturity time is presented for applications in low neutron source nuclear reactor startup simulations. This new method relies only on the calculation of the mean neutron density and does not require the additional calculation of the variance in the neutron density as the traditional method does. The most accurate method for determining the safe neutron source strength, required to sufficiently mitigate the probability of a rogue transient during nuclear reactor startup, uses the Pál-Bell equations. However, as space and energy dependencies are included, the numerical computation become computationally demanding. Therefore, approximate methods that significantly reduce the computation time and improve the computational efficiency of the simulation while remaining very accurate are extremely useful. The approximate method for determining the maturity time presented in this study has shown excellent agreement with traditional methods while offering an order of magnitude reduction in computation time.

Unraveling PTSD: Symptom cluster change during and 1 year after veterans' residential PTSD treatment.

Although treatment of posttraumatic stress disorder (PTSD) is effective in reducing symptom severity, remission rates are low. One potential underlying reason for treatment ineffectiveness is differential response of specific PTSD symptom clusters. Using data from a national Veterans Affairs (VA) residential PTSD treatment cohort, we conducted a longitudinal study to examine changes in Diagnostic and Statistical Manual of Mental Disorders, fifth edition PTSD symptom clusters from admission to 1-year follow-up. PTSD symptom data were analyzed from a national cohort of veterans who completed VA PTSD residential treatment between October 2019 and September 2020 (n = 1,648; 13% women; median age 44.2 years). Endorsement (%) and severity (M[SD]) of PTSD clusters and individual symptoms were compared at admission, discharge, 4-month and 1-year follow-ups. Large magnitude reductions in all four PTSD symptom clusters were observed from admission to discharge and both follow-ups; however, endorsement of all symptom clusters remained high. Intrusions (Cluster B) were the most highly endorsed at discharge and follow-up, whereas avoidance symptoms (Cluster C) were the least highly endorsed. Differential patterns of change were observed among the 20 individual PTSD symptoms; for example, flashbacks decreased during treatment, but increased to near admission levels by 1-year postdischarge. Results suggest that intrusive symptoms may be more resistant to residential treatment for PTSD and contribute to lower likelihood of treatment success. Future work is needed to examine differential treatment response for PTSD clusters, to inform the improvement of current and creation of novel treatment interventions, and to better address intrusive symptoms to maximize PTSD treatment gains. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Fighting Noise with Noise: A Stochastic Projective Quantum Eigensolver.

In the current noisy intermediate scale quantum era of quantum computation, available hardware is severely limited by both qubit count and noise levels, precluding the application of many current hybrid quantum-classical algorithms to nontrivial quantum chemistry problems. In this paper we propose applying some of the fundamental ideas of conventional Quantum Monte Carlo algorithms─stochastic sampling of both the wave function and the Hamiltonian─to quantum algorithms in order to significantly decrease quantum resource costs. In the context of an imaginary-time propagation based projective quantum eigensolver, we present a novel approach to estimating physical observables which can lead to an order of magnitude reduction in the required sampling of the quantum state to converge the ground state energy of a system relative to current state-of-the-art eigensolvers. The method can be equally applied to excited-state calculations and, combined with stochastic approximations of the system Hamiltonian, provides a promising near-term approach to Hamiltonian simulation for general chemistry on quantum devices.

A machine learning assisted multifidelity modelling methodology to predict 3D stresses in the vicinity of design features in composite structures

Multifidelity global–local finite element (FE) analyses are typically used to predict damage initiation hotspots around repetitive design features in large composite structures, such as composite airframes. We propose the use of machine learning (ML) methods to accelerate these analyses. We demonstrate this ML assisted framework for the stress analysis of a hole in plate feature in an aerospace C-spar structure. To enable this framework, we develop the following original features: a computationally efficient sampling scheme; a work-equivalent boundary condition homogenisation scheme; a volume averaged ply-by-ply stress approach; and a sequential long-short term memory neural network reformulated from a time basis to a stacking sequence basis with further bi-directionality customisation. Overall, we show that the developed method results in high-accuracy prediction of 3D stresses, with over two orders of magnitude reduction in modelling and simulation time compared to FE analyses.

A single mesh approximation for modeling multiphase flow in heterogeneous porous media

The control volume finite element (CVFE) approach is based on the discretization of primary flow and transport unknowns on two different meshes. The element mesh, used to represent the physical properties of the medium, differs from the control volume mesh necessary to ensure a mass conservative solution. The inherent two mesh feature of the CVFE approximation introduces inconsistency in the transport solution due to the averaging of physical and computed quantities between neighboring elements in the mesh. In this work, we present a consistent approach for modeling multiphase flow and transport in heterogeneous porous media. The approach is applied in the CVFE framework by enabling the discretization of primary unknowns on a single mesh. We combine the discretization of an element-wise, discontinuous pressure approximation with a first-order, discontinuous velocity approximation to resolve the elliptic or parabolic flow problem. The effectiveness of the formulation is achieved by exploiting the same finite element mesh as the flow problem, when updating the saturation solution. This direct mapping between the flow and transport mesh is simple yet effective for establishing a consistent solution in addition to circumventing the non-physical mass leakage exhibited in the classical CVFE method. We describe the interface approximations and the discontinuous terms needed for consistent solutions. The method is well suited to model flow in complex geometrical subsurface domains and is shown to be numerically stable while providing locally and globally mass conservative solutions. We apply the approach to several domains with complex geometrical features to emphasize the superiority of the approximation over conventional methods. The analysis shows over two orders of magnitude reduction in solution error compared to the classical CVFE. The new formulation effectively captures accurate transport solutions, even in the presence of varying material properties, without the need for mesh refinement.

Ultralow-Noise MoS2/Type II Superlattice Mixed-Dimensional van der Waals Barrier Long-Wave Infrared Detector.

Low-noise, high-performance long-wave infrared detectors play a crucial role in diverse applications, including in the industrial, security, and medical fields. However, the current performance of long-wave detectors is constrained by the noise associated with narrow bandgaps. Therefore, exploring novel heterostructures for long-wavelength infrared detection is advantageous for the development of compact and high-performance infrared sensing. In this investigation, we present a MoS2/type II superlattice mixed-dimensional van der Waals barrier long-wave infrared detector (Mixed-vdWH). Through the design of the valence band barrier, substantial suppression of device dark noise is achieved, resulting in 2 orders of magnitude reduction in dark current. The device exhibits outstanding performance, with D* reaching 4 × 1010 Jones. This integration approach synergizes the distinctive properties of two-dimensional layered materials (2DLM) with the well-established processing techniques of traditional three-dimensional semiconductor materials, offering a compelling avenue for the large-scale integration of 2DLM.