Solution Process Research Articles

Three Dimensional Microwave Data Inversion in Feature Space for Stroke Imaging.

Microwave imaging is a promising method for early diagnosing and monitoring brain strokes. It is portable, non-invasive, and safe to the human body. Conventional techniques solve for unknown electrical properties represented as pixels or voxels, but often result in inadequate structural information and high computational costs. We propose to reconstruct the three dimensional (3D) electrical properties of the human brain in a feature space, where the unknowns are latent codes of a variational autoencoder (VAE). The decoder of the VAE, with prior knowledge of the brain, acts as a module of data inversion. The codes in the feature space are optimized by minimizing the misfit between measured and simulated data. A dataset of 3D heads characterized by permittivity and conductivity is constructed to train the VAE. Numerical examples show that our method increases structural similarity by 14% and speeds up the solution process by over 3 orders of magnitude using only 4.8% number of the unknowns compared to the voxel-based method. This high-resolution imaging of electrical properties leads to more accurate stroke diagnosis and offers new insights into the study of the human brain.

Manufacturing profiled conical cylinder by a semi-closed isothermal precision die forging technology

An improved semi-closed isothermal precision dies forging process has been used to produce successfully precision profiled conical cylinder forging. The semi-closed die forging significantly improved the forming quality and deformation homogeneity of profiled forgings, and greatly reduced die forging force by isothermal forging with three-stage variable speed. The static recrystallization during solution process was inhibited, and fine and even dynamic recrystallized grains and abundant sub-grains were obtained. In addition, the difference of the microstructure at each position was small and the distribution of grains and second phase particles was uniform. This significantly improved the mechanical properties and homogeneity of forgings, and the average values of tensile strength, yield strength and elongation reached 480.9 MPa, 387.8 MPa and 8.75%, respectively.

Unraveling the Influence of Solvent on Side Reactions between Formamidinium Lead Triiodide and Methylammonium Cations.

Formamidinium lead triiodide (FAPbI3) perovskite thin films are commonly deposited through a solution process, often incorporating a specific amount of methylammonium halide to stabilize the α-phase or enhance their crystallinity. The precursor solution for such coatings significantly influences the fabrication of perovskite solar cells (PSCs), involving time-dependent aging and byproduct formation. The chemical principle underlying this behavior is believed to be related to the deprotonation of methylamine cations (MA+) and subsequent chemical reactions with FA+ to generate N-methylformamidinium. Nevertheless, the role of the solvent in the side reactions between these organic cations remains unclear. This work systematically investigates the reaction reactivity in three protic solvents and three aprotic solvents. We uncover the hidden role of dimethylamine from the hydrolysis products of N,N-dimethylformamide, promoting the reaction between FA+ and MA+. Additionally, we elucidate the impact of environmental factors, such as water and oxygen, in stabilizing precursor solutions. This work establishes a basic concept and scientific direction for rationalizing high-efficiency, reproducible, and long-term-stable PSCs.

Plasma–ionic liquid-assisted CO2 capture and conversion: A novel technology

The present study focused on CO2 capture, storage, and conversion through the innovative integration of plasma–ionic liquid (IL) technology. For the first time, we employed plasma-IL technology to confront climate change challenges. We utilized 1-Butyl-3-methylimidazolium chloride IL to capture and store CO2 under atmospheric pressure, and subsequently employed plasma to induce the transformation of IL-captured CO2 into CO. Furthermore, we performed computer simulations to enhance our understanding of the CO2 and CO capture processes of water and IL solutions. This comprehensive approach provides valuable insights into the potential of plasma–IL technology as a viable solution for climate change.

A Study of Promising Carbon Sorbents Prepared via High-Temperature Activation in Purification Processes of Aqueous Solutions from Dyes

A Study of Promising Carbon Sorbents Prepared via High-Temperature Activation in Purification Processes of Aqueous Solutions from Dyes

Visual Exploratory Analysis for Designing Large-Scale Network-on-Chip Architectures: A Domain Expert-Led Design Study.

Visualization design studies bring together visualization researchers and domain experts to address yet unsolved data analysis challenges stemming from the needs of the domain experts. Typically, the visualization researchers lead the design study process and implementation of any visualization solutions. This setup leverages the visualization researchers' knowledge of methodology, design, and programming, but the availability to synchronize with the domain experts can hamper the design process. We consider an alternative setup where the domain experts take the lead in the design study, supported by the visualization experts. In this study, the domain experts are computer architecture experts who simulate and analyze novel computer chip designs. These chips rely on a Network-on-Chip (NOC) to connect components. The experts want to understand how the chip designs perform and what in the design led to their performance. To aid this analysis, we develop Vis4Mesh, a visualization system that provides spatial, temporal, and architectural context to simulated NOC behavior. Integration with an existing computer architecture visualization tool enables architects to perform deep-dives into specific architecture component behavior. We validate Vis4Mesh through a case study and a user study with computer architecture researchers. We reflect on our design and process, discussing advantages, disadvantages, and guidance for engaging in a domain expert-led design studies.

Study on Optimization of Deep Purification Process Design of Zinc Oxygen Pressure Acid Leaching Solution

According to the characteristics of high impurity content and complex composition of oxygen pressure leaching (OPL) solution of zinc sulfide concentrate, combined with the quality requirements of large plate electrowinning and automatic plate stripping, the advanced purification process of solution was designed. Through the deep purification process consisting of neutralization indium precipitation and low iron purification, high temperature antimony salt nickel and cobalt removal, copper slag chlorine removal, low temperature zinc powder replacement copper and cadmium removal, fine purification, calcium and magnesium removal, the contents of harmful impurities such as iron, indium, copper, cadmium, nickel, cobalt, fluorine and chlorine in the solution are strictly controlled to ensure that the quality of the deeply purified zinc sulfate solution is qualified and can meet the needs of continuous and stable production. The energy-saving effect of advanced purification process is obvious, and the average DC power consumption per ton of electric zinc is 2880kWh, reaching the advanced level of the same industry in China. The good effect of advanced purification process ensures the successful application of OPL and large plate zinc electrowinning, and improves the technology and equipment level of zinc smelting industry, which has important popularization and application value.

Controlled Reflected McKean–Vlasov SDEs and Neumann Problem for Backward SPDEs

This paper is concerned with the stochastic optimal control problem of a 1-dimensional McKean–Vlasov stochastic differential equation (SDE) with reflection, of which the drift coefficient and diffusion coefficient can be both dependent on the state of the solution process along with its law and control. One backward stochastic partial differential equation (BSPDE) with the Neumann boundary condition can represent the value function of this control problem. Existence and uniqueness of the solution to the above equation are obtained. Finally, the optimal feedback control can be constructed by the BSPDE.

Analysis of electrical and hysteresis characteristics of flexible OTFT using solution-processable DPP-DTT polymer and Parylene-C

Organic thin-film transistors (OTFTs) fabricated on Parylene-C substrates have the advantages of a simple process, low cost, and flexible characteristics. This study introduces the manufacturing method and electrical characteristics of an OTFT using organic materials as the substrate, gate dielectric, and channel material. PDPP2T-TT-OD(DPP-DTT) is used as the channel material, which is a highly mobile p-type polymer with good air stability. The proposed OTFT device has flexible characteristics because it is fabricated on a Parylene-C substrate and can be used even in a curved state. Furthermore, the manufacturing process was largely achieved via a simple, low-cost solution process using spin-coating and photolithography with a photo-curable material. Under flat conditions, the threshold voltage (VTH) is approximately –3 V, the average ION/IOFF ratio is approximately 105, and the mobility is 0.84 cm2/Vs.

Development of a hybrid bio-purification process of lactic acid solutions employing an engineered E. coli strain in a membrane bioreactor

BackgroundA potential alternative to lactic acid production through sugar fermentation is its recovery from grass silage leachate. The separation and purification of lactic acid from fermentation broths remain a key issue, as it amounts to up to 80% of its industrial production cost. In this study, a genetically engineered E. coli strain (A1:ldhA), that cannot catabolize lactic acid, has been used to selectively remove impurities from a synthetic medium comprising typical components (i.e., glucose and acetic acid) of green grass silage leachate. A systematic approach has been followed to provide a proof-of-concept for a bio-purification process of lactic acid solutions in a membrane bioreactor operating in semi-continuous mode.ResultsThe synthetic medium composition was initially optimized in shake-flasks experiments, followed by scale-up in bench-scale bioreactor. Complete (i.e., 100%) and 60.4% removal for glucose and acetic acid, respectively, has been achieved in batch bioreactor experiments with a synthetic medium comprising 0.5 g/L glucose and 0.5 g/L acetic acid as carbon sources, and 10 g/L lactic acid; no lactic acid catabolism was observed in all batch fermentation tests. Afterwards, a hybrid biotechnological process combining semi-continuous bioreactor fermentation and ultrafiltration membrane separation (membrane bioreactor) was applied to in-situ separate purified medium from the active cells. The process was assessed under different semi-continuous operating conditions, resulting in a bacteria-free effluent and 100% glucose and acetic acid depletion, with no lactic acid catabolism, thus increasing the purity of the synthetic lactic acid solution.ConclusionsThe study clearly demonstrated that a bio-purification process for lactic acid employing the engineered E. coli strain cultivated in a membrane bioreactor is a technically feasible concept, paving the way for further technological advancement.

SOLVING STOCHASTIC TRANSPORTATION ELECTRICITY PROBLEM WITH FUZZY INFORMATION ON PROBABILITY DISTRIBUTION USING MATLAB PROGRAM

This study focuses on MATLAB code programs of the entire stages of solving Stochastic Transportation Linear Programming Problems with Fuzzy Uncertainty Information on Probability Distribution Space (STLPPFI) with its algorithm outlines. A MATLAB code program of STLPPFI problem solver with algorithm outlines are proposed to solve STLPPFI model problems, and it utilizes many concepts as Alpha-Cut technique, Truth Degrees technique, Linear Fuzzy Membership Function (LFMF), Trapezoidal Fuzzy Number , Triangular Fuzzy Number , Linear Fuzzy Ranking Function (LFRF), Expectation Weighted Summation technique (EWS) and analyzing cases via second condition test of alpha-cut technique. The STLPPFI problem solver is utlized to convert STLPPFI into its corresponding equivalent Deterministic Transportation Linear Programming Problem (DTLPP) via defuzzifying from fuzziness on probability distribution space and derandomization randomness of problem formulation respectively. In addition, Dual-Simplex algorithm method with Vogel Approximation Algorithm Method (VAM) are used to obtain optimal solution from DTLPP. All MATLAB code programs with their proposed algorithm outlines are new except Dual-Simplex and VAM. The MATLAB code program of STLPPFI problem solver are more efficient along with a numerical example on electricity field illustrating practicability of this proposed MATLAB code program with its algorithm. Finally, the solution procedure illustrates the MATLAB code program of the proposed method is practical and applicable in the fields of energy and industry as it facilitates the method of transforming the energy at the lowest cost, least time running and is commercially applicable. Comparative comments are provided between Dual-Simplex and VAM in solution process.

FGeo-SSS: A Search-Based Symbolic Solver for Human-like Automated Geometric Reasoning

Geometric problem solving (GPS) has always been a long-standing challenge in the fields of automated reasoning. Its problem representation and solution process embody rich symmetry. This paper is the second in a series of our works. Based on the Geometry Formalization Theory and the FormalGeo geometric formal system, we have developed the Formal Geometric Problem Solver (FGPS) in Python 3.10, which can serve as an interactive assistant or as an automated problem solver. FGPS is capable of executing geometric predicate logic and performing relational reasoning and algebraic computation, ultimately achieving readable, traceable, and verifiable automated solutions for geometric problems. We observed that symmetry phenomena exist at various levels within FGPS and utilized these symmetries to further refine the system’s design. FGPS employs symbols to represent geometric shapes and transforms various geometric patterns into a set of symbolic operation rules. This maintains symmetry in basic transformations, shape constructions, and the application of theorems. Moreover, we also have annotated the formalgeo7k dataset, which contains 6981 geometry problems with detailed formal language descriptions and solutions. Experiments on formalgeo7k validate the correctness and utility of the FGPS. The forward search method with random strategy achieved a 39.71% problem-solving success rate.

Penggabungan Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> dalam Matriks Poli (Metil Metakrilat) untuk Aplikasi Memori Tidak Meruap

MXenes, with their unique surface properties and 2D structure, have demonstrated promising potential in electronic devices, particularly in memory storage. This study explored the potential of 2D Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> for the nonvolatile memory (NVM) application. The simple solution process routes were used to fabricate the two-terminal bistable switching devices. The silver nanowires/nanocomposite/ITO structure was deposited on a glass substrate using spin coating and spray coating techniques. The Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> MXene flakes were incorporated into a poly(methyl methacrylate) (PMMA) polymer host to form the nanocomposite and act as a charge-trapping layer. Meanwhile, PMMA acts as a dielectric layer. The measured current-voltage data showed a bistable current behavior with the presence of a memory window. The fabricated NVM memory devices were reprogrammable when the endurance test was performed and stable up to 1×104 s cycles with a distinct ON/OFF ratio of 103. The conduction mechanisms were identified using the curve-fitting method with double log plots of current-voltage (I-V) data. Based on the obtained I-V characteristics, various conduction mechanisms, especially Schottky and Poole-Frenkel emission, trapped charge limiting current, and space charge limited current, were proposed to be responsible for the bistable switching behavior. Thus, the results of this study provide an experimental basis for using MXene in non-volatile memory applications.

High-efficiency recovery of valuable metals from spent lithium-ion batteries: Optimization of SO2 pressure leaching and selective extraction of trace impurities

The recovery of valuable metals from spent lithium-ion batteries (LIBs) is crucial for environmental protection and resource optimization. In the traditional recovery process of spent LIBs, the leaching of high-valence metals has the problems of high cost and limited reagent utilization, and some valuable metals are lost in the subsequent purification process of the leaching solution. To reduce the cost of reagents, this study proposes the use of low-cost SO2 as a reagent combined with pressure leaching to efficiently recover high-valence metals from delithiated materials of spent LIBs, while selective solvent extraction is used to remove trace impurities in the leaching solution to avoid the loss of valuable metals. Experimental results demonstrated that by optimizing the conditions to 0.25 MPa SO2 partial pressure and 60 min reaction time at 70 °C, the leaching efficiencies for Ni, Co, and Mn reached 99.6%, 99.3%, and 99.6%, respectively. The kinetic study indicated that the leaching process was diffusion-controlled. Furthermore, the delithiated materials were used to completely utilize the residual SO2 in the solution to obtain a high concentration Ni–Co–Mn rich solution. Subsequently, Fe and Al impurities were deeply removed through a synergistic extraction of Di-2-ethylhexyl phosphoric acid (D2EHPA) and tributyl phosphate (TBP) without loss of valuable metals, achieving a high-purity Ni–Co–Mn solution. The process developed based on this work has the characteristics of environmental friendliness, high valuable metal recovery, and high product purity, providing a reference technical method for the synergistic treatment of waste SO2 flue gas with spent LIBs and the deep purification of impurities in spent LIBs.

Realizing Phase‐Pure (PEA)2FAPb2I7 Perovskite Films by Inhibiting 3D Phase Formation

Abstract2D Ruddlesden–Popper (RP) layered metal‐halide perovskites have garnered significant interest due to their unique photoelectric properties and excellent stability. However, 2D perovskite films prepared via solution process generally exhibit multi‐quantum well structure with random well width distribution, which significantly impedes the carrier transportation. Herein, the synthesis of phase‐pure 2D (PEA)2FAPb2I7 (PEA = C8H11N, FA = CH4N2) perovskite thin films is reported in ambient environment achieved by suppressing the formation of the 3D perovskite phase. First, incorporation of MACl additive can effectively regulate the intermediate during crystallization, facilitating the formation of a metastable 3D MAxFA1‐xPbIyCl3‐y phase. Second, precise control of environmental humidity is employed to further inhibit the formation of α‐FAPbI3 phase. As a result, the perovskite intermediate composed of predominantly metastable 3D phase and 2D n = 2 phase is achieved, which is eventually transformed into 2D n = 2 perovskite during annealing, leading to markedly enhanced phase purity. Photoconductive‐type photodetectors based on the phase‐pure 2D RP perovskite films are fabricated, demonstrating a high detectivity of over 9.4 × 1012 Jones due to the improved carrier transportation. This study provides a comprehensive insight into the crystallization process of phase‐pure 2D perovskites.

Mixed localized waves in the coupled nonlinear Schrödinger equation with higher-order effects

In this work, the coupled nonlinear Schrödinger equation with higher-order effects is studied with the aid of Darboux transformation and an asymptotic analysis. We report mixed localized waves, rogue wave coexisting with breathers in the system. Under certain constraints, the structures and evolutionary processes of solutions have been influenced. For example, The phase, amplitude, and propagating direction of mixed localized waves change when rogue wave collides with breathers. Moreover, the localized waves characteristics together with collision dynamic behaviors of these explicit rogue wave and breathers are exhibited graphically and discussed in detail. These novel results may be meaningful to study integrable systems better.

BERPIKIR REFLEKTIF SISWA DALAM PEMECAHAN MASALAH MATEMATIS DITINJAU DARI GAYA KOGNITIF

This research aims to analyze the ability of reflective thinking in mathematical problem solving among 9th-grade students of SMP Negeri 3 Tanjung, focusing on curved surface solids from the perspective of cognitive styles. The sample selection was carried out using a purposive sampling technique, resulting in 6 participants, consisting of 3 students with a field-dependent cognitive style and 3 students with a field-independent cognitive style. Data collection techniques employed in this study include the GEFT test, a test of reflective thinking ability in mathematical problem solving, interviews, and documentation. Data analysis was conducted using the Miles and Huberman model, involving data reduction, data presentation, and conclusion. The results of this study indicate that among the four indicators of reflective thinking ability in mathematical problem solving, specifically in the elaborating stage, students with a field-dependent cognitive style have not fully grasped the ability to plan and execute solutions. They struggle to comprehend more complex problems presented in narrative form, leading to difficulties understanding the concepts and executing the solution process. Conversely, students with a field-independent cognitive style have successfully fulfilled all four indicators across the three stages of reflective thinking ability. They tackle problems methodically and accurately, following planned steps following pre-established concepts.

An Artificial Neural Network Based on Oxide Synaptic Transistor for Accurate and Robust Image Recognition.

Synaptic transistors with low-temperature, solution-processed dielectric films have demonstrated programmable conductance, and therefore potential applications in hardware artificial neural networks for recognizing noisy images. Here, we engineered AlOx/InOx synaptic transistors via a solution process to instantiate neural networks. The transistors show long-term potentiation under appropriate gate voltage pulses. The artificial neural network, consisting of one input layer and one output layer, was constructed using 9 × 3 synaptic transistors. By programming the calculated weight, the hardware network can recognize 3 × 3 pixel images of characters z, v and n with a high accuracy of 85%, even with 40% noise. This work demonstrates that metal-oxide transistors, which exhibit significant long-term potentiation of conductance, can be used for the accurate recognition of noisy images.

Aqueous solution processed transition-metal-doped ZnO as electron injection layers for efficient inverted organic light emitting diodes

Zinc oxide (ZnO) has attracted lots of attention to be used as interfacial materials in organic optoelectronic devices owing to its attractive properties. In this work, a series of transition-metal-doped ZnO thin films were prepared by using a facile aqueous solution process, thereafter these films were employed as electron injection layers (EILs) combined with the tris-(8-hydroxyquinoline) aluminum (Alq3) emitting layer to construct the inverted organic light-emitting diodes (IOLEDs). The transition-metal-doped ZnO EIL-based IOLEDs demonstrate markedly improved device performance compared to the reference neat ZnO EIL-based IOLED. However, different transition-metal ions have much different doping effect on the device performance. CoCl2 doped ZnO EIL based IOLED device possesss an optimal current efficiency of 5.52 cd A−1, which is increased about 40% compared to the device with the neat ZnO as EIL. The enhancement might be attributed to the increased electron mobility and favorable interfacial energy level alignment of the transition-metal doped ZnO EIL for more efficient electron injection. Our findings may provide a promising strategy to improve the electron injection properties of ZnO film in the OLED devices.

Optimal sizing of hybrid renewable energy systems using quasi-optimal control

This paper addresses the critical challenge of sizing hybrid renewable energy systems over their lifespan while accounting for uncertainties in energy sources and load demands. By leveraging stochastic programming, we introduce a novel modeling technique that ensures robust optimization without compromising numerical tractability. Unlike conventional methods, which determine system parameters for the entire project duration upfront, our approach enables annual adjustments to the renewable components’ sizing. This dynamic strategy alleviates early-stage under-utilization, aligning system capacity with evolving demand patterns. Central to our approach is the reformulation of the two-stage stochastic program as a quasi-optimal control. This reduces the number of optimization variables significantly, simplifying the solution process. Moreover, thousands of constraints are replaced with a system of differential equations, enhancing computational efficiency. By minimizing capital costs and dynamic operating expenses, we achieve an optimal system size. Through a real-world application in a rural area of South Africa, we demonstrate the effectiveness of our approach. The results showed a remarkable improvement in problem-solving efficiency, reduced under-utilization, and heightened adaptability to unpredictable weather conditions. This innovative framework represents a substantial leap forward in hybrid renewable energy systems design, offering a more agile and efficient solution for sustainable energy generation.