High Integration Research Articles

Research on foldable two-matrix 3D braided composites: Manufacturing and bending progressive damage

Research on foldable two-matrix 3D braided composites: Manufacturing and bending progressive damage

Topologically optimized flexible tricolor-shape micro-fibre arrayed film and three-dimensional tube display concurrent magnetism, luminescence and conductive aeolotropy

From the perspective of topology design, innovative devise concepts and manufacturing technologies are of great significance for manufacturing high-performance multifunctional composites. Herein, a one-dimensional tricolor-shape micro-fibre was innovatively devised and constructed via a triaxial parallel electro-spinning. As a study case and application, the unique structured [CoFe2O4/polymethylmethacrylate (PMMA)]//[polyaniline (PANI)/PMMA]//[Eu(TTA)3phen/PMMA] magnetic-conductive-luminescent multi-functionalized tricolor-shape micro-fibre arrayed film (marked as MTMAF) were fabricated by orientational arrangement of the tricolor-shape micro-fibres. Meanwhile, magnetic-conductive-luminescent multi-functional quasi tricolor-shape micro-fibre arrayed film (marked as MQMAF) and magnetic-conductive-luminescent multi-functional tricolor-shape nano-strip arrayed film (marked as MTNAF) were also fabricated by alteration of the proportions of solvents. It is further found that MTMAF has better performances than those of MTNAF and MQMAF. The tricolor-shape micro-fibre achieves the partitioning of three separate functional partitions on the microscopic-level through the elaborate topology devise and an electrospinning technology. More importantly, since magnetic, conductive, and luminescent fillings are limited in their subareas, adverse interactions among them can be effectively avoided, resulting in superior poly-functional performances. Since the intense conductive aeolotropism and multifunctionality, MTMAF can be employed as a stable micro-circuit interconnection, offering a foundation for practical applications. Red luminescence can be used to supervise whether MTMAF properly works or not in darkness. Three-dimensional tubes are constructed via crimping the MTMAF in two various modes. The high integration of zero-dimensional nanoparticles, one-dimensional micro-construction blocks, two-dimensional films and three-dimensional tubes is achieved in one material. The construction of three-dimensional tubes achieves the transformation of materials from two-dimension to three-dimension. Furthermore, a universal technique to manufacture micro-fibre/nano-strip with three micro-subareas has been established for constructing multi-functional composites, other functional fillings also can be introduced into the tricolor-shape micro-fibre/nano-strip to achieve different multi-function.

A Kriging Surrogate Model for Ball Grid Array Electronic Packaging With Stochastic Material and Geometrical Parameters

Abstract Ball grid arrays (BGAs) offer significant advantages in the automotive industry, such as their small size and high integration density, making them a promising electronic packaging approach. However, the operating environment of automobiles is more complex compared to other applications, primarily due to vibrations generated by power engines and oscillations caused by pavement roughness. The resonant frequencies of electronic packaging structures play a crucial role in system reliability and safety. However, accurately describing the implicit relationship between system resonant frequencies and material and geometrical parameters can be challenging. A Kriging surrogate model (KSM) is proposed by the combination of the Latin Hypercube stochastic sampling with finite element computation. Four different BGA configurations are established with either the initial values in the deterministic model or the specified sampling interval ranges in the stochastic model. The results of the finite element model (FEM) for BGA electronic packaging are validated and demonstrate qualitative agreement with published literature. The impacts of material and geometrical parameters on the resonant frequencies are investigated and compared. The mean, maximum, minimum, and variance are recorded based on a large database of stochastic samples. The feasibility of KSM for the resonant frequency prediction of BGA is confirmed by its satisfactory accuracy and computational efficiency.

One-Shot Remote Integration of Macromolecular Synaptic Elements on a Chip for Ultrathin Flexible Neural Network System.

The field of biomimetic electronics that mimic synaptic functions has expanded significantly to overcome the limitations of the von Neumann bottleneck. However, the scaling down of the technology has led to an increasingly intricate manufacturing process. To address the issue, we present a one-shot integrable electropolymerization (OSIEP) method with remote controllability for the deposition of synaptic elements on a chip by exploiting bipolar electrochemistry. Condensing synthesis, deposition, and patterning into a single fabrication step was achieved by combining alternating-current voltage superimposed on direct-current voltage-bipolar electropolymerization and a specially designed dual source/drain bipolar electrodes. As a result, uniform 6 × 5 arrays of poly(3,4-ethylenedioxythiophene) (PEDOT) channels were successfully fabricated on flexible ultrathin parylene substrates in one-shot process. The channels exhibited highly uniform characteristics and were directly used as electrochemical synaptic transistor with synaptic plasticity over 100 seconds. The synaptic transistors have demonstrated promising performance in an artificial neural network (NN) simulation, achieving a high recognition accuracy of 95.20%. Additionally, the array of synaptic transistor was easily reconfigured to a multi-gate synaptic circuit to implement the principles of operant conditioning. These results provide a compelling fabrication strategy for realizing cost-effective and disposable NN systems with high integration density. This article is protected by copyright. All rights reserved.

When Young Scholars Cooperate with LLMs in Academic Tasks: The Influence of Individual Differences and Task Complexities

As a novel AI-powered conversational system, large language models (LLMs) have the potential to be used in various applications. Recent advances in LLMs like ChatGPT have made LLM-based academic tools possible. However, most of the existing studies on the adoption of LLM for academic tasks were based on theoretical or qualitative analyses, which failed to provide empirical evidence on the effects of LLMs on users’ behaviors. Additionally, although previous work has investigated users’ acceptance of conventional conversational systems, little is known about how scholars evaluate LLMs when they are used for academic tasks. Hence, we conducted an empirical field experiment to assess the performance of 48 early-stage scholars on two core academic activities (paper reading and literature reviews) under varying time constraints. Prior to the tasks, participants underwent different training programs about LLM capabilities and limitations. Then, we built a hierarchy dependency network using the Bayesian network. Statistical regression analyses were further conducted to quantify relationships among influential factors of task performance and users’ attitudes toward the LLMs. It was found that young scholars have upheld relatively high academic integrity when using LLMs for academic tasks, and user-LLM performance varied with the task type and time pressure but not with the type of training we used. Further, scholars’ traits can also affect their performance in academic tasks and attitudes towards the LLMs. This work can inspire the future development of LLM-related user training and guide the optimization of LLMs.

Robust Homochiral Polycrystalline Metal-Organic Framework Membranes for High-Performance Enantioselective Separation.

Homochiral MOF membranes offer a promising route to efficient chiral separation, but their fabrication remains challenging. Here, we report for the first time the design and preparation of homochiral polycrystalline MOF-808 membranes for the first time. The membrane exhibits a high integrity and thin membrane thickness. Achieving homochirality through chiral amino acid postsynthetic modification, MOF-808 membranes demonstrate remarkable solvent stability. Notably, they successfully separated racemic naproxen enantiomers, achieving enantiomeric excess (ee) values of up to ∼95.0%. This work paves the way for turning achiral polycrystalline MOF membranes into high-performance chiral membranes for enantioselective separation.

Highly-integrable analogue reservoir circuits based on a simple cycle architecture

Physical reservoir computing is a promising solution for accelerating artificial intelligence (AI) computations. Various physical systems that exhibit nonlinear and fading-memory properties have been proposed as physical reservoirs. Highly-integrable physical reservoirs, particularly for edge AI computing, has a strong demand. However, realizing a practical physical reservoir with high performance and integrability remains challenging. Herein, we present an analogue circuit reservoir with a simple cycle architecture suitable for complementary metal-oxide-semiconductor (CMOS) chip integration. In several benchmarks and demonstrations using synthetic and real-world data, our developed hardware prototype and its simulator exhibit a high prediction performance and sufficient memory capacity for practical applications, showing promise for future applications in highly integrated AI accelerators.

MoS2/ZnO-heterostructured optoelectronic synapse for multiwavelength optical information-based sensing, memory, and processing

The rapid development of artificial intelligence and humanoid robots requires hardware-level revolution of synapses-based bionic vision system. However, current optoelectronic synapses featuring multiwavelength sensing and multifunctional processing necessitate intricate integrations of multi-materials and floating gate configurations, which induces complex fabrication process and limited integration density. Here, we propose a novel two-terminal optoelectronic synaptic device based on MoS2/ZnO heterostructure which integrates sense and memory functions and realizes multifunctional optical information processing while circumvents the need of complex configurations. By simultaneously exploiting the photo-adsorption oxygen dissociation property of ZnO and the persistent photoconductivity effect of MoS2, the device demonstrates synaptic capability of four-color perception with a single synaptic event consuming a mere 2.55×10−9 J. Different from the traditional power-density sensitive nociceptor, for the first time photon energy-sensitive nociceptors is developed, which can mimic the process of UV irradiation to the retina leading to fear of visible light. Diverse information processing ability, such as photonic information encryption, associative learning, and logic calculation, was demonstrated in a single device, indicating a practical strategy for facile design for future high integration intensity neuromorphic devices.

Polymer-based cascaded waveguide Bragg grating for blood glucose sensing.

Waveguide Bragg grating (WBG) blood glucose sensing, as a biological sensing technology with broad application prospects, plays an important role in the fields of health management and medical treatment. In this work, a polymer-based cascaded WBG is applied to glucose detection. We investigated photonic devices with two different grating structures cascaded-a crossed grating and a bilateral grating-and analyzed the effects of the crossed grating period, bilateral grating period, and number of grating periods on the sensing performance of the glucose sensor. Finally, the spectral reflectance characteristics, response time, and sensing specificity of the cascaded WBG were evaluated. The experimental results showed that the glucose sensor has a sensitivity of 175 nm/RIU in a glucose concentration range of 0-2 mg/ml and has the advantages of high integration, a narrow bandwidth, and low cost.

Statistical Analysis of Interatomic Transfer Integrals for exploring high-mobility organic semiconductors

ABSTRACT Charge transport in organic semiconductors occurs via overlapping molecular orbitals quantified by transfer integrals. However, no statistical study of transfer integrals for a wide variety of molecules has been reported. Here we present a statistical analysis of transfer integrals for more than 27,000 organic compounds in the Cambridge Structural Database. Interatomic transfer integrals were used to identify substructures with high transfer integrals. As a result, thione and amine groups as in thiourea were found to exhibit high transfer integrals. Such compounds are considered as potential non-aromatic, water soluble organic semiconductors.

Uniaxial-Oriented Chiral Perovskite for Flexible Full-Stokes Polarimeter.

Full-Stokes polarization detection, with high integration and portability, offers an efficient path toward next-gen multi-information optoelectronic systems. Nevertheless, current techniques relying on optical filters create rigid and bulky configurations, limiting practicality. Here, we first report a flexible, filter-less full-Stokes polarimeter featuring a uniaxial-oriented chiral perovskite film. We find that, the strategic manipulation of the surfactant-mediated Marangoni effect during blade coating, is crucial for guiding an equilibrious mass transport to achieve oriented crystallization. Through this approach, the obtained uniaxial-oriented chiral perovskite films inherently possess anisotropy and chirality, and thereby with desired sensitivity to both Linearly Polarized Light (LPL) and Circularly Polarized Light (CPL) vectors. The uniaxial-oriented crystalline structure also improves photodetection, achieving a specific detectivity of 5.23 × 1013 Jones, surpassing non-oriented devices by 10x. The as-fabricated flexible polarimeters enable accurate capture of full-Stokes polarization without optical filters, exhibiting slight detection errors for the Stokes parameters: ΔS1 = 9.2%, ΔS2 = 8.6%, and ΔS3 = 6.5%, approaching the detection accuracy of optics-filter polarimeters. Our proof of concept also demonstrates applications in matrix polarization imaging. This article is protected by copyright. All rights reserved.

3DOF displacement sensor based on the self-imaging effect of optical micro-gratings

In recent years, there has been an increasing demand for a multiple degrees of freedom (DOF) measurement system with high performance and high integration. Here, we report a 3DOF displacement sensor based on the self-imaging effect of optical micro-gratings. The optical field distribution behind a micro-grating with a period of 3 µm is analyzed theoretically. The transmission properties of a double-grating structure are investigated in theory. In the experiment, 3DOF displacement measurement within a range of 1 mm is demonstrated. Using an interpolation circuit with a subdividing factor of 1000, displacement measurement with a theoretical resolution of 3 nm is realized. The experimental resolution is ∼8nm. An error within 2 µm is obtained experimentally within a range of 1 mm for 3DOF measurement. With a few optical components such as a beam splitter prism and beam expanders, the sensor shows potential in developing ultra-compact multi-DOF displacement measuring systems. Together with a nanometric resolution, the 3DOF displacement sensor has shown great potential in applications such as high-precision mechanical engineering and semiconductor processing.

Operando Building of a Superior Interface Hybrid Film Enables Chemomechanically Durable Co-Free Ni-Rich Cathodes.

The Co-free Ni-rich layered cathodes become pivotal to reduce cost and increase benefit toward next-generation Li-ion batteries yet raise a major challenge for their extremely fragile cathode-electrolyte interface (CEI) film. Herein, we report the in situ construction of the Si/B-enriched organic-inorganic hybrid CEI films on LiNi0.9Mn0.1O2 (NM91) with the assistance of tris(trimethylsilyl) borate (TMSB) additive. The hybrid film exhibits superior Young's modulus, mechanical strength, and ductility, which greatly dissipate the microstrain of Co-free Ni-rich cathodes under various states of charge with high structural integrity. Furthermore, the surface oxygen anions have been significantly stabilized by bonding with the Si and B ions of TMSB with high safety. These merits enable a durable Co-free Ni-rich layered cathode with 96.9% and 87.7% capacity retentions (versus 72.7% and 70.2% of NM91) at a high rate of 5C and a high-temperature of 55 °C after 100 cycles. In a pouch-type full cell, 88.8% of initial capacity is still maintained after cycling at 1C for 500 times, greatly expediting the development and application of Co-free Ni-rich layered cathodes.

Modeling gas flow in low-permeability formations: An efficient combination of mixed finite elements and high order time integration schemes

Numerical simulation of gas flow in low permeability formations is a challenging task due to the high nonlinearity induced by (i) the compressibility of the gas, (ii) the Klinkenberg slippage effect and (iii) the Langmuir adsorption of the gas on the pore surface. Because of these nonlinearities, modeling gas flow in low permeability formations requires a great deal of computational effort. In this work, we develop an efficient numerical model using advanced spatial and temporal discretization methods for a simultaneous solution of the coupled equations of gas flow, cubic Peng-Robinson equation of state, slippage effect and Langmuir adsorption. The spatial discretization is performed with the lumped hybrid formulation of the mixed finite element method which is well adapted for fluid flow in heterogeneous porous media. The time integration is performed with high-order methods via the method of lines (MOL) which allows large time steps and efficient solution of the nonlinear system of equations. Numerical experiments, performed for gas extraction in a heterogeneous domain, point out the high efficiency of the new model since it can be until 10 times more efficient than the classical first-order time discretization method. Results of global sensitivity analysis show that the intrinsic gas-phase permeability and the Klinkenberg factor are the most influential parameters controlling the pumping rate in the case of gas extraction in a homogeneous domain.

Aminated nanocellulose-mediated synthesis of polyaniline/nanocellulose hybrid materials for sustainable conductive and supercapacitors nanopapers

Diamine-functionalized cellulose nanocrystals (DamCNCs) prepared by periodate oxidation and reductive amination were used as a scaffold for the in-situ oxidative polymerization of polyaniline (PANI). Unlike unmodified CNCs, the hybrid PANI/DamCNC particles formed a stable colloidal suspension over a large pH domain, PANI particles having nucleated and grown from the nanocrystals. The hybridization of PANI was validated by transmission electron microscopy images, along with Fourier-transform infrared, Raman, and UV–Vis spectra. By taking advantage of the colloidal stability of the PANI/DamCNC nanohybrids, flexible and freestanding thin nanopapers were prepared, with different contents in PANI/DamCNCs, using cationic or anionic cellulose nanofibrils (CCNFs or ACNFs, respectively). Conductive nanopapers were obtained by mixing CCNFs with PANI/DamCNCs at a content higher than 20 wt%, exhibiting high flexibility, mechanical integrity, transparency, and stability over time. This work proposes a simple process to fabricate a novel class of biobased conductive hybrid nanofiller based on PANI grafted on DamCNCs, stable in water, that may be used as an additive in nanocellulose suspensions to produce green flexible thin nanopapers, with potential use in different types of electronic devices such as electronic displays, smart packaging, or paper-based supercapacitors for energy storage.

Nectar and floral morphology differ in evolutionary potential in novel pollination environments.

Plants can evolve rapidly after pollinator changes, but the response of different floral traits to novel selection can vary. Floral morphology is often expected to show high integration to maintain pollination accuracy, while nectar traits can be more environmentally sensitive. The relative role of genetic correlations and phenotypic plasticity (PP) in floral evolution remains unclear, particularly for nectar traits, and can be studied in the context of recent pollinator changes. Digitalis purpurea shows rapid recent evolution of corolla morphology but not nectar traits following a range expansion with hummingbirds added as pollinators. We use this species to compare PP, heritability, evolvability and integration of floral morphology and nectar in a common garden. Morphological traits showed higher heritability than nectar traits, and the proximal section of the corolla, which regulates access to nectar and underwent rapid change in introduced populations, presented lower integration than the rest of the floral phenotype. Nectar was more plastic than morphology, driven by highly plastic sugar concentration. Nectar production rate showed high potential to respond to selection. These results explain the differential rapid evolution of floral traits previously observed in this species and show how intrafloral modularity determines variable evolutionary potential in morphological and nectar traits.

A blockchain based federated deep learning model for secured data transmission in healthcare Iot networks

The wide use of sensors in healthcare applications has made it necessary to have secure communication in healthcare Internet of Things (IoT) networks. The sensor data is sensitive, and can contain extremely confidential information such as medical diagnosis, clinical records, vital signs and health data of patients. The emergence of blockchain as a technology ensures consensus and trust among systems, and is now considered to be a new trend used to achieve high scalability, data integrity and privacy. Federated learning is a new technology based on distributed learning that exploits the concept of trust. In federated learning, each user builds an individual distributed model to help a central server that is accessible only to a trusted user group. This paper harnesses the potential of these approaches and proposes an attack detection model to discern normal user behaviours from that of adversaries in an IoT network. This model is called the Blockchain enabled Federated Learning model for secured communication in healthcare IoT (BFL-hIoT), to secure data in healthcare IoT networks. This model is trained and tested on a standard dataset and demonstrates the highest classification accuracy of 97.16 % for normal, 0.9546 for backdoors, 0.9618 for XSS etc., outperforming other blockchain and deep learning models.

Gate-Tunable Positive and Negative Photoconductance in Near-Infrared Organic Heterostructures for In-Sensor Computing.

The rapid growth of sensor data in the artificial intelligence often causes significant reductions in processing speed and power efficiency. Addressing this challenge, in-sensor computing is introduced as an advanced sensor architecture that simultaneously senses, memorizes, and processes images at the sensor level. However, this is rarely reported for organic semiconductors that possess inherent flexibility and tunable bandgap. Herein, an organic heterostructure that exhibits a robust photoresponse to near-infrared (NIR) light is introduced, making it ideal for in-sensor computing applications. This heterostructure, consisting of partially overlapping p-type and n-type organic thin films, is compatible with conventional photolithography techniques, allowing for high integration density of up to 520 devices cm-2 with a 5µm channel length. Importantly, by modulating gate voltage, both positive and negative photoresponses to NIR light (1050nm) are attained, which establishes a linear correlation between responsivity and gate voltage and consequently enables real-time matrix multiplication within the sensor. As a result, this organic heterostructure facilitates efficient and precise NIR in-sensor computing, including image processing and nondestructive reading and classification, achieving a recognition accuracy of 97.06%. This work serves as a foundation for the development of reconfigurable and multifunctional NIR neuromorphic vision systems.

42 Group sow housing considerations for improved survival and productivity

Abstract Group sow housing considerations for improved survival and productivity. The Australian pork industry decided in 2010 to voluntarily phase out stall housing for pregnant sows by 2017. The change was supported by extensive R&D by the Pork CRC for High Integrity Australian Pork and the time line was brought forward by two major retailers in Australia. For 85 to 90% of producers the transition was complete by 2019-2020 and sows were grouped at weaning or straight after mating. I reviewed the pertinent literature, interviewed many producers on what is required to make group housing successful for the sow and the producer and looked at trend from an Australian bench making project in some aspects of reproduction and sow mortality from 2006 to 2020. The research showed sows adapt to grouping and exhibit reduced aggressive behaviors, injuries and plasma indicators of stress within 4 to 5 d after mixing. During this period, it was all about space at mixing, grouping sows based on size/parity, ensuring they all receive adequate feed and familiarization with group housing by the sow and staff. Producers said it is all about ensuring sows are grouped on size/parity, feeding with many using ad libitum feeding for the week after mixing, space with a preference between 1.8 and 2.2 m2, flooring (slats preferred) and minimizing mixing events. Producers were split on the use of drop feeding and electronic sow feeders with opinions very divided. For drop feeding the preferred housing system comprised full length feeding stalls without a back gate. All producers said they would not go back to stalls. Most producers experienced a decline in farrowing rate and increased lameness during the transition. However, reproduction improved over time and sow mortality decreased. If the top 4 to 5 factors affecting aggressiveness and overall welfare are followed, group housing sows improves their welfare and does not reduce their reproductive performance or longevity. Detection of estrus can be more difficult in groups and a number of Australian producers have implemented the use of satiety blocks during the first 2 and last 2 wk of gestation to further improve welfare and meet retailer requirements. Mating in groups (not stalls) has also been reported to improve reproduction.

The axially-loaded behaviours of Schwarz Primitive (SP)-based structures: An experimental and DEM study

This study delves into the axial responses of Schwarz Primitive (SP) structures. Emphasising on bearing capacity, force distribution, cracking phenomena, load-displacement curve and energy absorption. Discrete element method (DEM) is adopted to analyse the axial load-bearing behaviour and fracture mechanics of Main SP and Secondary SP structures under various unit cell configurations after validated by experimental tests. The results indicates that despite sharing the same 1/8th cell structure, the axially-loaded behaviours of the Main SP and Secondary SP structures are not identical, particularly in scenarios involving a large unit cell size and a small number of unit cells. The Main SP structures display an axial load-bearing behaviour that is largely unaffected by variations in the number of unit cells along the x and y axes, while Secondary SP structures show a more pronounced improvement in average strength and energy absorption capacity when the number of unit cells increases. Main SP structures offer superior axial load-bearing capabilities and energy absorption efficiency, which is a significant consideration for their application in scenarios demanding high structural integrity. This distinction underlines the importance of tailored design and selection of SP configurations based on specific engineering requirements.