Manufacturing Process Research Articles

A new protein source for pet food: cultivated meat

Cultivated meat is an alternative protein source developed to address the sustainability, public health and animal welfare concerns of conventional meat production. Hundreds of startups and academic institutions worldwide are working to make cultivated meat a cost-effective protein source for humans. However, cultivated meat could also be used to feed dogs and cats, contributing to solving the meat supply issues that the growing pet food market has been facing in recent years. The advantages of using cultivated meat as a protein source for pets would include a reduction of the environmental impact of pets’ diets, decreased farm animal suffering and several benefits in the One Health framework, as cultivated meat-based pet food would significantly decrease the risk of spreading food safety pathogens, zoonotic diseases and resistant bacteria. The antibiotic-free manufacturing process and the aseptic conditions the cells require to grow in the bioreactors lead to these public health advantages. However, cultivated meat has never been produced at scale for human or pet consumption. Several technical challenges need to be overcome to make cultivated meat-based pet food prices accessible to consumers. As a novel ingredient, there is also no evidence of the effect of feeding cultivated meat to dogs and cats. In principle, cultivated meat can be both safe to be consumed long-term and nutritionally adequate – and with several possibilities for nutritional enhancement, potentially even superior to its conventional counterpart. However, the safety and nutritional soundness of cultivated meat-based products must be demonstrated by manufacturers to gain regulatory approval and favour consumer adoption. Veterinarians, veterinary nurses and technicians will play a critical role in the development of this new ingredient in many aspects, including product development, assessing safety and nutrition, conducting research and informing consumers. This review summarises the benefits and challenges of using cultivated meat as a pet food ingredient.

On-line recognition of mixture control chart patterns using hybrid CNN and LSTM for auto-correlated processes

Statistical process control (SPC), designed to detect and identify process disturbances, is an effective quality control method for ensuring process stability. Owing to the growing automation of the industry, the manufacturing process can be autocorrelated. Engineer process control (EPC) is typically used to address autocorrelation. However, process disturbances can be offset by feedback compensation, making control chart patterns (CCPs) difficult to identify. Most studies on control chart pattern recognition (CCPR) techniques are based on a single abnormal control chart pattern (CCP). However, a mixture of CCPs can occur during real-world manufacturing processes. With the development of intelligent manufacturing systems, early detection of abnormal concurrent CCPs has become an important issue. In this study, a hybrid model combining a convolutional neural network (CNN) and long short-term memory (LSTM) in an online detection system was used to recognize the concurrent CCPR problem in SPC-EPC processes. The results showed that the average accuracy of the deep learning CNN-LSTM method was 99.83%, which was significantly better than that of the machine learning method. In addition, the running time of the CNN-LSTM model was shortened. In a comparison of online monitoring between the deep learning method and the machine learning method, the CNN-LSTM model for an online monitoring system identified abnormal concurrent patterns faster. Therefore, the proposed CNN-LSTM online monitoring scheme can be applied confidently and successfully to identify mixture CCPs in an SPC-EPC process.

Model-based dimensional NDE from few X-ray radiographs: Application to the evaluation of wall thickness in metallic turbine blades

The extraction of 3D dimensional measurements based on a limited number of 2D X-ray radiographs of a part would offer a significant speed-up of quality control procedures in industry. However, there are challenges with respect to both measurements and uncertainties. This work addresses these challenges by creating an estimated numerical model of the imaged part on which dimensional measurements can be made. The numerical model is chosen as a parametric deformable model that encodes the expected shape variability of the parts resulting from the manufacturing process. The parameters and uncertainties of the numerical model of the imaged part are estimated by the registration of the computed projections of the model and the observed radiographs without the need of any segmentation. The registration requires the model, the initial parameters, and the observed radiographs. The proposed approach is applied to the inspection of turbine blades manufactured by investment casting, and in particular to the measurement of their wall thickness, which is a critical control. The deformable model consists in partitioning the inner ceramic core into multiple subparts, which may undergo a rigid body motion with respect to the master die. Wall thickness measurements are determined from the estimation of these rigid body motions. To assess the reliability of the proposed procedure, a repeatability study is performed. In addition, wall thickness measurements were compared to corresponding measurements from the surface of the metal boundary obtained by X-ray computed tomography. This surface was determined from a reconstructed tomogram using commercial software. Both analyses show that such measurements are reliable and efficient. Furthermore, residual differences between captured and computed projections reveal localized shape deviations from the CAD model, meaning that despite localized model errors, the approach is operable.

The effects of joint process parameters of two-step manufacturing processes on the mechanical performance of biocomposites using Taguchi and multiple regression techniques

This study evaluates the influence of joint parameters of extrusion (extrusion profile temperature) and injection molding (barrel profile temperature and mold temperature) manufacturing processes on the mechanical performance of biocomposite materials via the Taguchi and multiple regression techniques. Statistical analysis of variance (ANOVA) was performed to determine the most influential controllable factors for the individual responses. The results of the study revealed that the mechanical properties of the biocomposites are affected by the joint parameters of the two-step manufacturing techniques. This study will help in the process design of biocomposites with improved mechanical performance.

Enhanced catalytic performance of methanol-tolerant Rhizopus stolonifera immobilized on polyurethane foam with hydrophobic coating for biodiesel production

The limited methanol tolerance and glycerol adsorption tendency of whole-cell catalysts are the main factors contributing to the extended catalytic cycle and limited catalyst reusability in biodiesel preparation. In this study, a 7.5 % methanol-tolerant Rhizopus stolonifera mutant (MTS2) was developed through the atmospheric and room temperature plasma (ARTP), exhibiting a 1.5-fold increase in methanol tolerance compared with the wild type strain (WT-RS), along with a 93.5 % increase in lipases activity. Polyurethane foam PF3 with an average pore size of 0.15 mm and 90 A rigidity is optimal for MTS2 immobilization (MTS2 @PF3), enabling its application in continuous processing for industrial applications. Utilizing soybean oil as a substrate, the catalyst MTS2 @PF3 produced 95.5 % of fatty acid methyl esters (FAME) in 36 hours under optimal conditions (30°C, 180 r/min, catalyst dosage of 15 % g/g oil, 30 % water content, and methanol addition in Scheme 3), achieving over a 50 % reduction in reaction time compared with WT-RS@PF3. To address limitations in catalyst reusability due to glycerol adsorption, various modifiers, including rosin-based modifier (RM), amino silicone oil (ASO), graphene (GRA), betaine and Tween 80 were evaluated. The glycerol adsorption rates experienced substantial reductions (39.3 % with RM and 85.6 % with betaine), and the catalysts maintained above 60 % FAME yield even after 8 reaction cycles. The combination of enhanced methanol tolerance, lipase activity, and reduced glycerol adsorption contribute to enhanced catalytic efficiency and reusability, which can reduce production costs for biodiesel manufacturing. The composite of these attributes makes MTS2 @RM1-PF3 and Betaine-MTS2 @PF3 as promising candidate for industrial biodiesel production, addressing previous limitations in catalyst performance and sustainability. The developed immobilized whole-cell catalysts exhibit promising potential for more sustainable and cost-effective processes in biodiesel manufacturing.

Numerical study of entropy production and EMHD effects in a peristaltic motion of Prandtl fluid with solid particles and porous medium

Particulate-fluid flow involving chemical reactions plays a crucial role in pharmaceutical manufacturing, catalytic converters, and combustion processes. This research focuses on the analysis of mass and thermal transfer, highlighting the influence of electroosmosis and magnetic forces on the flow of Prandtl fluid through a peristaltic porous micro-channel. In addition, the multiphase flow attitude, affected by chemical reactions, is extensively examined. The flow model is formulated by utilizing the lubrication theory estimation, integrating lengthy-wavelength and creeping flow approximation to simplify the considered problem. To further simplify the problem, Debye linearization is used, resulting in a set of two ordinary differential equations. The outcomes indicate that velocity drops with rising magnetic field, while it enhances with the Helmholtz-Smoluchowski velocity coefficient. Furthermore, thermal distribution increases with greater concentrations of solid fragments and greater magnetic field. These findings provide valuable insights into optimizing mass and thermal conveyance in peristaltic problems, with potential appliances spanning numerous industrial and biomedical areas.

Approach to Design Sustainable Alkali-Activated Slag Recycled Aggregate Concrete: Mechanical and Microstructural Characterization

There is a steep increase in demand for concrete as the need for infrastructure is increasing with a rapid increase in urbanization. Consequently, there has been a surging demand for cement across the globe. By using alkaline concrete activated with ground granulated blast furnace slag (GGBS), cement usage can be eliminated in concrete, which addresses the issue of CO2 emissions concerned with the cement manufacturing process and promotes the use of industrial by-products as sustainable building materials. The current study focuses on proposing a methodology to design sustainable GGBS-based alkali-activated concrete incorporated with 100% coarse recycled coarse aggregates (RCA) recovered from construction and demolition (C&D), for various strengths by optimizing the mix proportions and verifying the same through experiments. From the current study, it is evident that this mix design procedure can be adopted to design alkali-activated slag recycled aggregate concrete (AASRAC) mixes for strengths ranging from 44MPa to 85MPa. The optimum values of alkalinity factor (λ) and NaOH concentration (M) i.e., 1.5 and 12, have a significant role in the development of high strengths which is attributed to the formation of hydrotalcite. Micrographs captured using scanning electron microscope (SEM) and energy dispersive X-ray spectroscopy (EDS) studies reveal that the alkaline binders promote the development of a denser and stronger interfacial transition zone (ITZ) that enhances the strength of lower AA/B concretes at the microstructural level as Ca/Si ratio is higher for lower AA/B concretes. Global warming potential (GWP) analysis reveals that the alkali-activated concretes have significantly lower GWP compared to conventional OPC-based concrete by approximately 2.5 times. The mix-design chart proposed in this study may pave the way to designing structural grade AASRAC with enhanced performance for the desired strength, which may find its application in fast-track construction and manufacturing of prefabricated elements.

The Effect of Differences in Fiber Sizes on the Cutting Force During the Drilling Process of Natural Fiber-Reinforced Polymer Composites

This experiment aimed to analyze the impact of different fiber sizes on cutting forces during the drilling of Natural Fiber-Reinforced Polymer Composites (NFRPC) while also evaluating surface quality attributes, including delamination, fiber pullout, and overhanging fibers, influenced by variations in coconut fiber dimensions within the NFRPC material. The manufacturing process for composite panels utilized various methods, including hand layup for 200 mm long coconut fibers and composite casting for shorter fibers (2, 4, and 6 mm) mixed with polymer-epoxy. The results indicate that panels made from NFRPC with continuous fiber lengths of 200 mm exhibit higher cutting force values (253,650 N) compared to epoxy panels without fibers (235,288 N), suggesting that a significant force is required to sever the continuous fibers within the NFRPC. Conversely, the incorporation of short coconut fibers measuring 2, 4, and 6 mm reduces the cutting forces on the composite panels. However, excessive surface roughness in the final hole quality can be detrimental, primarily due to issues of delamination and fiber pull-out.

Easy-to-make peptide-decorated C18 microspin columns combined with MALDI-MS enabling high-throughput enrichment and detection of arsenic (III) ions

In this study, a user-friendly, cost-effective, and high-throughput method was developed for the selective enrichment and accurate quantification of arsenic (III) ions using peptide-decorated C18 microspin columns, integrated with matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) analysis. The manufacturing process of the peptide-decorated C18 microspin columns originated from C18 StageTips packing with 3 μm C18 beads, followed by decoration with the peptide YYYCYCYYCR, which contained the arsenic (III) ion-binding motif CXCXXC, where X represents any amino acid. The microspin columns were applied to selectively capture arsenic (III) ions in environmental water by forming arsenic (III)-peptide complexes. After elution and drying, the high m/z ions from these complexes were directly desorbed and ionized with MALDI-MS by the addition of the α-CHCA matrix solution, effectively reducing interference from matrix-related ions and small molecules in the low m/z range. The developed method demonstrated a linear range from 10 μg/L to 1500 μg/L, with a limit of detection of 0.7 μg/L. Remarkably, this method enabled rapid quantification of arsenic (III) ions in environmental water, averaging under one minute per sample, using only a small volume of 50 μL. The reported method for detecting arsenic (III) ions in environmental water offers a practical approach and holds promise for analyzing other emerging toxic elements in the future.

One-pot synthesis of foamable bio-resin: High solid content, low viscosity and rapid low-temperature curing

The increasing global concerns surrounding sustainable resource development and energy-efficient utilisation have positioned the functional utilisation of natural biomass materials as a critical research hotspot in materials science. This study aims to enhance the utilisation of lignocellulose, a highly promising and abundant renewable energy source, to replace petroleum-based materials with wood-based materials. To achieve this objective, the study employed techniques such as liquefaction degradation, molecular reconstruction and directional induction to synthesise wood-based resin through a one-pot process, using poplar powder. The resulting resin exhibited a solid content ranging from 65 % to 68 % and viscosity between 8000 and 4000 mPa·s. Compared with resin formulations lacking divalent metal ions, the resin containing these ions demonstrated an approximate reduction of 8°C in peak curing temperature and a 42.96 % decrease in curing time. These characteristics satisfy the requirements for foaming resins, including high solid content, low viscosity and rapid curing at low temperatures. Additionally, the impacts of resin rheology and thermosetting on the foam pore structure were analysed using principles of rheology and thermodynamics. The integrated manufacturing process of the resin resulted in zero waste or by-products, thereby enhancing efficiency, conserving energy and demonstrating promising market prospects.

Multivariate process capability analysis with decision-maker preferences

A process capability analysis is an invaluable technique for assessing the efficacy of a system by determining its alignment with customer expectations. In the context of a manufacturing process with multiple correlated variables, the use of multivariate methods is essential for the analysis of quality characteristics. In the literature, there have been various proposals for MPCI (multivariate process capability indices) based on different approaches, including the proportion of non-conforming items or PCA (principal component analysis). In this context, a novel approach to capability analysis with multiple responses of varying degrees of importance has been proposed, termed WAMP (Weighted Arithmetic Mean with Prioritization). The findings indicated that the WAMP method demonstrated greater robustness than the SAM (simple arithmetic mean) and SGM (simple geometric mean) approaches. However, the WAM (weighted arithmetic mean) and WGM (weighted geometric mean) methods also exhibited satisfactory performance in accordance with the established acceptance criteria. The method was evaluated using both simulated and experimental data, demonstrating its efficacy in scenarios with varying degrees of correlation. When a greater weight is assigned to a single original variable, the MPCI is observed to be similar in value to that of the original variable with the highest weight when considered univariately. When equal weights are assigned to two original variables, the MPCI is situated within the capability indices of the original variables with the highest weight. Furthermore, it was observed that the performance of the MPCI improves with an increase in correlation. In conclusion, WAMP has been demonstrated to be a valuable and effective tool for capability analysis in systems with multiple correlated responses of varying degrees of importance.

Are Nanostructured Lipid Carriers (NLC) better than Solid Lipid Nanoparticles (SLN) for delivering abiraterone acetate through the gastrointestinal tract?

Abiraterone acetate (AbA) is a progesterone derivative indicated for the treatment of metastatic prostate cancer. This BCS (Biopharmaceutics Classification System) Class IV molecule has an extremely poor oral bioavailability (<10 %), notably due to its very low water solubility and intestinal permeability. Among the few existing galenic strategies to improve AbA’s oral bioavailability, lipid nanoparticles such as Solid Lipid Nanoparticles (SLN) and Nanostructured Lipid Carriers (NLC) are relevant nanovectors. The objective of this study is to develop and compare SLN and NLC for oral delivery of abiraterone acetate. Both SLN and NLC are biocompatible, biodegradable and produced by high pressure homogenization (HPH), an ecological-friendly manufacturing process, organic solvent-free and easily scalable. The HPH process allowed the formation of AbA-loaded SLN and NLC with particle size lower than 160 nm and high encapsulation efficiencies. The addition of a liquid lipid significantly reduced the mean diameter of the nanoparticles, reflecting the greater benefit of the NLC formulation compared to SLN. Both SLN and NLC formulations offered an important protection of AbA in intestinal media, with a better stability for NLC. When encapsulated in SLN or NLC, the AbA is strongly retained by the nanoparticles, whatever the dissolution medium, which means that both formulas are able to protect and retain the drug in the intestinal tract, right up to its delivery to the enterocytes surface. High concentrations of nanoparticles were administered without cytotoxicity, especially for the NLC, which provides a real added value in terms of biocompatibility with Caco-2 cells. Finally, the nanoparticles were able to penetrate into enterocytes by the transcellular route, demonstrating an intense cellular internalization.

Optimization of Resin Infusion Processes in Composite Manufacturing: An Experimental Study on Void Formation

This research aims at determining the effect of the process parameters namely the vacuum pressure, resin viscosity, temperature and flow rate on formation of voids in the composite manufacturing during resin infusion process. Thus, the study executes controlled experiments and quantitatively examines void content under different parameter configurations to determine that certain conditions substantially reduce voids, improving composite quality. The study reveals that selected vacuum pressure of about 100 kPa, resin viscosity of 200-250 cP at higher temperature and carefully regulated flow rates of 10- 15mL/min help to reduce air bubbles to the barest minimum. These findings provide significant advantages to composite producers on aspects of productivity, mechanical properties and material costs. Similarly, the results indicate the following from secondary research and comparative analysis: Further investigation of real-time void monitoring, exploring advanced optimization with machine learning models. This research is relevant for the enhancement of low-cost and efficient manufacturing techniques in industries that incorporate high-performance composites

Research progress on mineral-filled biocomposites: properties, manufacturing methods and applications

The review article presents a comprehensive analysis of recent research on biocomposites based on natural minerals as fillers. The various minerals available on the market and their potential to modify and improve the properties of composites are discussed. Methods of manufacturing biocomposites, such as blending, impregnation and coating application, are described in detail, taking into account the importance of process parameters and component ratios for achieving optimal material properties. The article also examines recent scientific developments related to the use of minerals in biocomposites, paying particular attention to their effects on strength, stiffness, environmental resistance and biodegradation. Despite advances in biocomposite manufacturing technology, there is a need for further research into optimizing manufacturing processes to obtain materials with homogeneous properties. Future research should focus on analyzing the effects of different types of minerals and their proportions on the properties of biocomposites. Biocomposites with natural minerals are widely used in various industrial sectors, from construction to automotive and food packaging, suggesting their potential as an alternative to traditional plastics, contributing to the development of greener materials.

Application of Image Recognition Technology in Nozzle Cleaning for Material Extrusion Additive Manufacturing Processes

Application of Image Recognition Technology in Nozzle Cleaning for Material Extrusion Additive Manufacturing Processes

Assessing Protein Content and Dimer Formation in the Bevacizumab Reference Product and Biosimilar Versions Marketed in Spain

Background: The manufacture of biologics is a complex, controlled, and reproducible process that results in a product that meets specifications. This should be based on data from batches used to demonstrate manufacturing consistency. Ten batches of originator product (Avastin®) were analyzed over a 10-year period. Methods: The β-expectation tolerance intervals and the process capability analysis were proposed to establish the specification limits for determining the acceptance criteria of the final product from the manufacturing process. Protein concentration and dimer content were utilized as CQAs. The analytical similarity between three biosimilars authorized in Spain since 2021 (Vegzelma®, Alymsys®, and Oyavas®) and the originator product were evaluated for both CQAs using two methods: the quality range (QR) method, based on one sample per batch, and the QRML one, which takes into account the inter- and intra-batch variability of the originator product. Results: The results indicate that the two main sources of variation are under control; even the level of variability observed is close to the capability of the analytical method. The manufacturing process, therefore, continues under statistical control. Similarity is demonstrated for the bevacizumab concentration regardless of the approach used, whereas similarity is demonstrated for the dimer content for only one of the biosimilar products. Conclusions: The proposed methodologies allow for the analysis of the consistency of the manufacturing process and the variability from batch to batch.

Coupled Electrolysis–Microfiltration System for Efficient Phosphorus Removal and Recovery in the Form of Iron Phosphate Compounds from Wastewater

Electrochemical technology presents a promising approach for phosphorus recovery from wastewater. Nevertheless, its application in industry is hindered by relatively low phosphorus recovery efficiency, high energy consumption and complex reactor configurations. In this study, a coupled electrolysis and microfiltration system was designed for phosphorus recovery in the shape of iron phosphate compounds with the use of steel pickling wastewater as the iron source. In the electrolysis unit, the anode diffusion layer was extracted from the porous anode surface with the production of an acid effluent and an alkaline effluent. The alkaline effluent was mixed with the stainless steel acid washing wastewater generated from the steel pickling process and then introduced into the microfiltration unit to intercept the iron phosphate crystals. The filtered effluent was finally introduced into the air aeration unit to further reduce the phosphorus content in the water. And the extracted acid solution could be reused in the pickling step of the iron and steel manufacturing process. The experimental results show that the coupled system achieved phosphorus recovery of 42~80% at a current density of 5~20 mA cm−2, accompanying energy consumption of 5.78~9.15 kWh (kg P)−1 and current efficiency of 79~43%, when the phosphorus concentration was 3 mM and the iron–phosphorus molar ratio was 1.5. After the microfiltration treatment, the residual phosphorus could be further reduced to 0.5 mg L−1 within 30 min at an aeration rate of 80 mL min−1, which met the discharge standard. The presence of interfering ions (HCO3− and SiO42−) posed inhibited effects on phosphorus recovery. Generally, this study provides a green and environmentally friendly way to efficiently recover phosphorus resources from wastewater.

Designing Phenolphthalein-Based Adsorptive Membranes for the High-Affinity, High-Capacity Capture of Contaminants from Water.

The selective removal of solutes is crucial for ensuring a sustainable water supply, recovering resources, and cost-effective biomanufacturing. Adsorptive membranes are promising in this regard due to their rapid mass transfer and low energy demands. However, state-of-the-art adsorptive membranes offer limited pore sizes and surface chemistries. This study reports the development of adsorptive membranes from reactive phenolphthalein-based (PPH-based) polymers. These polymers, which are molecularly engineered to possess a high density of reactive pendant groups, are transformed into porous membranes through a surface-segregation vapor-induced phase separation (SVIPS) method. Examining the thermodynamic characteristics of the polymer-solvent-nonsolvent system informs the SVIPS manufacturing process and facilitates the formation of diverse membrane morphologies with hydraulic permeabilities ranging from 3400 to 13,500 L m-2 h-1 bar-1. Copper ion binding experiments demonstrate a saturation capacity of 0.9 mmol Cu2+ g-1, indicating high accessibility of the pendant groups for postsynthetic modification. Functionalization with alkyne groups enables one-step click reactions, such as the thiol-yne and Cu(I)-catalyzed azide-alkyne cycloaddition, expanding the membrane functionality. The incorporation of cucurbit[7]uril-azide macrocycles demonstrates the affinity-mediated capture of methyl viologen from solution. The combination of PPH-based polymers and the SVIPS method provides a versatile adsorptive membrane platform with a dense presentation of reactive sites, facilitating customization through diverse and high-yielding reactions.

Wear performance enhancement of interface layer in CMT-WAAM fabricated ER4043/ER5356 Bimetallic wall through Friction Stir Surface Treatment

Abstract The cold metal transfer (CMT) based wire arc additive manufacturing (WAAM) technique has limited wear applications compared to other manufacturing methods due to its lower wear resistance. However, integrating friction stir processing (FSP) with WAAM can enhance mechanical or wear performance, making it a promising and reliable manufacturing process for aerospace, automotive, and marine applications. In this work, CMT-WAAM technique has been used to fabricate a bimetallic wall of aluminium alloys (ER4043/ER5356), employing a bidirectional depositional strategy. The impact of FSP on the interface layer of the WAAM wall, serving as a post-processing treatment on the wall's surface, is studied in terms of microstructure and microhardness. Additionally, a pin-on-disk wear test is performed on the interface layer of both WAAM and FSP-treated WAAM walls under loads of 20N, 30N, and 40N. Results from optical and Field emission scanning electron microscopy (FESEM) microstructures revealed the grain refinement in the stirred zone, with a higher wt. % of Mg through Energy Dispersive Spectrometer (EDS) analysis. X-ray diffraction (XRD) identifies various intermetallic compounds, including Al12Mg17, Al3.21Si0.47, and Mg2Si, with higher peak intensities in the FSP-treated wall. Electron Backscatter Diffraction (EBSD) analysis indicates a decrease in the average grain size of stirred area, which is ~72.40 µm in unstirred area and ~5.57 µm in stirred area due to the local strain concentration effect during FSP. Grain refinement during FSP leads to an increase in average hardness by 35.9%. The wear rate and coefficient of friction (COF) get reduced, credited to high-temperature dynamic recrystallization and continuous grain recovery in FSP. Scanning electron microscope (SEM) analysis of worn surfaces highlights abrasion, delamination, and adhesion as significant wear mechanisms.

Mutual advancement: How integrated circuits interact with artificial intelligence

Abstract. Integrated circuits and artificial intelligence complement each other. On one hand, the continuous optimization of electron and photon accelerators can reduce the energy consumption of artificial intelligence algorithms and adapt them to edge computing, thereby promoting the development of artificial intelligence. On the other hand, artificial intelligence not only assists in troubleshooting and optimizing of integrated circuits, but also automates the design of integrated circuits, making them more convenient and efficient. The interactive relationship between integrated circuits and artificial intelligence is presented through qualitative analysis and literature review in this paper. The mutual influence of these two technologies creates new breakthroughs and possibilities for the development of science and technology. However, while photonic artificial intelligence accelerators are suitable for high-speed neural networks, their current development is not yet mature due to the high cost, complex manufacturing process, and environmental disturbances. Additionally, artificial intelligence algorithms for integrated circuits design lack sufficient high-quality data for training due to the secrecy of integrated circuit parameters. Thus it requires a long time to train and perfect these algorithms.