Manufacturing Platform Research Articles

A blockchain-based self-adaptive collaboration mechanism for service-oriented manufacturing system

ABSTRACT The service-oriented manufacturing system, based on the cloud manufacturing platform, is adversely affected by factors such as diverse entities, geographical dispersion, and distributed collaboration. The system faces challenges like a lack of trust among entities and operational process uncertainty, thereby significantly reducing service collaboration efficiency. Blockchain, a promising technology in the information era, can address these issues by enhancing the authenticity of service data and trust among entities. In this paper, a blockchain-based operational mode is proposed to establish a completely trustworthy manufacturing environment. The potential abnormal events during collaborative service processes and their impacts are illustrated. According to these analyses, a self-adaptive service collaboration process is designed utilizing the blockchain, and a trust-based service collaboration model involving multiple entities is developed to enhance the system adjustment efficiency. This model, integrated with the solving algorithm, is deployed in smart contracts for automatic adjustment of service entities. An experimental study is conducted to verify the effectiveness of the proposed self-adaptive collaboration process and adjustment model. The results show that the proposed method can effectively boost the efficiency of the service-oriented manufacturing system.

Ultrahigh Piezoelectricity in Truss‐Based Ferroelectric Ceramics Metamaterials

AbstractConventional porous ferroelectric materials sacrifice their piezoelectric constants for improving various figures of merit due to a rapidly decreased dielectric constant. Here, novel truss‐based ferroelectric metamaterials that simultaneously offer ultrahigh piezoelectric constants and ultralow dielectric constants, originating from the unique combination of truss loading states and polarization direction, are discovered. The homogenization method alongside an analytical model is proposed to predict and elucidate their extraordinary properties, while a customized ferroceramic additive manufacturing platform is resorted to fabricate them. Unlike porous ferroelectrics, ultrahigh piezoelectric constants at low relative densities (ρr ≈0.1) are attained. For example, with appropriate scaling, the experimental values of d31, d33, and d42 for a ferroelectric octet truss with ρr = 0.1, can reach 849, −659, and 836 pC N−1, respectively, which are 3.14, 6, and 2 times higher than the counterpart of bulk BaTiO3 ceramics. Combined with the ultralow dielectric constant, extremely high ferroelectric figures of merit, e.g., piezoelectric voltage constant of 11.098 Vm N−1, piezoelectric energy harvesting figure of merit 9422 × 10−12 m2 N−1, and pyroelectric voltage sensitivity of 56.7 × 10−3 m2 C−1, are also observed. The multifunctional ferroelectric metamaterials open new avenues for their applications in self‐powered ultrasensitive accelerometers, high‐performance noncontact sensors, and wearable input devices.

Enhancing Patient-Centric Drug Development: Coupling Hot Melt Extrusion with Fused Deposition Modeling and Pressure-Assisted Microsyringe Additive Manufacturing Platforms with Quality by Design

In recent years, with the increasing patient population, the need for complex and patient-centric medications has increased enormously. Traditional manufacturing techniques such as direct blending, high shear granulation, and dry granulation can be used to develop simple solid oral medications. However, it is well known that “one size fits all” is not true for pharmaceutical medicines. Depending on the age, sex, and disease state, each patient might need a different dose, combination of medicines, and drug release pattern from the medications. By employing traditional practices, developing patient-centric medications remains challenging and unaddressed. Over the last few years, much research has been conducted exploring various additive manufacturing techniques for developing on-demand, complex, and patient-centric medications. Among all the techniques, nozzle-based additive manufacturing platforms such as pressure-assisted microsyringe (PAM) and fused deposition modeling (FDM) have been investigated thoroughly to develop various medications. Both nozzle-based techniques involve the application of thermal energy. However, PAM can also be operated under ambient conditions to process semi-solid materials. Nozzle-based techniques can also be paired with the hot melt extrusion (HME) process for establishing a continuous manufacturing platform by employing various in-line process analytical technology (PAT) tools for monitoring critical process parameters (CPPs) and critical material attributes (CMAs) for delivering safe, efficacious, and quality medications to the patient population without compromising critical quality attributes (CQAs). This review covers an in-depth discussion of various critical parameters and their influence on product quality, along with a note on the continuous manufacturing process, quality by design, and future perspectives.

Design and research of numerical control simulation platform in discrete manufacturing disturbed by vibration

It is of great significance to study the deep integration of manufacturing technology and new-generation information communication technology under vibration interference of machine tools to improve the intelligence level of CNC machine tools. In this paper, a numerical control manufacturing workshop affected by vibration in discrete manufacturing is taken as the research background, and a solution for a digital workshop operation simulation platform based on the industrial internet is proposed. By constructing the simulation environment of the operation process of the digital factory, the generation and transmission of manufacturing information in the digital factory are simulated. The application architecture of the machining workshop based on a numerical control simulation platform is proposed, and the business process of the numerical control machining workshop is analyzed. Then, the key technologies of NC machine tool modeling, synchronous mapping of data and model, data integration, and fusion are studied. Through the integration and implementation of the NC machine tool simulation platform in the machining workshop, the top-down data instructions can be issued accurately, and the bottom-up feedback information can be confirmed in time. Finally, the system is applied to the electronic information and ship machining workshop to verify the effectiveness of the system framework and method proposed in this paper.

The Effect of Elastomer Content and Annealing on the Physical Properties of Upcycled Polyethylene Terephthalate-Maleated Styrene Ethylene Butylene Styrene Blends for Additive Manufacturing.

In the work presented here, we explore the upcycling of polyethylene terephthalate (PET) that was derived from water bottles. The material was granulated and extruded into a filament compatible with fused filament fabrication (FFF) additive manufacturing platforms. Three iterations of PET combined with a thermoplastic elastomer, styrene ethylene butylene styrene with a maleic anhydride graft (SEBS-g-MA), were made with 5, 10, and 20% by mass elastomer content. The elastomer and specific mass percentages were chosen based on prior successes involving acrylonitrile butadiene styrene (ABS), in which the maleic anhydride graft enabled compatibility between different materials. The rheological properties of PET and the PET/SEBS blends were characterized by the melt flow index and dynamic mechanical analysis. The addition of SEBS-g-MA did not have a significant impact on mechanical properties, as determined by tensile and impact testing, where all test specimens were manufactured by FFF. Delamination of the tensile specimens convoluted the ability to discern differences in the mechanical properties, particularly % elongation. Annealing of the specimens enabled the observation of the effect of elastomer content on the mechanical properties, particularly in the case of impact testing, where the impact strength increased with the increase in SEBS content. However, annealing led to shrinkage of the specimens, detracting from the realized benefits of the thermal process. Scanning electron microscopy of spent tensile specimens revealed that, in the non-annealed condition, SEBS formed nodules that would detach from the PET matrix during the tensile test, indicating that a robust bond was not present. The addition of SEBS-g-MA did allow for shape memory property characterization, where deformation of tensile specimens occurred at room temperature. Specimens from the 20% by mass elastomer content sample group exhibited a shape fixation ratio on the order of 99% and a shape recovery ratio on the order of 80%. This work demonstrates a potential waste reduction strategy to tackle the problem of polymer waste by upcycling discarded plastic into a feedstock material for additive manufacturing with shape memory properties.

Inkjet Printed Multifunctional Graphene Sensors for Flexible and Wearable Electronics

AbstractThe exceptional electrical properties of graphene with high sensitivity to external stimuli make it an ideal candidate for advanced sensing technologies. Inkjet printing of graphene (iGr) can provide a versatile platform for multifunctional sensor manufacturing. Here the multifunctional sensor enabled by combining the design freedom of inkjet printing with the unique properties of graphene networks is reported on. A fully inkjet printed multimaterial device consists of two layers of iGr stripes separated by a dielectric polymeric layer of tripropylene glycol diacrylate (TPGDA). In these devices, the bottom iGr layer, capped with TPGDA, provides temperature sensing, the top uncapped iGr is sensitive to the external atmosphere, while the capacitance between the two iGr layers is sensitive to the applied pressure. The fast, sensitive, and reproducible performance of these sensors are demonstrated in response to environmental stimuli, such as pressure, temperature, humidity, and magnetic field. The devices are capable of simultaneous sensing of multiple factors and are successfully manufactured on a variety of substrates, including Si/SiO2, flexible Kapton films and textiles, demonstrating their potential impact in applications compatible with silicon technologies as well as wearable and healthcare devices.

Pricing Power Conflict and Cooperation Strategies of Competing Two‐Sided Platforms: Impact of the Differentiated Value‐Added Services and Cross‐Network Effects

ABSTRACTSince pricing power plays a pivot role in platforms' pricing strategies and services investment, thereby influencing the competitive landscape between the two platforms. This study investigates the pricing power preferences within a two‐sided manufacturing platform ecosystem, where a large‐scale platform (platform L) competes with a small‐specialized platform (platform R) for bilateral users through differentiated value‐added services (VAS) level. Both platforms exhibit cross‐network externality and engage in pricing power competition. Three endogenous pricing power modes are available, including horizontal Nash (mode B), platform L‐price‐leader Stackelberg (mode L), and platform R‐price‐leader Stackelberg (mode R). The optimal solutions under each mode and characterize the equilibrium evolution of pricing power preferences are derived. Findings reveal that at the low VAS level stage for platform L, mode R realizes equilibrium when the hassle cost is low; mode L realizes equilibrium when the hassle cost is high. At the high VAS level stage for platform L, mode L realizes equilibrium when the hassle cost is high; mode R realizes equilibrium only when the hassle cost is low and cross‐network externality is in a high range. Notably, competing platforms will trap into the pricing power conflict when both platforms strategically second moves in announcing prices. Therefore, this study proposes two feasible strategies for platform cooperation: joint revenue and VAS cost‐sharing and transfer payment. These strategies can reach a “win–win” outcome when sharing ratios are moderate or payment meets suitable thresholds. This study not only enhances the theory of two‐sided markets but also provides strategic guidance for platform competition and cooperation.

A novel supply-demand matching model for shared manufacturing resources

ABSTRACT Shared manufacturing is an innovative application of the sharing economy in manufacturing field, aiming to optimize capacity utilization and improve the efficiency of supply-demand matching. The supply-demand matching of manufacturing resources is a key issue on the shared manufacturing platform. In practice, shared manufacturing is proposed based on the objective of optimizing capacity utilization of idle manufacturing resources. In addition, multi-attributes on manufacturing resources are negotiated simultaneously, such as price, quality, and delivery time. However, the existing supply-demand matching models neither consider the optimization objective of capacity utilization nor multi-attribute negotiation requirements. The objective of this research is to propose a novel supply-demand matching model for the shared manufacturing resources, including a double auction-based supply-demand matching relationship determination and a multi-attribute negotiation-based transaction detail determination. In the first stage, a double auction model of manufacturing resources is proposed to determine the matching relationship between provider and demanders. In the proposed double auction model, utility functions for both parties are constructed to express their personalized preferences on bidding attributes; bidding strategies for both parties are determined to generate bidding values; a winner determination model is proposed to determine the matched provider and demander of manufacturing resources maximizing social welfare and capacity utilization. In the second stage, a multi-attribute negotiation model is developed to determine the concrete deal information of manufacturing resources, such as transaction prices, quality, and delivery time. Finally, the feasibility and efficiency of the proposed model is verified through numerical examples.

Design and fabrication of a parasite-inspired, millimeter-scale tissue anchoring mechanism.

Optimizing mechanical adhesion to specific human tissue types is a field of research that has gained increasing attention over the past two decades due to its utility for diagnostics, therapeutics, and surgical device design. This is especially relevent for medical devices, which could benefit from the presence of attachment mechanisms in order to better target-specific regions of the gastrointestinal (GI) tract or other soft tissues for sensing, sample collection, and drug release. In this work, and inspired by the tissue anchoring adaptations found in diverse parasitic taxa, we present a design and manufacturing platform for the production of a nonintuitive bioinspired millimeter-scale articulated attachment mechanism using laminate fabrication techniques. The functional design closely mimics the geometry and motions of curved hooks employed by some species of tapeworms to attach to their host's intestinal walls. Here, we show the feasibility of such a mechanism both in terms of attachment capabilities and manufacturability. Successful attachment of a prototype to tissue-simulating synthetic medical hydrogels is demonstrated with an adhesion force limited only by the ultimate strength of the tissue. These results demonstrate the efficacy of parasite-inspired deployable designs as an alternative to, or complement to, existing tissue attachment mechanisms. We also describe the design and manufacturing process workflow and provide insights for scaling the design for mass-production.

Microfluidic-Chip-Based Formulation and In Vivo Evaluations of Squalene Oil Emulsion Adjuvants for Subunit Vaccines.

Adjuvants play a crucial role in improving the immunogenicity of various antigens in vaccines. Squalene-in-water emulsions are clinically established vaccine adjuvants that improve immune responses, particularly during a pandemic. Current manufacturing processes for these emulsion adjuvants include microfluidizers and homogenizers and these processes have been used to produce emulsion adjuvants to meet global demands during a pandemic. These processes, however, are complex and expensive and may not meet the global needs based on the growing populations in low- and middle-income countries. At the forefront of adjuvant research, there is a pressing need to manufacture emulsion adjuvants using novel approaches that balance efficacy, scalability, speed of production, and cost-effectiveness. In this study, we explored the feasibility of a microfluidic chip platform to address these challenges and evaluated the adjuvanticity of the emulsion adjuvant prepared using the microfluidic chip process in CB6F1 mice model, and compared it with a control formulation. We developed and optimized the process parameters to produce emulsion adjuvants with characteristics similar to SEA160 (control formulation). The resulting emulsion prepared using the microfluidic chip process (MC160) when mixed with ovalbumin, maintained antigen structural integrity. Immunogenicity studies in a CB6F1 mouse model, with the Cytomegalovirus glycoprotein B (CMV gB) antigen, resulted in humoral responses that were non-inferior between MC160 and SEA160, thereby validating the microfluidic chip approach for manufacturing emulsion adjuvants. These findings demonstrate a proof of concept for using microfluidic chip platforms for formulating emulsion adjuvants, offering a simpler manufacturing platform that can be deployed to low- and middle-income countries for rapid production, improving adjuvant access and aiding in pandemic preparedness.

Ab-Initio and Experimental Study of Oxygen Reduction Reaction (ORR) Activity and Durability of Ordered PtNi/C Catalysts

Developing durable and highly active low-Pt electrocatalysts for oxygen reduction reaction (ORR) in acidic media is necessary for highly effective polymer electrolyte membrane fuel cells (PEMFCs). Intermetallic structure is thermodynamically more stable than random alloy metal compounds. In oxygen reduction reaction (ORR), Pt3Ni1 with (111) facet is to be the most effective electrocatalyst for ORR. Therefore, to develop a highly efficienct electrocatalyst for oxygen reduction reaction (ORR) in effective polymer electrolyte membrane fuel cell (PEMFC), an ordered PtNi/C intermetallic alloy on a carbon black support has been designed. To enhance ORR performance and reduce Pt usage, a Pt-transition metal alloy catalyst has been developed. Alloying Pt with a second metal on a carbon support material can improve activity due to the change in lattice parameter and the electronic effect. According to the d-band theory, the downshift effect of the d-band induced by the upshift of the fermi level is predicted to improve ORR activity by weakening the binding energy. In case of alloying Pt and Ni, it can be predicted that the difference in electronegativity between Pt and Ni will induce a fermi level shift, resulting in a d-band center shift effect, which can enhance ORR activity. Compared to random alloy structured electrocatalysts, intermetallic structures of ordered PtNi were more thermodynamically stable. Moreover, intermetallic structure stabilizes the alloy, improving the durability of metal components against chemical corrosion in acidic media, such as HClO4 or H2SO4. Therefore, to improve catalyst’s durability, heat treatment was used to align the structure, making it structurally stable and reducing Pt-Pt distance. Heat treatment screening was carried out between 500℃ and 800℃ using a thermal shock method to minimize particle size growth. X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and rotating disc electrode (RDE) were used to investigate the compositional difference and crystallinity of the intermetallic structure, electrochemical ORR activity and durability between disordered PtNi/C (d-PtNi/C) and ordered PtNi/C (o-PtNi/C). The electronic effect of the three Nicore@Ptshell models, namely ordered Nicore@Ptshell (o-PtNi), disordered Nicore@Ptshell (d-PtNi), and pure Pt147 (pure Pt), was estimated through density functional theory (DFT). The d-band theory and Bader charge analysis were used to estimate ORR activity and charge transfer, respectively. Additionally, the durability in acidic media of each model was estimated through dissolution potential calculations (Udiss). This work has supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT in Republic of Korea (MSIT) (NRF-2022R1A2C2093090). This work was supported by the Technology Innovation Program (20019175) funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea). This research was supported by the Ministry of Trade, Industry, and Energy (MOTIE), Korea, under “Digital manufacturing platform" (No. P0022331) supervised by the Korea Institute for Advancement of Technology (KIAT).

A Planar Sodium Nickel Chloride Battery Running at Intermediate Temperatures for Mid-Range Energy Storage

Sodium nickel chloride (Na-NiCl2) battery is one of the most promising candidates for grid scale electricity storage due to its high safety, long lifetime and demonstrated performance. The battery comprises molten Na and NiCl2 as negative and positive electrodes, respectively, in its charged state, separating them by a β”-Al2O3 solid electrolyte (BASE). In order to facilitate fast sodium ion transport in the cathode compartment, molten catholyte (NaAlCl4) is infiltrated into the cathode granule made of Ni and NaCl powders. The battery typically operates at 250-300oC so as to maximize the ionic flux in the cathode and through the solid electrolyte, and to minimize the dissolution of NiCl2 into the catholyte. However, this efficient battery is yet to be widely used in grid scale energy storage applications since it is still expensive mainly due to its use of expensive sealing technologies.The presentation introduces international collaborative efforts to develop a lower temperature operating planar Na-NiCl2 battery towards commercialization for the mid-range energy storage. Since the novel battery runs at 180oC, it can be fabricated at an ultra low manufacturing cost by adopting simpler and inexpensive polymer sealing and by introducing a planar cell design that can eliminate a number of unnecessary cell components. Starting with stating problems in traditional sodium beta-alumina batteries, their possible corresponding solutions are described. Challenges and progress in materializing the 6Ah class proto-type unit cell and its serially stacked cells will be discussed with related core technologies, including a cell design, highly toughened planar solid electrolyte, enhanced wetting, and semi-automated cell manufacturing platform.

Advancing Pt-Based Catalysts for alkaline Hydrogen Evolution: Achieving Boron Doping using 2D Borophene

Platinum-based catalysts are widely utilized in various electrochemical reactions such as oxygen reduction, hydrogen evolution, and oxygen evolution reaction. However, the high cost of Pt necessitates research on alloys with various transition metals to enhance catalyst activity while reducing expenses. Unfortunately, conventional alloy catalysts often suffer from decreased stability as transition metal elements dissolve, leading to catalyst degradation [1]. Various modifications such as core-shell structures or ordered structures are being introduced to enhance durability. Despite the exceptional catalytic activity demonstrated by many newly developed catalysts, durability often remains a concern [2]. Prolonged operation can lead to nanoparticle agglomeration, resulting in reduced surface area and active sites.In this study, boron is introduced to enhance durability by preventing particle agglomeration. Previous research has explored materials doped with boron or intermetallic structures as catalysts for various electrochemical reactions such as oxygen reduction, hydrogen evolution, and alcohol oxidation [3]. Boron has smaller electronegativity than metal elements and can expand the lattice of the metal via institutional doping. Consequently, the d-band center of the boron-introduced catalyst may downshift, weakening its bonding with oxygen or hydrogen and potentially improving activity.Unlike many studies utilizing boric acid, sodium borohydride, diethylamine borane as boron sources, this study employs borophene, a 2D structure of boron sheet. Chemically synthesized hydrogenated borophene (HB) serves as both a reducing agent and a boron source, incorporating boron into Pt-based catalyst [4]. A combination of various physicochemical analyses and computational approaches is employed to investigate the structure of the borophene-assisted catalyst.The introduction of boron in the form of borophene inhibits the nanoparticle agglomeration and particle size increase. Firstly, introducing borophene into Pt-metal alloy can suppress the unexpected growth of nanoparticle during constructing ordered structure. Intermetallic structure is usually formed through a few hours of heat treatment with high temperature. Typically, heat treatment leads to particle agglomeration, causing an increase in particle size. Compared with commercial Pt catalyst, Pt-metal alloy catalyst, and borophene-assisted Pt-metal catalyst, the introduction of boron in the form of borophene can reduce particle agglomeration during heat treatment. Additionally, the borophene-assisted Pt-based catalyst is employed in electrocatalytic reactions. Through durability tests lasting over 100 hours, borophene-assisted Pt-based catalyst exhibits superior durability in various electrochemical environments compared to conventional Pt catalysts and Pt-based catalyst without boron.Borophene-assisted catalyst holds promise for convenient application in synthesizing various metal nanoparticles, playing a crucial role in preventing agglomeration and maintaining high performance over an extended period. This study will significantly contribute to research on catalysts with excellent durability.This work has supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT in Republic of Korea (MSIT) (NRF-2022R1A2C2093090), Ministry of Trade, Industry & Energy (MOTIE, Korea) under the Technology Innovation Program (20019175) supervised by the Korea Evaluation Institute of Industrial Technology(KEIT), and “Digital manufacturing platform" (No. P0022331) supervised by the Korea Institute for Advancement of Technology (KIAT).[1] Beilstein J. Nanotechnol. 2014, 5, 44–67[2] J. Mater. Chem. A , 2017, 5, 1808-1825[3] ACS Catal . 2022, 12, 20, 12750–12764[4] J. Am. Chem. Soc. 2017 , 139, 13761-13769

Rapid Prototyping of Multiscale Flexible Printed Circuit Boards With NeXus, a Robotic Additive Manufacturing System

Abstract This paper demonstrates the NeXus system, a multiscale robotic additive manufacturing platform developed at the Louisville Automation and Robotics Research Institute, as a rapid prototyping tool through additively manufacturing a multilayer flexible printed circuit board (FPC) with a printed strain sensor and soldered surface mounted devices (SMD). Manufacturing of the demonstrator requires the application and curing of multiple materials with specialized properties, tools for automated assembly, and software advances to streamline the process enabling the use of industry-standardized programs to command the NeXus system. Additive manufacturing processes supported by the NeXus include aerosol jet printing (AJP) for fine feature silver conducting lines, direct write ink-jet printing for insulating materials, and intense pulsed light (IPL) for curing materials between depositions. The NeXus system transports and manipulates parts using a six-degree-of-freedom (DOF) high-precision positioner. Solder paste deposition and pick-and-place (PnP) procedures are performed by a 4DOF Selective Compliance Articulated Robot Arm (SCARA). Conversion methods between traditional printed circuit board (PCB) design software and production-ready command scripts were developed to translate basic drawings into command scripts. Multilayer structures with AJP 50-μm wide lines, an insulating bridge with a thickness of around 100 μm, and SMDs soldered to silver AJP pads were integrated within the demonstrator. An operational amplifier and other SMDs reduce the complexity of the accompanying control circuit and amplify the sensor's response by 1830 times. The successful fabrication of the demonstrator FPC highlights the rapid prototyping ability of the NeXus system.

Engineering Escherichia coli-Derived Nanoparticles for Vaccine Development.

The development of effective vaccines necessitates a delicate balance between maximizing immunogenicity and minimizing safety concerns. Subunit vaccines, while generally considered safe, often fail to elicit robust and durable immune responses. Nanotechnology presents a promising approach to address this dilemma, enabling subunit antigens to mimic critical aspects of native pathogens, such as nanoscale dimensions, geometry, and highly repetitive antigen display. Various expression systems, including Escherichia coli (E. coli), yeast, baculovirus/insect cells, and Chinese hamster ovary (CHO) cells, have been explored for the production of nanoparticle vaccines. Among these, E. coli stands out due to its cost-effectiveness, scalability, rapid production cycle, and high yields. However, the E. coli manufacturing platform faces challenges related to its unfavorable redox environment for disulfide bond formation, lack of post-translational modifications, and difficulties in achieving proper protein folding. This review focuses on molecular and protein engineering strategies to enhance protein solubility in E. coli and facilitate the in vitro reassembly of virus-like particles (VLPs). We also discuss approaches for antigen display on nanocarrier surfaces and methods to stabilize these carriers. These bioengineering approaches, in combination with advanced nanocarrier design, hold significant potential for developing highly effective and affordable E. coli-derived nanovaccines, paving the way for improved protection against a wide range of infectious diseases.

Strategic interactions between manufacturer channel choice and platform entry in a dual-market system

The full lifecycle concept has prompted sellers to provide ancillary services or products based on traditional product sales, leading to a dual-market system consisting of a base market and an add-on market. In this study, we consider a manufacturer selling base products through an online retail platform and then selling add-on products directly to consumers who have purchased base products. We investigate how the manufacturer’s distribution channel strategy in the base market interacts with the platform’s entry strategy in the add-on market. Results show that under the reselling (agency) channel, the platform’s entry of the add-on market enables the manufacturer to increase the wholesale price (reduce selling quantities to enjoy a higher margin) in the base market. We call this wholesale price effect (sales-control effect) caused by the platform’s entry. If the manufacturer adopts the agency (reselling) channel in the base market, the platform prefers (not) to enter the add-on market to compete with the manufacturer; if the manufacturer adopts the dual-channel, the platform enters only if both the commission rate and channel competition are high. Furthermore, the manufacturer prefers the dual-channel when both the commission rate and channel competition are low. Interestingly, due to the interactions between the two firms, the manufacturer will adopt the agency channel instead when the commission rate is extremely high. Finally, we examine conditions under which the platform has incentives to allow the manufacturer to change from a single-channel to a dual-channel in the base market.

Polarity controlled ScAlN multi-layer transduction structures grown by molecular beam epitaxy

We report on the molecular beam epitaxial growth and characterization of polarity-controlled single and multi-layer Scandium Aluminum Nitride (ScAlN) transduction structures grown directly on ScAlN templates deposited by physical vapor deposition (PVD) on Si(001) substrates. It is observed that direct epitaxial growth on PVD N-polar ScAlN leads to the flipping of polarity, resulting in metal (M)-polar ScAlN. By effectively removing the surface impurities, e.g., oxides, utilizing an in situ gallium (Ga)-assisted flushing technique, we show that high quality N-polar ScAlN epilayers can be achieved on PVD N-polar ScAlN templates. The polarity of ScAlN is confirmed by utilizing polarity-sensitive wet chemical etching and atomic-resolution scanning transmission electron microscopy. Through interface engineering, i.e., the controlled formation or removal of surface oxides, we have further demonstrated the ability to epitaxially grow an alternating tri-layer piezoelectric structure, consisting of N-polar, M-polar, and N-polar ScAlN layers. Such multi-layer, polarity-controlled ScAlN structures promise a manufacturable platform for the design and development of a broad range of acoustic and photonic devices.

Discrete-Event Simulation Integrates an Improved NEH Algorithm for Practical Flowshop Scheduling Problems in the Satellite Industry

The production of multiple types of satellites based on a common manufacturing platform represents a permutation flowshop scheduling problem (PFSP) with complex constraints. This is a highly complex scheduling problem, yet there is still a gap between theoretical research and practical application, particularly in the satellite industry. Therefore, we propose a more practical method that integrates discrete-event simulation modelling and an improved NEH algorithm to solve a more realistic PFSP. The discrete-event simulation-based method includes the following three main components: a flexible PFSP simulation modelling approach, an improved NEH algorithm, and an interaction mechanism between the simulation model and the optimisation algorithm. The proposed method allows automatic and flexible simulation modelling according to the characteristics of the actual satellite manufacturing workshop, which determines the practical nature of the approach proposed in this paper and then achieves excellent scheduling results based on the special interaction mechanism. The computational results demonstrate that this is a 9.18% improvement over the initial NEH algorithm and a 1.40% improvement over the best current improved NEH algorithm.

Atomic Layer Processing (ALP): Ubi es et Quo Vadis?

AbstractAtomic Layer Processing (ALP) techniques have transformed materials engineering by enabling atomic/molecular‐level control over composition, fidelity in structure replication, and properties. Tracing its origins to pioneering molecular layering and atomic layer deposition work in the mid‐20th century, this multifaceted field has remarkably diversified to include molecular layer deposition (MLD), atomic layer etching (ALE), area‐selective deposition (ASD), and vapor‐phase infiltration (VPI) processes. ALP is making great impacts across diverse disciplines – facilitating semiconductor miniaturization through ultrathin dielectric films, improving battery materials and engineering catalysts for energy applications, creating bioactive surfaces for advanced biomaterials, and promoting sustainable membranes for environmental remediation. As ALP techniques continue evolving through integration with additive manufacturing, machine learning, and in situ diagnostics, new frontiers in materials design are emerging, driven by the growing focus on environmental considerations like renewable precursors, energy‐efficient processes, and waste minimization. This perspective article examines ALP's historical development, highlights current state‐of‐the‐art applications across selected fields, and provides insights into the anticipated future trajectory, emerging application domains, and the pivotal role of academic‐industry‐research laboratory collaborations in catalyzing ALP innovations and facilitating its widespread adoption as a transformative manufacturing platform.

CuBe: a geminivirus-based copper-regulated expression system suitable for post-harvest activation.

The growing demand for sustainable platforms for biomolecule manufacturing has fuelled the development of plant-based production systems. Agroinfiltration, the current industry standard, offers several advantages but faces limitations for large-scale production due to high operational costs and batch-to-batch variability. Alternatively, here, we describe the CuBe system, a novel bean yellow dwarf virus (BeYDV)-derived conditional replicative expression platform stably transformed in Nicotiana benthamiana and activated by copper sulphate (CuSO4), an inexpensive and widely used agricultural input. The CuBe system utilizes a synthetic circuit of four genetic modules integrated into the plant genome: (i) a replicative vector harbouring the gene of interest (GOI) flanked by cis-acting elements for geminiviral replication and novelly arranged to enable transgene transcription exclusively upon formation of the circular replicon, (ii) copper-inducible Rep/RepA proteins essential for replicon formation, (iii) the yeast-derived CUP2-Gal4 copper-responsive transcriptional activator for Rep/RepA expression, and (iv) a copper-inducible Flp recombinase to minimize basal Rep/RepA expression. CuSO4 application triggers the activation of the system, leading to the formation of extrachromosomal replicons, expression of the GOI, and accumulation of the desired recombinant protein. We demonstrate the functionality of the CuBe system in N. benthamiana plants expressing high levels of eGFP and an anti-SARS-CoV-2 antibody upon copper treatment. Notably, the system is functional in post-harvest applications, a strategy with high potential impact for large-scale biomanufacturing. This work presents the CuBe system as a promising alternative to agroinfiltration for cost-effective and scalable production of recombinant proteins in plants.