Alloy design for laser powder bed fusion additive manufacturing:a critical review

Metal additive manufacturing(AM)has been extensively studied in recent decades.Despite the significant progress achieved in manufacturing complex shapes and structures,challenges such as severe cracking when using existing alloys for laser powder bed fusion(L-PBF)AM have persisted.These challenges arise because commercial alloys are primarily designed for conventional casting or forging processes,overlooking the fast cooling rates,steep temperature gradients and multiple thermal cycles of L-PBF.To address this,there is an urgent need to develop novel alloys specifically tailored for L-PBF technologies.This review provides a comprehensive summary of the strategies employed in alloy design for L-PBF.It aims to guide future research on designing novel alloys dedicated to L-PBF instead of adapting existing alloys.The review begins by discussing the features of the L-PBF processes,focusing on rapid solidification and intrinsic heat treatment.Next,the printability of the four main existing alloys(Fe-,Ni-,Al-and Ti-based alloys)is critically assessed,with a comparison of their conventional weldability.It was found that the weldability criteria are not always applicable in estimating printability.Furthermore,the review presents recent advances in alloy development and associated strategies,categorizing them into crack mitigation-oriented,microstructure manipulation-oriented and machine learning-assisted approaches.Lastly,an outlook and suggestions are given to highlight the issues that need to be addressed in future work.

Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.

Rationally designing electrolyte additives for highly improving cyclability of LiNi_(0.5)Mn_(1.5)O_(4)/Graphite cells

High voltage is necessary for high energy lithium-ion batteries but difficult to achieve because of the highly deteriorated cyclability of the batteries.A novel strategy is developed to extend cyclability of a high voltage lithium-ion battery,LiNi_(0.5)Mn_(1.5)O_(4)/Graphite(LNMO/Graphite)cell,which emphasizes a rational design of an electrolyte additive that can effectively construct protective interphases on anode and cathode and highly eliminate the effect of hydrogen fluoride(HF).5-Trifluoromethylpyridine-trime thyl lithium borate(LTFMP-TMB),is synthesized,featuring with multi-functionalities.Its anion TFMPTMB-tends to be enriched on cathode and can be preferentially oxidized yielding TMB and radical TFMP-.Both TMB and radical TFMP can combine HF and thus eliminate the detrimental effect of HF on cathode,while the TMB dragged on cathode thus takes a preferential oxidation and constructs a protective cathode interphase.On the other hand,LTFMP-TMB is preferentially reduced on anode and constructs a protective anode interphase.Consequently,a small amount of LTFMP-TMB(0.2%)in 1.0 M LiPF6in EC/DEC/EMC(3/2/5,wt%)results in a highly improved cyclability of LNMO/Graphite cell,with the capacity retention enhanced from 52%to 80%after 150 cycles at 0.5 C between 3.5 and 4.8 V.The as-developed strategy provides a model of designing electrolyte additives for improving cyclability of high voltage batteries.

Electrolyte Design for Low‑Temperature Li‑Metal Batteries:Challenges and Prospects

Electrolyte design holds the greatest opportunity for the development of batteries that are capable of sub-zero temperature operation.To get the most energy storage out of the battery at low temperatures,improvements in electrolyte chemistry need to be coupled with optimized electrode materials and tailored electrolyte/electrode interphases.Herein,this review critically outlines electrolytes’limiting factors,including reduced ionic conductivity,large de-solvation energy,sluggish charge transfer,and slow Li-ion transportation across the electrolyte/electrode interphases,which affect the low-temperature performance of Li-metal batteries.Detailed theoretical derivations that explain the explicit influence of temperature on battery performance are presented to deepen understanding.Emerging improvement strategies from the aspects of electrolyte design and electrolyte/electrode interphase engineering are summarized and rigorously compared.Perspectives on future research are proposed to guide the ongoing exploration for better low-temperature Li-metal batteries.

Magnesium-based biomaterials for coordinated tissue repair:A comprehensive overview of design strategies,advantages,and challenges

Magnesium-based biomaterials(MBMs)are one of the most promising materials for tissue engineering due to their unique mechanical properties and excellent functional properties.This review describes the development,advantages,and challenges of MBMs for biomedical applications,especially for tissue repair and regeneration.The history of the use of MBMs from the beginning of the 20th century is traced,and the transformative advances in contemporary applications of MBMs in areas such as orthopedics and cardiovascular surgery are emphasized.The review also provides insight into the signaling pathways affected by MBMs,such as the PI3K/Akt and RANKL/RANK/OPG pathways,which are critical for osteogenesis and angiogenesis.The review advocates that future research should focus on optimizing alloy compositions,surface modification and exploring innovative technologies such as 3D printing to improve the efficacy of MBMs in complex tissue repair.The potential of MBMs to tissue engineering and regenerative medicine is significant,urging further exploration and interdisciplinary collaboration to maximize their therapeutic effects.

Multi-Stage Multidisciplinary Design Optimization Method for Enhancing Complete Artillery Internal Ballistic Firing Performance

To enhance the comprehensive performance of artillery internal ballistics—encompassing power,accuracy,and service life—this study proposed a multi-stage multidisciplinary design optimization(MS-MDO)method.First,the comprehensive artillery internal ballistic dynamics(AIBD)model,based on propellant combustion,rotation band engraving,projectile axial motion,and rifling wear models,was established and validated.This model was systematically decomposed into subsystems from a system engineering perspective.The study then detailed the MS-MDO methodology,which included Stage I(MDO stage)employing an improved collaborative optimization method for consistent design variables,and Stage II(Performance Optimization)focusing on the independent optimization of local design variables and performance metrics.The methodology was applied to the AIBD problem.Results demonstrated that the MS-MDO method in Stage I effectively reduced iteration and evaluation counts,thereby accelerating system-level convergence.Meanwhile,Stage II optimization markedly enhanced overall performance.These comprehensive evaluation results affirmed the effectiveness of the MS-MDO method.

Development of a Decision Aid for Family Surrogate Decision Makers of Critically Ill Patients Requiring Renal Replacement Therapy in ICU:A User-Centered Design for Rapid Prototyping

Objectives Renal replacement therapy(RRT)is increasingly adopted for critically ill patients diagnosed with acute kidney injury,but the optimal time for initiation remains unclear and prognosis is uncertain,leading to medical complexity,ethical conflicts,and decision dilemmas in intensive care unit(ICU)settings.This study aimed to develop a decision aid(DA)for the family surrogate of critically ill patients to support their engagement in shared decision-making process with clinicians.Methods Development of DA employed a systematic process with user-centered design(UCD)principle,which included:(i)competitive analysis:searched,screened,and assessed the existing DAs to gather insights for design strategies,developmental techniques,and functionalities;(ii)user needs assessment:interviewed family surrogates in our hospital to explore target user group's decision-making experience and identify their unmet needs;(iii)evidence syntheses:integrate latest clinical evidence and pertinent information to inform the content development of DA.Results The competitive analysis included 16 relevant DAs,from which we derived valuable insights using existing resources.User decision needs were explored among a cohort of 15 family surrogates,revealing four thematic issues in decision-making,including stuck into dilemmas,sense of uncertainty,limited capacity,and delayed decision confirmation.A total of 27 articles were included for evidence syntheses.Relevant decision making knowledge on disease and treatment,as delineated in the literature sourced from decision support system or clinical guidelines,were formatted as the foundational knowledge base.Twenty-one items of evidence were extracted and integrated into the content panels of benefits and risks of RRT,possible outcomes,and reasons to choose.The DA was drafted into a web-based phototype using the elements of UCD.This platform could guide users in their preparation of decision-making through a sequential four-step process:identifying treatment options,weighing the benefits and risks,clarifying personal preferences and values,and formulating a schedule for formal shared decision-making with clinicians.Conclusions We developed a rapid prototype of DA tailored for family surrogate decision makers of critically ill patients in need of RRT in ICU setting.Future studies are needed to evaluate its usability,feasibility,and clinical effects of this intervention.

Optimization of magnetic field design for Hall thrusters based on a genetic algorithm

Magnetic field design is essential for the operation of Hall thrusters.This study focuses on utilizing a genetic algorithm to optimize the magnetic field configuration of SPT70.A 2D hybrid PIC-DSMC and channel-wall erosion model are employed to analyze the plume divergence angle and wall erosion rate,while a Farady probe measurement and laser profilometry system are set up to verify the simulation results.The results demonstrate that the genetic algorithm contributes to reducing the divergence angle of the thruster plumes and alleviating the impact of high-energy particles on the discharge channel wall,reducing the erosion by 5.5%and 2.7%,respectively.Further analysis indicates that the change from a divergent magnetic field to a convergent magnetic field,combined with the upstream shift of the ionization region,contributes to the improving the operation of the Hall thruster.

SAR regional all-azimuth observation orbit design for target 3D reconstruction

Three-dimensional(3D) synthetic aperture radar(SAR)extends the conventional 2D images into 3D features by several acquisitions in different aspects. Compared with 3D techniques via multiple observations in elevation, e.g. SAR interferometry(InSAR) and SAR tomography(TomoSAR), holographic SAR can retrieve 3D structure by observations in azimuth. This paper focuses on designing a novel type of orbit to achieve SAR regional all-azimuth observation(AAO) for embedded targets detection and holographic 3D reconstruction. The ground tracks of the AAO orbit separate the earth surface into grids. Target in these grids can be accessed with an azimuth angle span of360°, which is similar to the flight path of airborne circular SAR(CSAR). Inspired from the successive coverage orbits of optical sensors, several optimizations are made in the proposed method to ensure favorable grazing angles, the performance of 3D reconstruction, and long-term supervision for SAR sensors. Simulation experiments show the regional AAO can be completed within five hours. In addition, a second AAO of the same area can be duplicated in two days. Finally, an airborne SAR data process result is presented to illustrate the significance of AAO in 3D reconstruction.

Optimization of Callus Induction Medium for Schisandga chinensis Baill via Uniform Design

[Objective]This study was to optimize callus induction medium for Schisandga chinensis Baill.[Method]Using callus induction rate as an indicator,uniform design was employed to optimize hormone combination at poly-factors and poly-levels for callus induction from Schisandga chinensis Baill.[Results]Optimal hormone combinations depended on different explants：optimum medium for both tender leaf and petiole was MS ＋3 mg/L 6-BA,for stem segment was MS ＋3 mg/L 6-BA ＋0.6 mg/L NAA.[Conclusion]Uniform design is a time-saving and convenient method for the optimum medium for callus and yields a higher callus induction rate.

Uniform Design for Optimizating Regeneration Shoots Directly from Tender Leaves and Plant Regeneration System of Rhododendron chrysanthum Pall.

[Objective] The experimental was aimed to screen the optimum regeneration shoot induction media and rooting media for tender leaves of Rhododendron chrysanthum Pall.[Method] The tender leaves of Rhododendron chrysanthum Pall were taken as explants to select the optimum bud induction media and rooting media through uniform design and the screening results were verified.[Result] The optimum media for regeneration shoot of Rhododendron chrysanthum Pall contained 1/4 MS,3.70 mg/L ZT, 0.02 mg/L IAA and 1.00 mg/L KT and its induction rate was 95.5% and the rooting media contained modified MS, 0.10 mg/L IAA and 0.07 mg/L NAA and its rooting rate was 98%. [Conclusion] Through this experiment, regeneration systems for regeneration shoot and regenerated plant from tender leaves of Rhododendron chrysanthum Pall were created successfully.

Structural Carpentry in Qing Dynasty-A Framework for the Hierarchically Modularized Chinese Timber Structural Design

This article, by using mathematical expressions, offers a scientific framework for understanding how the grading system of Qing′s structural carpentry determines the design and construction in the grand style timber architecture.The Qing′s grand style timber structure, which is ready for prefabrication and assembly, is extremely hierarchical oriented and significantly standardized. The general procedure in designing a grand style timber structure is to start with the grade that defines the basic module (dou kou); next comes with the number of bracket set (cuan), the number of longitudinal bays and the number of purlins which affect its plan and cross section; thirdly choose a roof type that determines its longitudinal section and the facade as well. A series of formulae are conducted to help depict the layout, cross sectional roof curvature and special longitudinal treatments in 4 sloped and 9 spined roofs respectively.

Design Principles and Mechanistic Understandings of Non-Noble-Metal Bifunctional Electrocatalysts for Zinc-Air Batteries

Zinc-air batteries(ZABs)are promising energy storage systems because of high theoretical energy density,safety,low cost,and abundance of zinc.However,the slow multi-step reaction of oxygen and heavy reliance on noble-metal catalysts hinder the practical applications of ZABs.Therefore,feasible and advanced non-noble-metal elec-trocatalysts for air cathodes need to be identified to promote the oxygen catalytic reaction.In this review,we initially introduced the advancement of ZABs in the past two decades and provided an overview of key developments in this field.Then,we discussed the work-ing mechanism and the design of bifunctional electrocatalysts from the perspective of morphology design,crystal structure tuning,interface strategy,and atomic engineering.We also included theoretical studies,machine learning,and advanced characterization technologies to provide a comprehensive understanding of the structure-performance relationship of electrocatalysts and the reaction pathways of the oxygen redox reactions.Finally,we discussed the challenges and prospects related to designing advanced non-noble-metal bifunctional electrocatalysts for ZABs.

Machine learning for membrane design and discovery

Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and environment.This review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isfirst provided with the current bottlenecks and potential solutions.Through an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation membranes.Furthermore,the best practices of integrating ML methods and specific application targets in membrane design and discovery are presented with an ideal paradigm proposed.The challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.

Recent advances in cobalt phosphide-based materials for electrocatalytic water splitting:From catalytic mechanism and synthesis method to optimization design

Electrochemical water splitting has long been considered an effective energy conversion technology for trans-ferring intermittent renewable electricity into hydrogen fuel,and the exploration of cost-effective and high-performance electrocatalysts is crucial in making electrolyzed water technology commercially viable.Cobalt phosphide(Co-P)has emerged as a catalyst of high potential owing to its high catalytic activity and durability in water splitting.This paper systematically reviews the latest advances in the development of Co-P-based materials for use in water splitting.The essential effects of P in enhancing the catalytic performance of the hydrogen evolution reaction and oxygen evolution reaction are first outlined.Then,versatile synthesis techniques for Co-P electrocatalysts are summarized,followed by advanced strategies to enhance the electrocatalytic performance of Co-P materials,including heteroatom doping,composite construction,integration with well-conductive sub-strates,and structure control from the viewpoint of experiment.Along with these optimization strategies,the understanding of the inherent mechanism of enhanced catalytic performance is also discussed.Finally,some existing challenges in the development of highly active and stable Co-P-based materials are clarified,and pro-spective directions for prompting the wide commercialization of water electrolysis technology are proposed.

Step‑by‑Step Modulation of Crystalline Features and Exciton Kinetics for 19.2%Efficiency Ortho‑Xylene Processed Organic Solar Cells

With plenty of popular and effective ternary organic solar cells(OSCs)construction strategies proposed and applied,its power conversion efficiencies(PCEs)have come to a new level of over 19%in single-junction devices.However,previous studies are heavily based in chloroform(CF)leaving behind substantial knowledge deficiencies in understanding the influence of solvent choice when introducing a third component.Herein,we present a case where a newly designed asymmetric small molecular acceptor using fluoro-methoxylated end-group modification strategy,named BTP-BO-3FO with enlarged bandgap,brings different morphological evolution and performance improvement effect on host system PM6:BTP-eC9,processed by CF and ortho-xylene(o-XY).With detailed analyses supported by a series of experiments,the best PCE of 19.24%for green solvent-processed OSCs is found to be a fruit of finely tuned crystalline ordering and general aggregation motif,which furthermore nourishes a favorable charge generation and recombination behavior.Likewise,over 19%PCE can be achieved by replacing spin-coating with blade coating for active layer deposition.This work focuses on understanding the commonly met yet frequently ignored issues when building ternary blends to demonstrate cutting-edge device performance,hence,will be instructive to other ternary OSC works in the future.

OptoGPT: A foundation model for inverse design in optical multilayer thin film structures

Optical multilayer thin film structures have been widely used in numerous photonic applications.However,existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design targets,or are difficult to suit for different types of structures,e.g.,designing for different materials at each layer.These methods also cannot accommodate versatile design situations under different angles and polarizations.In addition,how to benefit practical fabrications and manufacturing has not been extensively considered yet.In this work,we introduce OptoGPT(Opto Generative Pretrained Transformer),a decoder-only transformer,to solve all these drawbacks and issues simultaneously.

An evaluation of force-based design vs.direct displacement-based design of jointed precast post-tensioned wall systems

The unique features of jointed post-tensioned wall systems, which include minimum structural damage and re-centering capability when subjected to earthquake lateral loads, are the result of using unbonded post-tensioning to attach the walls to the foundation, along with employing energy dissipating shear connectors between the walls. Using acceptance criteria defined in terms of inter-story drift, residual drift, and floor acceleration, this study presents a multiplelevel performance-based seismic evaluation of two five-story unbonded post-tensioned jointed precast wall systems. The design and analysis of these two wall systems, established as the direct displacement-based and force-based solutions for a prototype building used in the PREcast Seismic Structural Systems （PRESSS） program, were performed at 60% scale so that the analysis model could be validated using the PRESSS test data. Both buildings satisfied the performance criteria at four levels of earthquake motions although the design base shear of the direct displacement-based jointed wall system was 50% of that demanded by the force-based design method. The study also investigated the feasibility of controlling the maximum transient inter-story drift in a jointed wall system by increasing the number of energy dissipating shear connectors between the walls but without significantly affecting its re-centering capability.

A Finite and Instantaneous Screw Based Approach for Topology Design and Kinematic Analysis of 5-Axis Parallel Kinematic Machines

Unifying the models for topology design and kinematic analysis has long been a desire for the research of parallel kinematic machines(PKMs). This requires that analytical description, formulation and operation for both finite and instantaneous motions are performed by the same mathematical tool. Based upon finite and instantaneous screw theory, a unified and systematic approach for topology design and kinematic analysis of PKMs is proposed in this paper. Using the derivative mapping between finite and instantaneous screws built in the authors’ previous work, the finite and instantaneous motions of PKMs are analytically described by the simple and non?redundant screws in quasi?vector and vector forms. And topological and parametric models of PKMs are algebraically formulated and related. These related topological and parametric models are ready to do type synthesis and kinematic analysis of PKMs under the unified framework of screw theory. In order to show the validity of the proposed approach, a kind of two?translational and three?rotational(2T3R)5?axis PKMs is taken as example. Numerous new structures of the 2T3R PKMs are synthe?sized as the results of topology design, and their Jacobian matrix is obtained easily for parameter optimization and performance evaluation. Some of the synthesized PKMs have outstanding capabilities in terms of large workspaces and flexible orientations, and have great potential for industrial applications of machining and manufacture. Among them, METROM PKM is a typical example which has attracted a lot of attention from global companies and already been developed as commercial products. The approach is a general and unified approach that can be used in the innovative design of different kinds of PKMs.

Product family modeling technology for customized cosmetic packaging design based on basic-element theory

Background:As the market demands change,SMEs(small and medium-sized enterprises)have long faced many design issues,including high costs,lengthy cycles,and insufficient innovation.These issues are especially noticeable in the domain of cosmetic packaging design.Objective:To explore innovative product family modeling methods and configuration design processes to improve the efficiency of enterprise cosmetic packaging design and develop the design for mass customization.Methods:To accomplish this objective,the basic-element theory has been introduced and applied to the design and development system of the product family.Results:By examining the mapping relationships between the demand domain,functional domain,technology domain,and structure domain,four interrelated models have been developed,including the demand model,functional model,technology model,and structure model.Together,these models form the mechanism and methodology of product family modeling,specifically for cosmetic packaging design.Through an analysis of a case study on men’s cosmetic packaging design,the feasibility of the proposed product family modeling technology has been demonstrated in terms of customized cosmetic packaging design,and the design efficiency has been enhanced.Conclusion:The product family modeling technology employs a formalized element as a module configuration design language,permeating throughout the entire development cycle of cosmetic packaging design,thus facilitating a structured and modularized configuration design process for the product family system.The application of the basic-element principle in product family modeling technology contributes to the enrichment of the research field surrounding cosmetic packaging product family configuration design,while also providing valuable methods and references for enterprises aiming to elevate the efficiency of cosmetic packaging design for the mass customization product model.