Many soft matter systems in manufacturing industry exist as solutions, e.g., polymer solutions/gels, and colloidal suspensions. A soft matter solution is made by dissolving one or more different soft materials in a liquid. Soft matter solutions usually show fascinating phase structure and dynamic properties. They have found wide applications in intelligent manufacturing technology such as functional coating and ink-jet printing. In this talk, I will present my recent works on the multiscale modeling and computations of some typical multiphase soft matter solutions such as simple binary solutions, polymer solutions, and diblock copolymer solutions. I will introduce some general major difficulties for the theoretical modeling and computations of these multiphase solutions, for example, free-interface dynamics, contact line dynamics, complex substrate topography, evaporation dynamics, and phase separation dynamics. I then present our methods of overcoming these difficulties. In addition, we have recently noticed a natural combination of the deep learning methods with promising “brute forces” with “intelligent” variational principles of physics. This combination provides a very powerful numerical method of solving various problems in soft matter physics. I will also give some examples to show how we use this method to study the dynamics of soft matter solutions.

Greater uncertainty in global trade flows and black swan events, such as COVID-19, have increasingly challenged the current supply chain business model. Digital technologies have been recognized as a key enabler for enabling resilient and responsive supply chains. In this seminar, I would like to share about the ongoing research program Supply Chain 4.0, which aims to research and co-develop digital and automation technologies with industry members to enable responsive, resilient and secured supply chain management processes to prepare company for the ever volatile, uncertain, complex, and ambiguous (VUCA) global supply chain environment. Details of the three research theme will be shared, which including Supply Chain Connectivity, Data-Driven Optimization and Smart Warehouse Automation for next generation logistics.

As a key enabling technology of Industry 4.0, Digital Twin has been applied to various industrial domains covering different lifecycle phases to provide a comprehensive virtual description of products and systems. While the benefit of Digital Twin is undoubted, it faces challenges when dealing with certain complex industrial systems, which requires integrating all relevant data, information and knowledge involving multiple domains and across the entire lifecycle. Semantic technologies, such as ontology engineering and knowledge graphs, provide potential solutions by empowering Digital Twins with augmented interoperability and cognitive capabilities. The Model Based Systems Engineering (MBSE) technology facilitates the formalized application of modeling to support cross-domain and cross-lifecycle information representation. Enabled by these state-of-the-art technologies, the Cognitive Digital Twin (CDT) concept has been recently proposed which reveals a promising evolution of the current Digital Twin concept towards a more intelligent, comprehensive, and full lifecycle representation of complex systems. In this seminar, the concept of CDT and its key features will be presented, together with application cases developed in collaborative projects with EU industries.

Materials featuring three-dimensional microarchitectures exhibit various extreme functional properties, including negative thermal expansion, high-efficiency electromechanical conversion, ultrahigh stiffness and damage tolerance. Their remarkable properties are dominated by both the parent material and their microarchitecture and thus, they are commonly referred to as architected metamaterials. The rapid progress in 3D printing techniques has enabled the creation of architected metamaterials and unfolded many potential applications. However, the characterization and applicability of these metamaterials are significantly limited by the manufacturing scalability. Additionally, most currently available 3D printing methods only handle single structural materials, and it remains a challenge to 3D print multifunctional architected metamaterials. This presentation will focus on 3D printing techniques that address these key challenges, the investigation of elusive metamaterial properties, as well as the design and manufacturing of multifunctional architected metamaterials. The talk will first introduce a large-area projection stereolithography system capable of manufacturing submeter scale objects with micro-scale architectures, which enables the investigation of size effect in high-temperature ceramics and fracture toughness of mechanical metamaterials. This talk will then demonstrate the design and multi-material additive manufacturing of a series of robotic metamaterials that seamlessly integrate piezo-active, structural and conducting architectures. These robotic metamaterials can directly serve as micro-robots and achieve multi-degree-of-freedom motion, proprioception as well as responses to remote stimuli. All these works contribute to the understanding of the process-structure-property relationship of architected metamaterials as well as the creation of future intelligent materials and devices.

China Intelligent Manufacturing 2025 is a vital national strategy for developing China as a world super power in manufacturing, which can make everything with high quality and efficiency. In this strategy, the critical but most difficult objective is to build smart machine tools. Smart machine tools can efficiently cut workpieces into qualified parts without manual operation. On these machines, cutters can be automatically measured for wear with a sensor (an on-machine tool setter) during machining, and then the following toolpath is compensated with the tool wear. Besides, the workpiece is measured with a sensor (a touch probe) right after each geometric feature is cut, and re-machining of the out-of-tolerance area is automatically planned. However, smart machine tools have not been built and applied in the manufacturing industry. It is urgent and important for Chinese researchers to develop the kernel techniques of smart machine tools. Prof. Chen is leading an international research team to conduct advanced research on smart machine tools in the following topics: (a) automatic multi-axis tool path generation and compensation, (b) automatic, in-process and on-machine cutter inspection, and (c) automatic, in-process and on-machine workpiece measurement. His team has successfully addressed many technical challenges and developed several new products for smart machine tools.

The performance of semiconductor integrated
circuits can be improved through 3Dintegration
of additional layers in the post-Moore era.
However，3Dintegrationofoptoelectronics
remains a technological challenge.3Dprinting
has been emerging as a disruptive approach to
manufacturing due toitssimpledesign-friendly
manner. Over the past decadesscientistsand
engineers have continually developed methods
for a diverse selection of materialshigh
precision and throughput that are essential for
3D optoelectronic devices but so far this still
remains a great challenge. In this talkIwill
introduce my
study
of
developing
high-performance 3D nanoprintingtechniques
for advanced 3Doptoelectronics.Thestudy
consists of two parts:(1)developmentof
advanced 3D printing techniques for functional
semiconductor materialswhere nanopipette
confined supersaturation is localized for creating
freeform perovskites 3D nanostructures as3D
nanopixels
and
heterostructures.(2)
Development of parallel 3D nanoprinting in a
liquid meniscus or a droplet form todeliver
materials ink that improves the throughputThis
study will enable a true manufacturing platform
for next-generation 3D optoelectronic devices.
making a great impact oninterdisciplinary
manufacturing and materials science fields such
as stretchable electronicsphotonicsand
biomedical engineering.

A mircoLED display is a self-emissive display
comprising millions of micrometer-scale LEDsIt
potentially outperform LCD and OLED display not
only because its higher power efficiency, better
image quality, wider color gamut but also due to its
good scalability, transparency, flexibility and other
characteristics. lt is an emerging technology
expected to disrupt the display market. For
manufacturing microLED displays, tens of millions
of microscopic LED chips need to be transferred
and assembled at a high through-put with an
ultra-high yield. There is significant investment
across both industry and academia, and the
technology is advancing very quickly in this field;
however, there is no existing approach that has
demonstrated a cost-effective way of doing it. in
this talk, I will introduce the background of the
application and review state-of-the-art mass
transfer development for microLED display
manufacturing. Methods including elastomeric
stamping, fluidic assembly, laser printing, etc. will
be discussed and assessed in details.

Visualizing the flow physics and structural dynamics
is critical to our comprehension of fluid-structure
interaction phenomena, which are pervasive in
engineering and biological systems. Traditional
measurement techniques relyon single-input
sensors and optical diagnostic tools, which often fail
to capture fluid-structure interactions that are
transient in nature, hindering our understanding
of their physical underpinnings. In this talk, i will
present my recent effort in the manufacturing of
multi-input smart sensors that are capable of
capturing velocity and pressure of an airflow, and
quantifying the deformation and UV damage of a
structure. This effort is complemented by the
development of a multi-input optical measurement
technique, which can accurately capture highly
transient fluid-structure interactions. Finally, I will
briefly discuss other techniques I have employed
for the study of fluid-structure interactions, ranging
from evolutionary algorithm-based optimization of
highway infrastructures, to
continuum
mechanics-based modeling of soft active sensors
and actuators, and data-driven modeling of animal
swimming.

The free-form surface, also termed manifold, is a
smooth 3D skin that contains aesthetic value and
presents functionalities. With the integration of
mathematics, computer-aided design, and
construction techniques, people can bring the
free-form surface into reality. However, how to
achieve an optimal layout on the free-form surface is
still an open topic. In this talk, I will first introduce
my research efforts on topology optimization on the
freeform surface using the extended level set method
and conformal mapping theory. Next, I will present
my work on optimizing a typical adaptive surface- the
origami structure, which can transform from
flattening 2D status to a complex 3D design at a given
crease pattern. In terms of fabricating thin shell
surfaces, I will briefly introduce our surface weaving
method, which can directly construct a 3D surface by
weaving two groups of computed strips. The future
research directions and applications will be discussed
at the end.

This talk will present our projects as examples
which demonstrate the use of a "art to science"
research methodology. Our team adopts a
creative-driven interdisciplinary approach in their
fundamental and applied research on wearable
technologies and its applications to effectively
enable knowledge transfer and realize market
applications. In short, these topics are centered on
understanding the customer experience, social
needs, and the past to shape the future. Aesthetic
research method (or Design thinking research) thus
provides a creative approach try to solve complex
problems in a user-centric manner. These research
works have contributed to discoveries, inventions
and developments which have been adopted by
some of the largest textile manufacturers and
implemented into their products, deriving concrete
financial gains. Yet, we believe there is still room for
improvement and we hope we can do better in the
future.