Soft Matter Emerging Investigator – Daisuke Aoki

Daisuke Aoki currently serves as an Assistant Professor in the Department of Chemical Science and Engineering at Tokyo Institute of Technology. He was born in Gunma Prefecture (Japan) in 1983. After he had earned a B.E. and a M.E. in Polymer Engineering at Yamagata University under the supervision of Prof. O. Haba, he obtained his PhD from Tokyo Institute of Technology in 2014 under the tutelage of Prof. T. Takata working on topological changes in rotaxane-based polymers. Between 2014 and 2017, he served as a specially appointed Assistant Professor in the group of Prof. T. Takata. In 2017, he was appointed to his current position at Tokyo Institute of Technology in the group of Prof. H. Otsuka. His research is focused on the synthesis and characterization of functional polymers with applications in materials science. He can be found on Twitter @dice_k_polymer.

Read Daisuke’s Emerging Investigator article “Characterization of N-phenylmaleimide-terminated poly(ethylene glycol)s and their application to a tetra-arm poly(ethylene glycol) gel” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

 

How do you feel about Soft Matter as a place to publish research on this topic?

Soft Matter focusing on innovative soft matter topic, is great place to me, since I really like gels and elastomers.

What aspect of your work are you most excited about at the moment and what do you find most challenging about your research?

I’m really excited about project on polymer topology which govern the macroscopic properties and function. The most challenging on my research is to build special topology with polymers and find special function derived from topology.

In your opinion, what are the most important questions to be asked/answered in this field of research?

Are you excited for your result and research?

Can you share one piece of career-related advice or wisdom with other early career scientists?

“Connecting the dots” I like this phrase in Steve Jobs’ speech. I believe that continuation of research leads to connecting dots in chemistry and paving the way toward new chemistry.

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Soft Matter Emerging Investigator – Michael Bartlett

Michael D. Bartlett is an Assistant Professor of Mechanical Engineering and in the Macromolecules Innovation Institute (MII) at Virginia Tech. He received his B.S.E. from the University of Michigan, Ph.D. from the University of Massachusetts Amherst, and was a postdoctoral fellow at Carnegie Mellon University. He leads the Soft Materials and Structures Lab, which investigates and creates multifunctional soft materials and composites with highly controllable mechanical and functional properties for deformable electronics and soft robotics, adaptive materials, and switchable adhesives. More information can be found at www.bartlett.me.vt.edu and he can be found on Twitter @SMSLaboratory.

Read Michael’s Emerging Investigator article “Deterministic control of adhesive crack propagation through jamming based switchable adhesives” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

 

How do you feel about Soft Matter as a place to publish research on this topic?

The blend of materials, physics, and chemistry makes Soft Matter a great outlet for research on soft materials.

Can you share one piece of career-related advice or wisdom with other early career scientists?

Do not be afraid to fail. Some of the most challenging topics or experiments are also the most exciting.

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Soft Matter Emerging Investigator – Juliane Simmchen

Juliane started her research group in 2016 as a freigeist fellow of the Volkswagen foundation. After doing her PhD at the Autonomous University of Barcelona until 2014, she joined the group of Samuel Sanchez in the department of Prof. Siegfried Dietrich at MPI Stuttgart for a PostDoc until 2015. She is interested in the basic mechanisms that drive micromotion as well as targeted material design for future microswimmer applications. She can be found on Twitter @julianesimmchen.

Read Juliane’s Emerging Investigator article “Apparent phototaxis enabled by Brownian motion” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

 

How do you feel about Soft Matter as a place to publish research on this topic?

Soft Matter is the flagship journal of our community and besides that, we chose it for the first independent publication of Linlin Wang, my first PhD student (Soft Matter, 2018,14, 6969-6973). So my connection to this journal is almost a sentimental one…

What aspect of your work are you most excited about at the moment and what do you find most challenging about your research?

Active matter is operating right at the border between living and non living systems. Especially the interactions in complex environments are sometimes stunningly similar to what we observe in e.g. bacteria. Scientifically seen, these intricate connections and the fine tuning of these systems are so fascinating, but this is fun. The challenge is to integrate the next generation of scientists into these microadventures and show them how beautiful the connections are. 

In your opinion, what are the most important questions to be asked/answered in this field of research?

There are far reaching discoveries to be made in colloidal assembly for building materials and I am sure, some particularly interesting ones will contain active contributions.  

Can you share one piece of career-related advice or wisdom with other early career scientists?

‘The test of all knowledge is experiment’ – (my favorite citation from Feynman) and if you enjoy science, stay flexible and enjoy the changes that come with it. 

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Soft Matter Emerging Investigator – Nicoletta Gnan

Nicoletta Gnan is a researcher at the Institute for Complex Systems of the Italian National Research Council (CNR). She earned her Masters degree in Physics from the University of Rome “Sapienza” in 2006, then spent three years as PhD fellow at the Roskilde University in Denmark studying the structure and dynamics of a special class of liquids and glasses. Before joining the CNR in 2013, initially as a postdoc and later as a permanent researcher, she received a postdoctoral fellowship at the University of Rome “Sapienza” to perform simulations of colloidal particles in critical solvents. Her research interests are the numerical modelling of colloidal particles, the investigation of effective interactions in colloidal dispersions and the study of the collective behaviour of passive and active systems.

Read Nicoletta’s Emerging Investigator article “Universality class of the motility-induced critical point in large scale off-lattice simulations of active particles” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

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Soft Matter Emerging Investigator – Timm Krüger

Timm Krüger is Reader in Chemical Engineering at the University of Edinburgh. His group investigates microfluidic systems and blood flow via modelling and computer simulations. He can be found on Twitter @timmkrueger.

Read Timm’s Emerging Investigator article “Emergent cell-free layer asymmetry and biased haematocrit partition in a biomimetic vascular network of successive bifurcations” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

 

How do you feel about Soft Matter as a place to publish research on this topic?

Soft Matter is an excellent platform for interdisciplinary research as the journal cuts across traditional disciplines.

What aspect of your work are you most excited about at the moment and what do you find most challenging about your research?

The most challenging aspect is to perform research with collaborators in biology and medicine to address topical problems that cannot be answered within a single discipline.

In your opinion, what are the most important questions to be asked/answered in this field of research?

A big open question is how the particulate nature of blood is affecting organ function and cancer development.

Can you share one piece of career-related advice or wisdom with other early career scientists?

If you could write two mediocre papers or one excellent paper, always write the excellent paper.

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Soft Matter Emerging Investigator – Jiajia Zhou

Jiajia Zhou received his BSc in physics from Peking University in 2002. He then went to Canada and finished his PhD in physics from McMaster University in 2010, under the supervision of Prof. An-Chang Shi. He was a postdoctoral researcher from 2011 to 2015 at University Mainz in Germany with Prof. Friederike Schmid. He joined Beihang University as an Associate Professor in 2015, and moved to South China University of Technology in 2021. His research focuses on theoretical modelling and computer simulation of soft matter.

Read Jiajia’s Emerging Investigator article “Wetting equilibrium in a rectangular channel” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

 

How do you feel about Soft Matter as a place to publish research on this topic?

Soft Matter is a great platform to publish our research on soft matter.

What aspect of your work are you most excited about at the moment and what do you find most challenging about your research?

My research focuses on the theory and simulation of soft matter dynamics. I’m most excited about applying our theoretical formulation (Onsager principle) to various different systems, making predictions to compare with simulations and experiments. The most challenging aspect of our research is to construct a model that is as simple as possible, but not simpler (borrowed from Einstein).

In your opinion, what are the most important questions to be asked/answered in this field of research?

Soft matter systems involve many different physical/chemical processes, and often out of equilibrium. For us, the most important question is how to derive the non-equilibrium dynamical equations that are thermodynamically consistent, and can be verified by experiments.

Can you share one piece of career-related advice or wisdom with other early career scientists?

Find a good mentor. I am fortunate to work with Prof Masao Doi when I started my independent research. The influence is immense.

 

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Soft Matter Emerging Investigator – Ryan McGorty

Ryan McGorty received his bachelor’s degree in physics at the University of Massachusetts Amherst and his PhD in physics at Harvard University. Following a postdoctoral appointment at the University of California San Francisco, he joined the faculty of the Physics and Biophysics Department at the University of San Diego. The research of his undergraduate-driven lab focuses on the development of new microscopy techniques, the rheology of colloidal suspensions, and transport in biomaterials. He can be found on Twitter @ryanmcgorty.

Read Ryan’s Emerging Investigator article “Anomalous and heterogeneous DNA transport in biomimetic cytoskeleton networks” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

 

How do you feel about Soft Matter as a place to publish research on this topic?

I feel that Soft Matter is an excellent journal to read about the latest soft matter research and to publish my lab’s work. Soft Matter is where I find the most interdisciplinary and interesting work on biomaterials and biological aspects of soft materials.

What aspect of your work are you most excited about at the moment and what do you find most challenging about your research?

At the moment, I am most excited about employing new optical microscopy and image analysis techniques to investigate soft materials. A challenge in this work is sorting through and analyzing the mountains of imaging data one can rapidly acquire with current techniques.

Can you share one piece of career-related advice or wisdom with other early-career scientists?

One piece of advice I have for other early career scientists working in the field of soft matter is to look to adjacent fields for new techniques and methods that might be applicable to your research. I find that Soft Matter is an excellent place to both find and publish new techniques. 

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Soft Matter Emerging Investigator – Xinpeng Xu

Dr. Xinpeng Xu received his B.S. in physics from Wuhan University in 2008 and Ph.D. in Nano Science and Technology from the Hong Kong University of Science and Technology (HKUST) in 2012. After several years of post-doctor experiences in HKUST, Weizmann Institute of Science, and Technion-Israel, he joined the physics program in GTIIT in the fall of 2017 as an assistant professor. His main research interests lie generally in the theory of soft matter and biological systems in close collaboration with experiments. His recent research focuses on the structure, phase behavior, and dynamics of soft matter composite such as colloidal suspensions, polymer solutions/gels, animal cell-matrix systems, using the approaches of continuum mechanics and statistical thermodynamics.

Read Xinpeng’s Emerging Investigator article “Onsager’s variational principle in active soft matter” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

 

How do you feel about Soft Matter as a place to publish research on this topic?

Soft Matter is one of the most important and decent peer-reviewed interdisciplinary journals in the field of soft matter and biological systems. In the past decade, active soft matter has become a major research subject for soft matter physicists, through close collaboration with biologists and chemists, etc. Our work is about the field theory of active soft matter and its applications, which fits the general interests of the audience of Soft Matter.

What aspect of your work are you most excited about at the moment and what do you find most challenging about your research?

In the past decade, active soft matter has become a major research subject for soft matter physicists, through close collaboration with biologists and chemists, etc. The basic idea is to bring the study of active matter into the fold of condensed matter physics based on the consideration that the collective behaviors of active matter emerge from the interactions among the constituent self-propelling units and the dissipation mechanisms operating inside the system. In particular, soft matter physics provides a lot of useful model reference systems for active matter, such as liquid droplets, colloid suspensions, nematic liquid crystals, polymer gels, and surfactants, etc. The major challenge is then to couple these reference systems with active and specific molecular processes in a thermodynamically-consistent way. To tackle these challenges, we showed that Onsager’s variational principle (OVP), based on linear irreversible thermodynamics and widely used in the dynamic modeling of inert soft matter, can be simply extended to include biochemical activity and conveniently applied to study the emergent structures and dynamics of active soft matter. OVP can not only help to formulate thermodynamically-consistent models, but can also be used to find approximate solutions for the complicated active soft matter dynamics.

In your opinion, what are the most important questions to be asked/answered in this field of research?

What are the application range and limits of the active field theory based on linear irreversible thermodynamics in understanding the emergent phenomena in living biological systems?

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Soft Matter Emerging Investigator – Li-Heng Cai

Li-Heng Cai received his B.S. in Physics at Lanzhou University and Ph.D. in Materials Science at the University of North Carolina at Chapel Hill, where he researched both theoretical polymer physics and experimental biophysics under the supervision of Michael Rubinstein and Richard Boucher. He switched from theory to experimentation during his postdoctoral training with David A. Weitz and Jeffrey J. Fredberg at Harvard University. In 2018, he joined the faculty in the School of Engineering and Applied Science at the University of Virginia, where he leads the Soft Biomatter Laboratory. His research aims to understand and control the interactions between active soft materials and living systems to solve challenges in energy, healthcare, and environmental sciences. He has been recognized by the ACS PRF Doctoral New Investigator Award and the NSF CAREER Award. He can be found on Twitter @lihengcai and his lab group @SoftBiomatter.

Read Li-Heng’s Emerging Investigator article “Molecular understanding for large deformations of soft bottlebrush polymer networks” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

 

How do you feel about Soft Matter as a place to publish research on this topic?

Bottlebrush polymer networks are a new class of soft yet ‘solvent’ materials matching the mechanical properties of biological tissues. Understanding and controlling the mechanical properties of bottlebrush polymer networks is critical to the design and creation of new soft materials. With its diverse and interdisciplinary readership, Soft Matter is the ideal place to publish research in bottlebrush polymer networks.

What aspect of your work are you most excited about at the moment and what do you find most challenging about your research?

We discovered a previously unrecognized dependence of the extensibility of bottlebrush networks on the stiffness, and were able to develop a molecular theory to precisely capture the unusual mechanical behaviour. Because I was a theorist, I tend to develop a deep understanding of experimental findings. This raises a challenge: how to design and perform the simplest possible yet key experiments, which would generate reliable data for the subsequent theoretical understanding. Finally, how to exploit the newly developed understanding to design and create better materials of practical use.

In your opinion, what are the most important questions to be asked/answered in this field of research?

The most important and challenging question to be answered in the research of polymer networks is how to independently control the extensibility and the stiffness of a polymer network. These two most important mechanical properties of polymer networks and are intrinsically coupled: stiffer networks are less extensible. Solving this challenge would open avenues for designing high-performance polymer networks.

Can you share one piece of career-related advice or wisdom with other early career scientists?

To me, the most important thing is to identify problems of both fundamental and practical importance. Every project we are doing now meets this criterion. Being able to do so allows me to attract the talent and resources required to do the work.

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Soft Matter Emerging Investigator – Tristan Bereau

Tristan Bereau is an assistant professor at the Van ‘t Hoff Institute for Molecular Sciences and the Informatics Institute of the University of Amsterdam. He completed a Ph.D. in Physics at Carnegie Mellon University, Pittsburgh, PA, USA. In 2012, Tristan moved to the University of Basel as a postdoctoral researcher. He was a group leader at the Max Planck Institute for Polymer Research from 2014, leading an Emmy Noether group from 2016 to 2019. His work focuses on the interface between multiscale modeling and machine learning for soft matter. He can be found on Twitter @tristanbereau.

Read Tristan’s Emerging Investigator article “Free-energy landscape of polymer-crystal polymorphism” and check out all of the 2021 Soft Matter Emerging Investigator articles here.

 

How do you feel about Soft Matter as a place to publish research on this topic?

Soft Matter is a high-quality journal to publish important developments relating to the field of soft matter. It’s a great venue to present scientific developments, but also leaves room for more technical/methodological contributions of high quality.

What aspect of your work are you most excited about at the moment and what do you find most challenging about your research?

Developments in machine learning are quickly changing the way we approach many problems. The capacity of machine learning to transform so many scientific fields is quickly reshaping our field. This makes for exciting opportunities to shape the way we integrate machine learning in soft matter. To take full advantage of these tools, it demands careful attention to methodological developments in computer science.

In your opinion, what are the most important questions to be asked/answered in this field of research?

In many ways hard condensed matter has more rapidly embraced machine learning. Soft matter has had a late start, though the pace of research is greatly accelerating. To further catch up, it’s important to improve how we blend in two aspects—scale separation and entropy—in machine learning models.

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