Singapore

Subcellular compartmentalization is a key feature of eukaryotic cells. Selectively targeting subcellular compartments, though holding many exciting opportunities for biomedicine, remains rather underdeveloped. Enzyme noncovalent synthesis (ENS), an approach that integrate enzymatic reactions and self-assembly, provides a new way for subcellular targeting. In this talk, we briefly introduce the development of supramolecular self-assemblies for targeting mitochondria, endoplasmic reticulum, Golgi apparatus, and cell membrane. We mainly focus on the use ENS, which spatiotemporally controls the formation of supramolecular assemblies, for subcellular targeting and its applications, such as developing novel cancer therapeutics.

MATERIALS FOR HUMANITY (MH 21)

Enzymatic Noncovalent Synthesis for Targeting Subcellular Organelles

### Artificial Intelligence in Metabolism (AIM)

AIM is a seminar series that will explore the potential of data science in metabolic research. It is hosted by the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) at the University of Copenhagen.
The seminar series takes place over three days in June and July, 2021 from 4pm to 5:30 pm CEST.

![](https://assets.underline.io/uploads/markdown_image/1/image/bc89e60b0a0f2d7550c75517a10f2843.png)
**About AIM**

Artificial Intelligence in Metabolism brings together renowned investigators to discuss how cutting edge data science can be best utilized to challenge current dogmas and catalyse better translation in metabolic and biomedical research.

Significant new discoveries in metabolic research increasingly rely on large-scale profiling, data integration and machine learning-based techniques. Not only can these techniques be leveraged to distil novel actionable biological hypotheses to be tested in relevant physiological contexts/clinical settings, they for example enable us to develop predictive tools to more effectively and timely identify at-risk individuals or personalized drugs/interventions. 

At the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) we have set up enabling biology platforms that utilize sophisticated metabolomics, single-cell and data integration techniques to enrich our deeply phenotyped and genotyped patient cohorts. These data, along with the associated Danish longitudinal health register information, constitute a unique base to empower current and next generations of scientists to tackle the major questions in metabolic research.

We envision that data and machine learning models will be at the heart of future teams driving novel discoveries in metabolic research, through interdisciplinary approaches involving traditional biomedical scientists alongside data scientists, mathematicians and bioinformaticians.
Please join us in our effort to discuss and incubate new ideas to better explore and model metabolic disease.

![](https://assets.underline.io/uploads/markdown_image/1/image/bc89e60b0a0f2d7550c75517a10f2843.png)



AIM Seminar Series 2021

AIM is a seminar series that will explore the potential of data science in metabolic research. It is hosted by the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) at the University of Copenhagen. The seminar series takes place over three days in June and July, 2021 from 4pm to 5:30 pm CEST.

technical paper

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MH 21 is arranged around 6 themes that focus attention on pressing needs that should be addressed to enhance the well-being of communities and provide a forum for presenting breakthrough discoveries.

Fluorescence imaging in the second near-infrared window (NIR-II, 1,000-1,700 nm) demonstrates unique advantages of high sensitivity, high temporal and spatial resolution, and excellent image quality in comparison to that in the first near-infrared window (NIR-I, 650-950 nm) due to low scattering of photons and zero background fluorescence in the NIR-II region. Currently, a variety of NIR-II fluorescence imaging probes, such as single-wall carbon nanotubes, quantum dots, rare-earth-doped nanoparticles, conjugated polymer nanoparticles, small molecules, and AIEgens, have been developed as significant imaging tools for basic and clinical research. In this report, we begin with briefly introducing the advances of NIR-II fluorescence molecular probes in the last 10 years, including the design, preparation, and NIR-II fluorescence molecular imaging applications of AIEgens and indocyanine green (ICG). Subsequently, we highlight the large-scale preparation of NIR-II imaging probes and their applications in large animals, including New Zealand white rabbits and cynomolgus monkeys. Finally, we prospect the opportunities and challenges of NIR-II fluorescent molecular imaging probes in basic and translational studies.

Advances in NIR-II Fluorescence Imaging Probes

It is well-known that luminescent materials have found applications in many fields, such as lighting, display, biomedical analysis and solar energy light conversion and so on. The NIR excitation light for upconversion nanoparticles have many advantages in biomedical application, such as good photostability, low or zero background luminescence, higher penetration depth and so on. NIR light can be used to excite upconversion nanoparticles to produce UV-vis light, which can be further employed to excite the prodrugs or photosensitizers to kill cancer cells. Various of therapy processes can be combined together in one system under NIR irradiation, thus increasing the treatment efficacy.



Rare Earth Up-conversion Luminescent Nanomaterials: Controllable Synthesis, Property Modification and Biomedical Application

Cancer, a major public health problem worldwide, is a death causing disease. Chemotherapy and radiotherapy are main treatments for cancer. However, their side effects and resistance limited their clinical use. On the other hand, nanomedicine, the area of interdisciplinary science, applies nanotechnology to health and medicine [1]. First, we demonstrate that how nanotechnology overcomes platinum drug resistance [2]. The platinum prodrug was designed and tethered onto surface of gold nanorods. The designed delivery system can overcome resistance through increasing drug uptake and decreasing drug deactivation. We also used nanomedicine strategy to deliver chemotherapy drugs, such as Histone deacetylase (HDAC) inhibitor, to sensitize radiotherapy through inhibiting DNA repair [3]. Second, we developed a multifunctional platform with controlled activation of platinum prodrug using near infrared (NIR) light and with real-time evaluation of drug efficacy [4]. The ultraviolet (UV) light sensitive platinum prodrug was synthesized and conjugated onto surface of upconversion nanoparticles (UCNPs). Upon absorbing NIR light, UCNPs convert it into UV light, which activates platinum prodrug, release active components and then induce cancer cells apoptosis. Meanwhile, an apoptosis-imaging probe was also conjugated onto UCNPs. Once NIR light irradiated UCNPs, cancer cells apoptosis was triggered, which unleashed the release of enzyme, caspase-3 and subsequently activate the imaging probe. Therefore, the direct imaging of apoptosis in living cells can be for real-time evaluation of drug efficacy. Finally, yet importantly, nowadays immunotherapy generates promising clinical data that have not seen before. It showed that combining radiotherapy and immunotherapy can enhance immune responses and can boost ‘abscopal effect’. Unfortunately, response rates for this strategy remain low. Herein we utilizes antigen-capturing nanoparticles (AC-NPs) to improve this strategy [5]. Our engineered AC-NPs can capture a set of protein antigens released post radiotherapy and it helped antigen presentation, which eventually induce enhanced immune responses and enhance ‘abscopal effect’.

Nanomedicine Strategies for Improving Chemoradiotherapy, Real-time Evaluating Drug Efficacy, and Enhancing Immunotherapy in Cancer Treatment

The unique optical properties of lanthanide-doped inorganic nanocrystals have rendered their potential usefulness as novel nanodrugs for many applications. Surface modification with organic dye molecules is a useful strategy to manipulate the optical properties of lanthanide-doped nanocrystals. The interaction between dye molecules and nanocrystals provides unprecedented possibilities to gain new optical phenomena from the organic-inorganic composite systems. The development of highly efficient lanthanide-based organic-inorganic nanoconjugates may overcome the existing limitations to the lanthanide-doped nanomaterials and stimulate applications in area such as light energy harvesting, light emission, biosensing, therapeutics and photocatalysis. Driven by this motivation, our group has recently devoted to the fabrication and mechanical studies of lanthanide nanocrystals with either unique crystal lattice structures or novel core-shell heterogeneous structures. We are trying to understand the energy transfer through the surface of lanthanide-doped nanocrystals for applying these materials in nanomaterial therapeutics.

Dye-coupled lanthanide nanocrystals for advanced optical biosensing and photodynamic therapy

Formidable progress has been recently achieved in the fabrication and characterization of disordered low dimensional materials with unprecedented properties. For instance, particular forms of disordered graphene (reduced graphene oxides) and other two-dimensional materials, obtained by chemical exfoliation techniques, have been found suitable to improve the performances of composite materials, with applications in energy, textiles, solar cells, thermoplastics etc. In parallel, catalytic vapor deposition methods have been used intensively to upscale the growth of two-dimensional materials at wafer size, with resulting material morphologies ranging from polycrystalline to fully amorphous phases. Recent reports on wafer-scale synthesis of ultrathin layered amorphous carbon and boron nitride, structurally dominated by sp2 hybridization but lacking crystalline orders, have shown superior performances of those materials as coating and interfacial components, providing a new platform for properties reinforcement in the industrial context.

Here, we present our computational strategies to achieve predictive modelling in this context. For the “computationally-assisted” material synthesis, we use machine learning to generate atomic interaction potential in an arbitrary disordered local environment and obtain realistic large-scale material configurations through classical molecular dynamics, while generic tight-binding models are generated based on resulting spatial atomic distribution and optimized DFT-inspired Hamiltonian parameters. Next, we employ efficient linear scaling quantum transport [1] (see also www.lsquant.org) to simulate structural models containing up to a billion atoms, hence demonstrating unprecedented supremacy to match predictive modelling with experimental scales, and therefore constituting decision-making tools for material design and industrial performances achievement. We illustrate our strategy on various examples including the (thermal) reduction process of graphene-oxides for recovering higher crystallinity, the correlation between the degree of disorder and resulting physical properties in polycrystalline materials [2], as well as amorphous phases of sp2 carbon members [3] and boron-nitride [4]. The obtained results provide scaling laws and guiding rules for researchers and engineers to target the proper material growth and integration conditions for reaching the upper limit of a given application objective, such as flexible conductors, spin channel, ultrathin heat spreaders, energy harvesters, insulating thermal barriers, or ultralow dielectric coefficient materials.
[1] Z. Fan et al. S. Roche, Physics Reports 903, 1-69 (2021)
[2] AW Cummings et al. Advanced Materials 26 (30), 5079-5094 (2014)
[3] A Antidormi, L Colombo, S Roche, 2D Materials 8 (1), 015028
[4] S. Hong, et al. A. Antidormi, S. Roche, M. Chhowalla, H.J. Shin & H.S. Shin, Nature 582, 511–514 (2020)

Multiscale Computational Methods for Exploring Electrical and Thermal properties of highly disordered Composites Materials: From Machine-learning based Molecular Dynamics to Linear Scaling Transport Methods

It has been well known that various kinds of lattice defects are ubiquitous in real materials and they govern mechanical properties of materials based on pioneering studies. While removal of detrimental influence by lattice defects has been one of the principal aim of recent studies [1-2], it is reported that further exploitations of those lattice defects for other functional properties is possible, where lattice defects play yet another role or more to control or even create resultant materials properties [3-6].
Aiming at modifying or even creating new properties that single crystals cannot acquire, we have carried out modeling of lattice defects for atomistic simulations including molecular dynamics and ab initio calculations [7-12]. Then, we identify the origin of the resultant thermal transport properties, thereby exploiting lattice defects for advanced materials [13-15] in the framework of “crystal defect cores” [16].
In this presentation, findings upon modeling of lattice defects, resultant transport properties and underlying mechanisms behind the properties will be discussed.

References:
[1] S.F. Chichibu, et al., Nat. Mater. 5 (2006) 810–816.
[2] Z. Chen, et al., Nat. Commun. 8 (2017) 14101.
[3] Y. Takashima, et al., Nat. Commun. 2 (2011) 168.
[4] A. Nakamura, KM, et al., Nat. Mater. 2 (2003) 453–456.
[5] Y. Oshima, AN, KM, Science. 360 (2018) 772–774.
[6] K. Matsunaga, TY, AN, et al., Acta Mater. 195 (2020) 645–653.
[7] T. Oyama, MY, KM, et al., Phys. Rev. B, 71 (2005) 224105.
[8] M. Yoshiya and T. Oyama, J. Mater. Sci., 46 [12] (2011) 4176-4190.
[9] B. Feng, et al., Nat. Commun., 7 (2016) 11079.
[10] T. Yokoi and M. Yoshiya, Physica B, Condensed Matter, 532 (2018) 2-8.
[11] T. Yokoi, AN, KM, Phys. Rev. Mater., 4 (2020) 014605.
[12] T. Yokoi, AN, KM, et al., Phys. Chem. Chem. Phys., 23 (2021) 10118.
[13] S. Fujii, MY, et al., Sci. Rep., 8 (2018) 11152.
[14] S. Fujii, TY, MY, Acta Mater., 171 (2019) 154-162.
[15] W. Sekimoto, SF, MY, Scr. Mater., 202 (2021) 113991.
[16] https://www.core.mp.pse.nagoya-u.ac.jp/en/

Modeling of Lattice Defects and Resultant Thermal Transport Properties of Materials

N-type transparent conductors (TCs) are key materials in the modern optoelectronics industry. Despite years of research, the development of a high-performance p-type TC has lagged far behind that of its n-type counterparts, delaying the advent of “transparent electronics” based on transparent p-n junctions.[1] Here, we computationally investigate three layered oxychalcogenide structural motifs to try to predict new p-type TCs, namely the [Cu2Ch2][A3B2O5] (325), [Cu2Ch2][A4B2O6] (426) and [Cu2Ch2][A2BO2] (212) structural motifs. Specifically, we have used a materials informatics approach (SMACT) to screen through the search space using low-cost heuristic tools.[2] This reduces the potential combinations from 1800 to a more computationally tractable 228, which then undergo DFT calculations to assess thermodynamic and dynamic stability. In this talk, I will present an update on how our search has predicted >50 novel semiconductors with potential applications ranging from TCs[3,] to photocatalysts,[4], solar absorbers and thermoelectrics.

[1] A. Walsh and J.-S. Park, The Holey Grail of Transparent Electroncs, Matter, 3, 604 (2020)
[2] D. W. Davies, K. T. Butler, A. J. Jackson, A. Morris, J. M. Frost, J. M. Skelton and A. Walsh, Computational Screening of All Stoichiometric Inorganic Materials, Chem, 1 617 (2016)
[3] B.A.D. Williamson, G.J. Limburn, G.W. Watson, G. Hyett, and D.O. Scanlon. Computationally Driven Discovery of Layered Quinary Oxychalcogenides: Potential p-Type Transparent Conductors?
[4] G. J. Limburn, M. J.P. Stephens, B. A. D. Williamson, A. Iborra-Torres, D. O. Scanlon and G. Hyett. Photocatalytic, structural and optical properties of mixed anion solid solutions Ba3Sc2−xInxO5Cu2S2 and Ba3In2O5Cu2S2−ySey, Journal of Materials Chemistry A, 8, 19887 (2020).


Computational Prediction of Novel Quinary Layered Oxychalcogenides

There is an ever-increasing need for new magnetic materials. When developing them, it is advantageous to improve our understanding of mechanisms that are decisive for the existing materials. Iron and iron-based materials are prototype magnetic systems and the question is whether their properties have already reached their limits or can be further improved beyond the current horizons. We have employed quantum mechanical calculations to shed a new light on relations between the extended defects and magnetic properties in Fe-Al-based materials. We show that there is a very strong competition between the thermodynamic stability, that favors Al atoms becoming the first nearest neighbors of Fe atom, and iron magnetic moment that is reduced by this trend [1-3]. We analyze how extended defects, in particular antiphase boundaries, alter local atomic configurations of Fe atoms and, consequently, increase the magnetic moment. The increase can be as massive as by 140% in off-stoichiometric Fe2AlTi intermetallic com-pound with the Heusler L21 structure [4]. We suggest that defects can be used as designing tool when developing new magnetic materials. Additional studies of point defects are under way [5]. 

References
[1] I. Miháliková et al., Nanomaterials 8 (2018) 1059; doi:10.3390/nano8121059.
[2] I. Miháliková et al., Materials 12 (2019) 1430; doi:10.3390/ma12091430. 
[3] M. Friák et al., Nanomaterials 10 (2020) 044, doi:10.3390/nano10010044.
[4] M. Friák et al., Crystals 9 (2019) 299; doi:10.3390/cryst9060299.
[5] P. Šesták et al., manuscript in preparation (2021). 



Designing improved magnetic materials by exploiting extended defects

Transforming the abundant atmospheric nitrogen (N2) into ammonia (NH3), a widely used industrial feedstock, through a green and sustainable process has gained an increasing interest for both commercial and environmental needs. The current industrial route for the production of NH3 is based on the Haber-Bosch (H-B) process, which is conducted under high temperature (~500℃) and pressure (~200 atm) conditions and consumes about 2% of the world’s energy per year. Thus, it is of paramount significance to search for energy-efficient and environmentally friendly techniques to replace the H-B process. The electrochemical nitrogen reduction reaction (eNRR), which takes place at mild conditions and can be driven by renewable energies such as solar and wind, constitutes a desirable alternative. However, the development of low-cost and high-efficient electrocatalysts for eNRR has remained elusive up to now. In this work, we conduct a comprehensive study to unravel the reaction mechanisms of N2 fixation on SAC-Nb2CN2 and molybdenum nitride by using density-functional-theory (DFT) calculations. 
For SAC-Nb2CN2, we screen the transition metals (TM), including 26 elements, supported on two-dimensional (2D) Nb2CN2 (TM-Nb2CN2) for their applications into electrochemical reduction of N2 (NRR) based on first-principles calculations. We show that most SACs can bind with Nb2CN2 strongly through a TM-N3 configuration. We find that Mn-Nb2CN2 is a promising candidate for the N2 reduction reaction (NRR), with a low overpotential of 0.51 V through the distal mechanism. Importantly, TM-Nb2CN2 presents high selectivity to NRR by blocking the hydrogen adsorption and preventing the hydrogen evolution reaction (HER). 
For molybdenum nitride, the activity and selectivity of eNRR on pristine (001) and (110) Mo5N6 surfaces as well as few specific numbers of heteroatom anchored N-terminated surfaces are all evaluated and compared. We find that the Mo and N atoms on the pristine Mo5N6 surface are both active for eNRR, while follow different pathways in mechanism. Moreover, the eNRR catalytic performance of Mo5N6 could be further boost by specific metal atoms anchoring, such as single atom, metal dimer and heterodiatom pair. Finally, a full map of eNRR mechanism on pristine and metal atom-decorated Mo5N6 surfaces are illustrated. 
Our work not only provides a fundamental understanding of eNRR mechanism on TMNs based materials, but also offers powerful strategies towards the rational design of efficient NRR electrocatalysts.

Design of Catalysts for Water Splitting and N2/CO2 Reduction

Starting from bcc/fcc unit cells for iron ground/excited states, mostly we use the minimum unit cell for the target crystal from the well-known materials database with long history. We have extended the standard unit cell for Wurtzite (B, Al, In)xGa1-xN to 2x2x2 supercell etc., and found that previously used unit cells are NOT the ones for the best ground state atomic structures. We found that there are energetically more favorable complex atomic structures only possible to be explained by introducing larger number of atoms in larger unit cells. For quite long time ago, double Perovskite structure (deformed unit cells) has found to be better than the single unit call, which can be explained by introducing the φ4 potential minimum, better than the simple harmonicφ2 one. This is not the only one case, but there are many such cases which are related to widely used materials, some of them have been known to explain the experimental observations.
In this presentation, our recent work will be introduced on a necessary larger unit cell for Wurtzite (B, Al, In)xGa1-xN system, which has been know experimentally to explain the favorable growth direction known as pulling effect in epitaxial layer fabrication, which now is cleared to be related to the lager unit cell we have theoretically introduced. Minority elements are presented by two atoms in the simulation cell and the energetics of these spatial configurations are analyzed to estimate the preferable group-III sites of boron, aluminum and indium atoms. Boron atom energetically prefers to occupy in a collinear orientation along the c-axis [0001], which we proved to be related to the experimentally known “pulling effect”.
More recently clarified phenomena will be presented.



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