bluuebunny/crossref_metadata_2025_split huggingface dataset:
(Keynote) Automated / Autonomous Platforms for Synthesis, Purification, and Characterization of Quantum Dots
Authors: Kenis Paul J.A , Vikram Ajit , Xu Rui Hua Jeff 
Published: August 2024

Controlling composition, structure, and thus properties of nanomaterials continues to be of importance to numerous fields. For example, applications of quantum dots range from displays and bioimaging, to metal nanoparticles for (electro-) catalytic conversions. The vastness of synthesis parameter space, in combination with still limited understanding of the nucleation and growth mechanisms for many quantum dots systems still hampers progress in identifying nanomaterials with desired properties for existing and newly envisioned purposes. Furthermore, the identification of optimal synthesis recipes for these nanostructures remains a major hurdle.
This presentation will report on the development and application a number of enabling capabilities for the synthesis and characterization of quantum dots, achieved through reactor engineering. We demonstrate how the use of automated flow reactors not only helps in run-to-run reproducibility but also in uncovering mechanistic information. Examples include reactors with dedicated nucleation, growth, and shell formation zones, and investigation that revealed mechanistic insight of how water concentration affects QD synthesis outcome. We also employed an autonomous flow reactor system to map synthesis parameter space of specific QD systems, a project that relied on fast, fully automated in-situ characterization using UV-vis or photo-luminescence in combination with multi-step machine learning workflows The utility of flow reactors, however, is limited when considering chemistries with longer reaction times. Hence, more recently we developed a fully automated batch reactor for parameter space mapping of QD synthesis via hot injection, the most frequently used method in both QD research and production at scale. This batch platform is being augmented with purification capabilities, to address some of the challenges of in-line, in-situ characterization of raw reaction mixtures, and to enable using advanced optical and structural characterization methods to provide insight into the actual structure of the QD materials.
(Invited) Synthesis of Ultra-Bright Colloidal Silicon Quantum Dots (PLQY~80%) and Highly Efficient LEDs (EQE>10%)
Authors: Saitow Ken-ichi 
Published: August 2024

Silicon is the second most abundant element in the Earth’s crust and could be considered an environmentally benign material. Silicon has been widely used in electronic devices and solar cells, and it has dominated the semiconductor research and development. However, the photoluminescence (PL) of the bulk material shows an invisible NIR wavelength (λ ~ 1100 nm). In addition, the PL quantum yield (PLQY) of bulk crystal Si is ~0.01% owing to the indirect transition nature. In contrast, silicon quantum dots show PL in the entire visible spectral region [1]. Furthermore, colloidal silicon quantum dots demonstrate PLQYs of 60% [2], and thereby they give highly impact as environmentally benign and heavy-metal-free quantum dots (i.e., In, Cd, and Pb free) for displays, lighting, and biomedical imaging via solution processing. Indeed, silicon quantum dot LEDs have recently been produced from a natural substance, by upcycling discarded rice husks [3].
Herein, red PL with a PLQY of 60–80% and LEDs with an external quantum efficiency of >10% were obtained at 1/3600th of the cost of existing methods. This was achieved by using trichlorosilane and an organic solvent to prepare a hydrogen silsesquioxane (HSQ) polymer, and by optimizing the LED optoelectric properties. Based on many silicon quantum dots synthesized in our study, each of them enabled us to quantitative the relationships HSQ polymer structure, PLQY, and LED efficiency, exhibiting the critical parameters that governed their performances. Moreover, the simple and cost-effective methods proposed here could prove invaluable for the synthesis and characterization of silicon quantum dots in the near future.
References
[1] Canham, L. Faraday Discuss. 2020, 222, 10–81; [2] Ono, T.; Xu, Y.; Sakata, T.; Saitow, K. I. ACS Appl. Mater. Interfaces 2022, 14, 1373–1388; [3] Terada, S.; Ueda, H.; Ono, T.; Saitow, K. ACS Sustainable Chem. Eng. 2022, 10, 1765–1776.
(Invited) Towards Non-Blinking Strongly Confined Perovskite Quantum Dots
Authors: Mi Chenjia , Gee Gavin , Atteberry Mattew , Dong Yitong 
Published: August 2024

Quantum information science has shown its capabilities to enable secure quantum communications. Single photon emitters (SPEs) that emit photons one at a time are fundamental elements of such transformative technologies. Colloidal cesium lead halide (CsPbX3, X=Br, I) perovskite QDs are ideal for next-generation SPEs because of their high room-temperature luminescence efficiency and low-cost, scalable syntheses. Unfortunately, individual perovskite QDs show insufficient photostability and severe photoluminescence (PL) intensity fluctuations (also called blinking). This has greatly limited the spectroscopic studies of perovskite QDs for SPE developments. One major roadblock toward non-blinking, photostable perovskite QDs is their highly ionic crystal structure. When preparing single perovskite QD samples, QD colloids often need to be diluted. During this process ligands can detach from the QD, introducing defects. This is particularly detrimental to strongly confined perovskite QDs since exciton-surface lattice interaction is greatly enhanced. As a result, strongly size confined perovskite QDs are experiencing severe PL blinking with large PL “OFF” occurrences.
To suppress perovskite QD blinking and photodegradation, we embedded QDs in an organic crystal matrix consists of Phenethylammonium bromide (PEABr) salts. The bromide rich surface of a QD can be epitaxially anchored onto the PEABr crystals and therefore be stabilized. Individual strongly confined CsPbBr3 QDs in our matrix show nearly non-blinking behavior under non-resonant laser excitations at room temperature. These QDs remain photostable without PL intensity decrease and spectral shift after more than 12 hours of continues excitations. We anticipate that these QDs will lead to more accurate and detailed study of exciton dynamics and structural-optical property relationships in strongly confined perovskite QDs.
Mixed Electronic-Ionic Conductive Polymer Binder for Silicon-Based Solid-State Battery
Authors: Li Defu , Ahmed Faiz , Liu Gao 
Published: August 2024

Silicon has attracted extensive research attention in lithium-ion battery (LIB) field due to its high theoretical specific capacity (~3600 mAh/g) and cost-effectiveness. In recent years, silicon has emerged as a viable candidate for anode material for solid-state battery (SSB) technology. Similar to its application in LIBs, silicon utilizing in SSBs encounters challenges, such as significant volume variation (~300%) during cycling and poor cycling performance. In addition, the utilization of silicon in SSB faces another critical bottleneck in ionic conductivity due to the absence of liquid electrolyte. To address these challenges, various pioneering studies have explored potential solutions, including controlling the thickness of silicon anode to be below 150 nm,(1) fabricating electrodes with a combination of silicon and solid-state electrolyte (e.g, Garnet-type electrolyte(2) and sulfide electrolyte(3)), subjecting SSBs to a high pressure (10-50 MPa)(4).
Here, we introduced an alternative approach to mitigate these challenges by designing anodes through incorporating silicon with mixed electronic-ionic conductive (MEIC) hierarchically ordered structure (HOS) polymer binders. These multifunctional HOS polymer binders effectively preserve the structural integrity of electrode materials, even when silicon materials experiences significant volume expansion and shrinkage during the charging-discharging process. Owing to establishments of covalent bonds between silicon surface and the polymer binders, the resulting SSBs exhibited excellent resilience and only required hand-tightening force (<1 ton) for operation. These polymer binders effectively maintained continuous electronic and ionic pathways within silicon-based anodes without the need of additional additives, such as carbon material and solid-state electrolytes. Utilizing these versatile polymer binders, the resultant SSBs featured an outstanding cycling performance over 100 cycles in full cells, with an average Coulombic efficiency exceeding 97%.

Reference

A. Song, W. Zhang, H. Guo, L. Dong, T. Jin, C. Shen and K. Xie, Advanced Energy Materials, 13, 2301464 (2023).

W. Ping, C. Yang, Y. Bao, C. Wang, H. Xie, E. Hitz, J. Cheng, T. Li and L. Hu, Energy Storage Materials, 21, 246 (2019).

M. Rana, Y. Rudel, P. Heuer, E. Schlautmann, C. Rosenbach, M. Y. Ali, H. Wiggers, A. Bielefeld and W. G. Zeier, ACS Energy Letters, 8, 3196 (2023).

D. H. Tan, Y.-T. Chen, H. Yang, W. Bao, B. Sreenarayanan, J.-M. Doux, W. Li, B. Lu, S.-Y. Ham and B. Sayahpour, Science, 373, 1494 (2021).
Solid-State Lithium-Ion Superionic Electrolytes with Reduced Moisture Sensitivity
Authors: Bahmani Farzaneh , Rodmyre Collin , Smirnova Alevtina W 
Published: August 2024

The remarkable safety and high energy density of solid-state batteries (SSBs) created significant advantages in the development of next-generation energy storage. The properties of these batteries are highly dependent on the characteristics of solid-state electrolytes (SSEs), making them a crucial material in the development of such batteries. Following diverse principles of material design, lithium halide SSEs, particularly Li3InCl6, open new opportunities in the development of SSBs due to their unique properties including broad electrochemical stability window, high lithium-ion conductivity, and excellent deformability. Through a mechano-thermal synthesis approach, Li3InCl6 demonstrates substantial ionic conductivity at room temperature. We studied the temperature-dependent behavior of Li3InCl6 by using in-situ/operando techniques such as XRD and XPS. However, its susceptibility to moisture poses a significant challenge for practical implementation in SSBs. To overcome this limitation, this research is focused on a novel solution: hafnium doping of Li3InCl6. Integrating hafnium into the Li3InCl6 structure results in a substantial improvement in electrochemical performance. The Li2.6In0.6Hf0.4Cl6 solid-state electrolyte not only showcases heightened ionic conductivity but also demonstrates improved resistance to moisture. The achieved ionic conductivity reaches approximately 1 mS cm-1, marking a significant 3.5-fold increase compared to Li3InCl6. Noteworthy is the fact that, after 5 hours of exposure to air with 15% humidity, the observed reduction in ionic conductivity for Li2.6In0.6Hf0.4Cl6 is 37%, a notably lower decrease compared to the 57% reduction seen in Li3InCl6.
The efficacy of hafnium doping provides a crucial advancement in the field of solid-state electrolytes, promising a transformative impact on next-generation energy storage systems.
Enhancing Shelf-Life of Electrolytes with LiPF6 By Increasing Stability Under Commercially Relevant Storage Conditions
Authors: Usrey Monica Lee , Guillot Sarah Lucienne , Hennek Matthew , Garg Shipra , Homa Arthur , Sriramulu Suresh 
Published: August 2024

Lithium hexafluorophosphate (LiPF6) salt is the most commonly used lithium salt in commercial Li-ion batteries due to its high conductivity, passivation of Al current collectors for positive electrodes, and participation in SEI layer formation at graphite anodes.1 However, LiPF6 suffers from poor thermal stability and poor stability toward protic species (like water) leading to decomposition that can significantly reduce Li-ion battery performance especially under the extreme conditions demanded by today’s industrial applications. Specifically, LiPF6 decomposition leads to HF generation, especially in the presence of water2, which results in multiple negative outcomes in Li-ion cells including dissolution of cathode materials and gas generation.3 Conditions during electrolyte blending, transport, and/or storage often exacerbate LiPF6 instability and increase HF generation.
To date, efforts to replace LiPF6 have not proven to be commercially successful, therefore strategies to improve the stability of LiPF6 electrolytes under relevant storage conditions are critical to support the deployment of Li-ion batteries. Koura has extensively characterized the degradation of LiPF6 as a function of multiple conditions, including temperature, water content, and electrolyte composition to inform the design of strategies to improve stability.
This presentation will summarize Koura’s efforts to understand LiPF6 decomposition under conditions relevant to the Li-ion electrolyte supply chain. Specifically, we will present data showing a series of fluorinated materials that improve the thermal stability of LiPF6 electrolyte through the elimination of existing HF and suppression of additional formation.
References:

Sascha Nowak and Martin Winter 2015 J. Electrochem. Soc. 162 A2500

Hui Yang et al 2006 J. Power Sources 161 573

Weishan Li 2020 J. Electrochem. Soc. 167 090514
Early-Stage Evaluation of Battery Safety Based on Materials, Component, and Microcell Calorimetry Measurements
Authors: Albertus Paul , Bhargava Bhuvsmita , Wang Zixuan , Ogundipe Taiwo , Zaman Samaa 
Published: August 2024

There are numerous “beyond lithium ion” battery chemistries under development at universities, national labs, companies, and other organizations. Early-stage battery chemistry work typically focuses on demonstrating performance at the materials, coin, and pouch cell level, with evaluation and design for safety left for later stages.1 In this talk, we will describe the opportunities for assessing the safety of a battery chemistry at the earliest stages of its development, as soon as the active materials and electrolyte have been identified.2 With carefully designed and quantitative experiments, key information such as the amounts of heat released by the reactions of and among cell components, the temperatures at which that heat is released, the release of toxic or otherwise dangerous gases, the material heat capacities, and other key properties can be measured with differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA), and other approaches. We have demonstrated the value of this approach for a LixCoO2+C+PVDF cathode sheet /LLZO/Li metal material set, where we identified the previously under-appreciated role of the cathode sheet conductive additive and binder in the reaction pathways upon heating to 500°C in a DSC pan.3 Despite this material set containing no liquid electrolyte, delithiated LixCoO2 releases oxygen upon heating to >~230°C, and that oxygen can react exothermically with the Li metal and conductive carbon. In addition, PVDF binder releases HF gas at >400°C, which can also react exothermically with Li metal.
This talk will focus on the methodology required to obtain accurate measurements on milligram-scale samples, with an emphasis on the sample preparation and DSC methods to obtain accurate, repeatable results. Approaches associated with DSC baselining and integration methods will be presented. The talk will also present results from our recent work on material sets that are more commercially relevant for electric vehicle applications than the LixCoO2 cathode sheet/ LLZO / Li material set. In particular, results from material sets such as NMC532 cathode sheet / LLZO / Li, NMC811 cathode sheet / LLZO / Li, and NMC811 cathode sheet / LPSCl / Li metal will be presented. Finally, we will discuss the implications of our early-stage, material-scale work for future large-format cells.
1. See Category 3 in the ARPA-E EVS4ALL program, https://arpa-e.energy.gov/technologies/programs/evs4all
2. Joule 6, 742–755, April 20, 2022.
3. ACS Appl. Mater. Interfaces 2023, 15, 49, 57134–57143
Polymerized Acrylonitrile Artificial SEI for Long-Life Li-Metal Battery and Enhanced Stability for Li/Li10GeP2S12 Interface
Authors: Hoang Binh , Lin Chuan-Fu , Damircheli Roya , Brausch Madison , Ferrari Victoria 
Published: August 2024

Lithium metal anode batteries have attracted significant attention as a promising energy storage technology, offering a high theoretical specific capacity and low electrochemical potential. Utilizing lithium metal as the anode material can substantially increase energy density compared to conventional lithium-ion batteries. However, the practical application of lithium metal anodes has encountered notable challenges, primarily due to the formation of dendritic structures during cycling. These dendrites pose safety risks and degrade battery performance. Addressing these challenges necessitates the development of a reliable and effective protection layer for lithium metal. This study presents a cost-effective and convenient method to produce lithium metal protective layers by creating ex-situ polymer layers using acrylonitrile (AN). This method extends the lifetime of lithium metal anodes by a remarkable factor of six under high current (1 mA/cm²) cycling conditions. While the cycle life of bare lithium metal is approximately 150 hours under high current conditions, AN-treated lithium metal anodes exhibit an impressive longevity of over 900 hours.
Furthermore, with the increasing attentions on solid-state electrolytes – which address the safety concerns and energy density limitations associated with conventional liquid electrolytes in lithium-ion batteries, the interface between Li metal and solid-state electrolytes has been the major challenges. For example, Li10GeP2S12 (LGPS) stands out among these solid electrolyte materials, boasting high ionic conductivity (1 x 10⁻² S cm⁻¹). Nonetheless, the severe instability of the interface between lithium metal anodes and solid electrolytes, including dendrite formation and electrolyte degradation, hindering their practical implementation. This work also goes deeply to explore the stability and performance of Li | LGPS systems by utilizing a polymerized acrylonitrile interfacial. By elucidating the mechanisms governing the interfacial layers, this low-cost fabrication of AN-treated lithium metal holds significant potential for advancing the commercialization of future lithium-metal batteries, surpassing the capabilities of traditional lithium-ion batteries.
Influence of Transition-Metal Order of LNMO Spinel on the Li Ion Diffusion
Authors: Glibo Albina , Cupid Damian Marlon , Kahr Juergen 
Published: August 2024

Cathode materials contribute a substantial portion to the weight, cost, and environmentally sustainability of LIBs. A key strategy to enhance energy density at reduced cost and improved sustainability is to develop more cost-effective, cobalt-free, higher-energy-density alternatives. Among the Co-free electrode cathode chemistries, the LiNi0.5Mn1.5O4 (LNMO) spinel stands out as most promising. It exhibits a high specific energy density of 650 Wh/kg, attributed to its elevated operating voltage of approximately 4.7 V vs. Li+/Li. Furthermore, LNMO is more thermally stable than NMC and has high ionic conductivity. However, LNMO suffers from rapid capacity decay leading to short battery life, and high-voltage electrolytes that are resistant to decomposition at the higher operating voltages are required.
LNMO forms two phases depending on the ordering of transition metals (TM). In the disordered phase, Ni and Mn ions are randomly distributed on the 16d sites of the Fd3̅m cubic unit cell, whereas in the ordered phase, the which Ni and Mn atoms occupy 4b sites and 12d sites of the P4332 cubic cell, respectively. In this work, the impact of TM ordering on fundamental parameters such as the unit cell size, electrode expansion, and Li-ion diffusion coefficients at different states of charge were explored using techniques such as in-operando x-ray diffraction, in-situ dilatometry, galvanostatic intermittent titration technique, and electrochemical impedance spectroscopy. The electrodes for these studies were prepared using both PVDF and water-based binders such as CMC in order to gain key insights into the effect of aqueous electrode processing on the Li+-ion transport parameters, interface resistances, and electrode expansion during cycling.
Rapid Inverse Parameter Inference Using Physics-Informed Neural Networks
Authors: Hassanaly Malik , Weddle Peter J , Randall Corey R , Dufek Eric J. , Smith Kandler 
Published: August 2024

As Li-ion batteries become more essential in today's economy, tools need to be developed to accurately and rapidly diagnose a battery's internal state-of-health. Using a Li-ion battery's (high-rate) voltage response, it is proposed to determine a battery's internal state through Bayesian calibration.
However, Bayesian calibration is notoriously slow and requires thousands of model runs. To accelerate parameter inference using Bayesian calibration, a surrogate model is developed to replace the underlying physics-based Li-ion model. Developing a surrogate model for rapid Bayesian calibration analysis is discussed for both the single particle model (SPM) and the pseudo two-dimensional (P2D) model.
Surrogate models are constructed using physics-informed neural networks (PINNs) that encode the influence of internal properties on observed voltage responses. In practice, a neural network can be trained by: 1) using simulation results of the physics-based model (i.e., a data-loss approach); 2) using the residuals of the governing equations themselves (i.e., a physics-loss approach); or 3) using a combination of simulation results and governing equation residuals. In the present work, PINNs are developed using a variety of training losses and neural network architectures. In this analysis, it is shown that a PINN surrogate model can be reliably trained with only physics-informed loss. However, using a coupled data-informed and physics-loss approach produced the most accurate PINNs. Figure~\ref{fig:spm_2d} illustrates the absolute relative errors of trained PINN networks using several different training losses and neural network architectures.
After determining a consistent training strategy for both the SPM and P2D PINN surrogate models, the PINNs are extended to determine additional internal state-of-health parameters. As more and more parameters were introduced, the PINN training suffered from ``the curse of dimensionality", which was mitigated by using a hierarchical training approach (where a PINN trained with fewer variable model parameters was used to train a PINN with more variable model parameters).
Next, the high-dimensionality PINN surrogates are then integrated into Bayesian calibration schemes to identify internal Li-ion battery properties from experimentally measured voltages. Interpreting the high-dimensional parameter posteriors is discussed with respect to model error, parameter prior choices, and experimental errors.

Figure 1