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This review provides an overview of emerging ultrafast synthesis technologies for energy and environmental applications. Representative ultrafast methods include Joule heating, plasma, laser, infrared, microwave, and flame-assisted synthesis, etc.

Chlorine-36, generally expressed as a ratio against stable chlorine (36Cl/Cl x1015), has a half-life of 301 kyr, thus it is a useful tracer for estimating residence time of old groundwater between 50 kyr - 1 Myr. An underutilised use of 36Cl/Cl is as a sensitive tracer of catchment scale processes such as: identifying sources of salinity, weathering, delineating groundwater-surface water interactions, quantifying irrigation infiltration, and identifying anthropogenic inputs.We highlight the utility of 36Cl/Cl for gleaning insights into regional natural and anthropogenic processes in the Nogoa, Namoi and Murrumbidgee river catchments of eastern Australia. All catchments are within important agricultural regions and are regulated by one or more large reservoirs in their headwaters. The Nogoa River (Lat 23°S) flows east and forms part of the Fitzroy River that meets the Coral Sea near the town of Rockhampton. The Namoi (Lat 30°S) and Murrumbidgee (Lat 35°S) rivers form part of the Murray-Darling Basin and flow westwards (inland) before joining the Darling and Murray Rivers respectively to flow south towards the Southern Ocean. River water was sampled bi-monthly in several stations from the upper to middle reaches of each river during two years between 2017-2020. Sampling took place during drought conditions; 2019 being the driest in ~120 years of instrumental records in many areas. Climatic conditions favoured sampling of baseflow with flows mostly relying on reservoir releases in some cases (Namoi River) until total reservoir and river dryness.At the ground surface 36Cl can be produced via two main pathways. Typically, the dominant source of 36Cl in surface water is atmospheric, which was produced in the troposphere and stratosphere via interaction of cosmic-ray protons and secondary neutrons with Ar. However, secondary cosmic-ray neutrons can produce 36Cl when they collide with rocks and minerals. These reactions are modulated by the composition of the geological materials and their elevation. The Nogoa and Namoi Rivers have similar basic geological materials in their headwaters at relatively lower altitudes, while the Murrumbidgee has abundant mafic and felsic igneous rocks in the headwaters at higher altitudes.In general, the Namoi River showed the higher 36Cl/Cl ratios (~650-300) followed by the Murrumbidgee River (~500-200) and the lowest readings were recorded in the Nogoa River (~200-100). These results do not follow simple latitudinal or elevation trends. In this presentation we discuss plausible geological and anthropogenic processes that may account for the observations.

Atomic scale imaging revealed that the deposition/stripping of Na from the β′′-Al2O3 solid electrolyte causes delamination cracks and the closure of the conduction planes.

The very high ionic conductivity of Li

Summary Advancing lithium-ion battery technology requires the optimization of cycling protocols. A new data-driven methodology is demonstrated for rapid, accurate prediction of the cycle life obtained by new cycling protocols using a single test lasting only 3 cycles, enabling rapid exploration of cycling protocol design spaces with orders of magnitude reduction in testing time. We achieve this by combining lifetime early prediction with a hierarchical Bayesian model (HBM) to rapidly predict performance distributions without the need for extensive repetitive testing. The methodology is applied to a comprehensive dataset of lithium-iron-phosphate/graphite comprising 29 different fast-charging protocols. HBM alone provides high protocol-lifetime prediction performance, with 6.5% of overall test average percent error, after cycling only one battery to failure. By combining HBM with a battery lifetime prediction model, we achieve a test error of 8.8% using a single 3-cycle test. In addition, the generalizability of the HBM approach is demonstrated for lithium-manganese-cobalt-oxide/graphite cells.

International audience; Layered cathode materials are commonly used in lithium and sodium ion batteries, but they are prone to degradation under electrochemical cycling during battery operation. Here we report a new type of degradation mechanism through the electrochemically induced mechanical buckling and delamination cracking of intercalation layers in a P2 Na0.7-Ni0.3Mn0.6Co0.1O2 (Na-NMC) cathode material. Kinks form in the delaminated layers due to severe local bending, and each kink consists of a vertical array of dislocations, resulting from an easy slip between transition metal oxide layers. In situ mechanical compression experiments directly reveal the kink formation due to strong mechanical anisotropy parallel and perpendicular to the intercalation layers in single-crystal Na-NMC. In situ electrochemical experiments indicate that kinks form during the desodiation process. Our results unveil a new mechanism of electrochemically induced mechanical degradation stemming from weak interlayer bonding in layered cathode materials. This work has broad implications for the mitigation of degradation associated with irreversible interlayer slip in layered cathode materials.

The increasing demand for safe and dense energy storage has shifted research focus from liquid electrolyte-based Li-ion batteries toward solid-state batteries (SSBs). However, the application of SSBs is impeded by uncontrollable Li dendrite growth and short circuiting, the mechanism of which remains elusive. Herein, we conceptualize a scheme to visualize Li deposition in the confined space inside carbon nanotubes (CNTs) to mimic Li deposition dynamics inside solid electrolyte (SE) cracks, where the high-strength CNT walls mimic the mechanically strong SEs. We observed that the deposited Li propagates as a creeping solid in the CNTs, presenting an effective pathway for stress relaxation. When the stress-relaxation pathway is blocked, the Li deposition-induced stress reaches the gigapascal level and causes CNT fracture. Mechanics analysis suggests that interfacial lithiophilicity critically governs Li deposition dynamics and stress relaxation. Our study offers critical strategies for suppressing Li dendritic growth and constructing high-energy-density, electrochemically and mechanically robust SSBs.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.

It is crucial to suppress lithium dendrite formation in lithium metal batteries. Formation of a good solid–electrolyte interphase (SEI) has been considered to be effective in limiting lithium dendrite growth. However, how the SEI may be modified during lithium deposition is hard to resolve due to challenges in in situ investigation of the SEI with fine details. We report an in situ study that uncovers the lithium dendrite suppression mechanism arising from SEI modification by a poly(diallyldimethylammonium chloride) (PDDA) cationic polymer film, using electrochemical liquid cell transmission electron microscopy (TEM). Lithium nanogranules are obtained in the presence of the polymer film. Chemical mapping of the deposits provides remarkable details of the SEI on individual nanogranules. It shows that lithium fluorides are uniformly distributed within the inner SEI layer of individual lithium nanogranules, arising from the instantaneous reaction of the deposited lithium with PF6− ions accumulated by the cationic polymer film, and thus the dendritic growth of lithium is prohibited. The ability to directly measure SEI chemistry at the nanoscale down to the individual nanograins in situ and unveil its correlation with the lithium deposition behavior opens future opportunities to explore unsolved mechanisms in batteries.

Energy storage systems (ESSs) are a critical component of the electric grid, dispatching (charging and discharging) to performing grid applications such as frequency regulation, energy arbitrage, and peak shaving. Today, lithium-ion batteries are considered the best electrochemical ESSs in grid applications, and various cathode chemistries have been developed. On the electric grid, batteries can provide up to 13 ESS services, and different combinations of grid services and chemistries produce different battery aging and life performance under the given dispatch. Therefore, the characterization of each grid application dispatch can give an insight into optimal participation strategies for lithium-ion chemistries for each grid service. In this paper, an efficient algorithm is presented which uses a dispatch interval matrix to capture metrics in the ESS dispatch relevant to lithium-ion battery aging and performance, and implements unsupervised learning and dimensionality reduction on this matrix to produce characteristic duty cycles of the dispatch, from which synthetic duty cycles are produced that are suitable for laboratory testing and fast simulation. The algorithm is demonstrated for the dispatch under the grid application of peak shaving. Finally, an electrochemical-aging model is used to simulate a lithium-ion battery under both the original power dispatch and the synthetic duty cycle to validate the effectiveness of the method proposed in this paper to retain the operating stress factors.

The application of N fertilisers to enhance crop yield is common throughout the world. Many crops have historically been, or are still, fertilised with N in excess of the crop requirements. A portion of the excess N is transported into underlying aquifers in the form of NO

Author(s): Jungjohann, KL; Gannon, RN; Goriparti, S; Randolph, SJ; Merrill, LC; Johnson, DC; Zavadil, KR; Harris, SJ; Harrison, KL | Abstract: The dramatic 50% improvement in energy density that Li-metal anodes offer in comparison to graphite anodes in conventional lithium (Li)-ion batteries cannot be realized with current cell designs because of cell failure after a few cycles. Often, failure is caused by Li dendrites that grow through the separator, leading to short circuits. Here, we used a new characterization technique, cryogenic femtosecond laser cross sectioning and subsequent scanning electron microscopy, to observe the electroplated Li-metal morphology and the accompanying solid electrolyte interphase (SEI) into and through the intact coin cell battery's separator, gradually opening pathways for soft-short circuits that cause failure. We found that separator penetration by the SEI guided the growth of Li dendrites through the cell. A short-circuit mechanism via SEI growth at high current density within the separator is provided. These results will inform future efforts for separator and electrolyte design for Li-metal anodes.

In this issue of Joule, Dahn and coworkers present the development of a hybrid lithium-ion/lithium-metal cell that allows for an extra boost of capacity when needed. This battery has the potential to help eliminate range anxiety with electric vehicles.

At an electrode, ions and solvent accumulate to screen charge, leading to a nanometer-scale electric double layer (EDL). The EDL guides electrode passivation in batteries, while in (super)capacitors, it determines charge storage capacity. Despite its importance, quantification of the nanometer-scale and potential-dependent EDL remains a challenging problem. Here, we directly probe changes in the EDL composition with potential using in situ vibrational spectroscopy and molecular dynamics simulations for a Li-ion battery electrolyte (LiClO4 in dimethyl carbonate). The accumulation rate of Li+ ions at the negative surface and ClO4- ions at the positive surface from vibrational spectroscopy compares well to that predicted by simulations using a polarizable APPLE&P force field. The ion solvation shell structure and ion-pairing within the EDL differs significantly from the bulk, especially at the negative electrode, suggesting that the common rationalization of interfacial electrochemical processes in terms of bulk ion solvation should be applied with caution.

Accurately predicting the lifetime of complex, nonlinear systems such as lithium-ion batteries is critical for accelerating technology development. However, diverse aging mechanisms, significant device variability and dynamic operating conditions have remained major challenges. We generate a comprehensive dataset consisting of 124 commercial lithium iron phosphate/graphite cells cycled under fast-charging conditions, with widely varying cycle lives ranging from 150 to 2,300 cycles. Using discharge voltage curves from early cycles yet to exhibit capacity degradation, we apply machine-learning tools to both predict and classify cells by cycle life. Our best models achieve 9.1% test error for quantitatively predicting cycle life using the first 100 cycles (exhibiting a median increase of 0.2% from initial capacity) and 4.9% test error using the first 5 cycles for classifying cycle life into two groups. This work highlights the promise of combining deliberate data generation with data-driven modelling to predict the behaviour of complex dynamical systems. Accurately predicting battery lifetime is difficult, and a prediction often cannot be made unless a battery has already degraded significantly. Here the authors report a machine-learning method to predict battery life before the onset of capacity degradation with high accuracy.

Author(s): Zhang, X; Wang, QJ; Harrison, KL; Jungjohann, K; Boyce, BL; Roberts, SA; Attia, PM; Harris, SJ | Abstract: We offer an explanation for how dendrite growth can be inhibited when Li metal pouch cells are subjected to external loads, even for cells using soft, thin separators. We develop a contact mechanics model for tracking Li surface and sub-surface stresses where electrodes have realistically (micron-scale) rough surfaces. Existing models examine a single, micron-scale Li metal protrusion under a fixed local current density that presses more or less conformally against a separator or stiff electrolyte. At the larger, sub-mm scales studied here, contact between the Li metal and the separator is heterogeneous and far from conformal for surfaces with realistic roughness: the load is carried at just the tallest asperities, where stresses reach tens of MPa, while most of the Li surface feels no force at all. Yet, dendrite growth is suppressed over the entire Li surface. To explain this dendrite suppression, our electrochemical/mechanics model suggests that Li avoids plating at the tips of growing Li dendrites if there is sufficient local stress; that local contact stresses there may be high enough to close separator pores so that incremental Li+ ions plate elsewhere; and that creep ensures that Li protrusions are gradually flattened. These mechanisms cannot be captured by single-dendrite-scale analyses.