Force Shadows: An Online Method to Estimate and Distribute Vertical Ground Reaction Forces from Kinematic Data.

Kinetic models of human motion rely on boundary conditions which are defined by the interaction of the body with its environment. In the simplest case, this interaction is limited to the foot contact with the ground and is given by the so called ground reaction force (GRF). A major challenge in the reconstruction of GRF from kinematic data is the double support phase, referring to the state with multiple ground contacts. In this case, the GRF prediction is not well defined. In this work we present an approach to reconstruct and distribute vertical GRF (vGRF) to each foot separately, using only kinematic data. We propose the biomechanically inspired force shadow method (FSM) to obtain a unique solution for any contact phase, including double support, of an arbitrary motion. We create a kinematic based function, model an anatomical foot shape and mimic the effect of hip muscle activations. We compare our estimations with the measurements of a Zebris pressure plate and obtain correlations of 0.39≤r≤0.94 for double support motions and 0.83≤r≤0.87 for a walking motion. The presented data is based on inertial human motion capture, showing the applicability for scenarios outside the laboratory. The proposed approach has low computational complexity and allows for online vGRF estimation.

Modeling and Fundamental Dynamics of Vacuum, Gas, and Antisolvent Quenching for Scalable Perovskite Processes.

Hybrid perovskite photovoltaics (PVs) promise cost-effective fabrication with large-scale solution-based manufacturing processes as well as high power conversion efficiencies. Almost all of today's high-performance solution-processed perovskite absorber films rely on so-called quenching techniques that rapidly increase supersaturation to induce a prompt crystallization. However, to date, there are no metrics for comparing results obtained with different quenching methods. In response, the first quantitative modeling framework for gas quenching, anti-solvent quenching, and vacuum quenching is developed herein. Based on dynamic thickness measurements in a vacuum chamber, previous works on drying dynamics, and commonly known material properties, a detailed analysis of mass transfer dynamics is performed for each quenching technique. The derived models are delivered along with an open-source software framework that is modular and extensible. Thereby, a deep understanding of the impact of each process parameter on mass transfer dynamics is provided. Moreover, the supersaturation rate at critical concentration is proposed as a decisive benchmark of quenching effectiveness, yielding ≈ 10-3 - 10-1s-1 for vacuum quenching, ≈ 10-5 - 10-3s-1 for static gas quenching, ≈ 10-2 - 100s-1 for dynamic gas quenching and ≈ 102s-1 for antisolvent quenching. This benchmark fosters transferability and scalability of hybrid perovskite fabrication, transforming the "art of device making" to well-defined process engineering.

Discovering Process Dynamics for Scalable Perovskite Solar Cell Manufacturing with Explainable AI.

Large-area processing of perovskite semiconductor thin-films is complex and evokes unexplained variance in quality, posing a major hurdle for the commercialization of perovskite photovoltaics. Advances in scalable fabrication processes are currently limited to gradual and arbitrary trial-and-error procedures. While the in situ acquisition of photoluminescence (PL) videos has the potential to reveal important variations in the thin-film formation process, the high dimensionality of the data quickly surpasses the limits of human analysis. In response, this study leverages deep learning (DL) and explainable artificial intelligence (XAI) to discover relationships between sensor information acquired during the perovskite thin-film formation process and the resulting solar cell performance indicators, while rendering these relationships humanly understandable. The study further shows how gained insights can be distilled into actionable recommendations for perovskite thin-film processing, advancing toward industrial-scale solar cell manufacturing. This study demonstrates that XAI methods will play a critical role in accelerating energy materials science.

Danger in the Dark: Stability of Perovskite Solar Cells with Varied Stoichiometries and Morphologies Stressed at Various Conditions.

The long-term stability of perovskite solar cells (PSCs) remains a bottleneck for commercialization. While studies on the stoichiometry and morphology of PSCs with regard to performance are prevalent, understanding the influence of these factors on their long-term stability is lacking. In this work, we evaluate the impact of stoichiometry and morphology on the long-term stability of cesium formamidinium-based PSCs. We demonstrate that the lead iodide (PbI2) to formamidinium iodide (FAI) ratio influences stability under various stress factors (elevated temperature and light). A high molar ratio (PbI2/FAI > 1.1) in the perovskite precursor displays drastic degradation under ISOS-L1 (100 mW/cm2, 25 °C, maximum power point tracking) conditions. However, postdegradation analysis contradicts these results. Devices with PbI2/FAI ≤ 1.1 are stable under light, but intermittent current density-voltage characterizations indicate that device performance decreases during storage in the dark. Migration of iodide (I-) ions to the electron-transport layer (ETL) and iodine vacancies (VI-+) to the hole-transport layer (HTL) forms localized shunts in the absorber layer. Pinhole formation, surrounded by FA+-rich regions, explains the extent of damage in comparably aged films. In summary, this work emphasizes the importance of reporting stability under different stress conditions, coupled with postdegradation and dark recovery analyses of PSCs to better understand the complexities of perovskite instability under real-life conditions such as expected during outdoor operation.

Triple-junction perovskite-perovskite-silicon solar cells with power conversion efficiency of 24.4.

The recent tremendous progress in monolithic perovskite-based double-junction solar cells is just the start of a new era of ultra-high-efficiency multi-junction photovoltaics. We report on triple-junction perovskite-perovskite-silicon solar cells with a record power conversion efficiency of 24.4%. Optimizing the light management of each perovskite sub-cell (∼1.84 and ∼1.52 eV for top and middle cells, respectively), we maximize the current generation up to 11.6 mA cm-2. Key to this achievement was our development of a high-performance middle perovskite sub-cell, employing a stable pure-α-phase high-quality formamidinium lead iodide perovskite thin film (free of wrinkles, cracks, and pinholes). This enables a high open-circuit voltage of 2.84 V in a triple junction. Non-encapsulated triple-junction devices retain up to 96.6% of their initial efficiency if stored in the dark at 85 °C for 1081 h.

Monolithic Two-Terminal Perovskite/CIS Tandem Solar Cells with Efficiency Approaching 25.

Monolithic two-terminal (2T) perovskite/CuInSe2 (CIS) tandem solar cells (TSCs) combine the promise of an efficient tandem photovoltaic (PV) technology with the simplicity of an all-thin-film device architecture that is compatible with flexible and lightweight PV. In this work, we present the first-ever 2T perovskite/CIS TSC with a power conversion efficiency (PCE) approaching 25% (23.5% certified, area 0.5 cm2). The relatively planar surface profile and narrow band gap (∼1.03 eV) of our CIS bottom cell allow us to exploit the optoelectronic properties and photostability of a low-Br-containing perovskite top cell as revealed by advanced characterization techniques. Current matching was attained by proper tuning of the thickness and bandgap of the perovskite, along with the optimization of an antireflective coating for improved light in-coupling. Our study sets the baseline for fabricating efficient perovskite/CIS TSCs, paving the way for future developments that might push the efficiencies to over 30%.