# Investigating the densification of Li6PS5Cl solid electrolyte through multi-scale characterization techniques

Ove Korjus, Saptarshee Mitra, Quentin Berrod, Victor Vanpeene, Markus Appel, Ludovic Broche, Sandrine Lyonnard, Claire Villevieille

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## To cite this version:

Ove Korjus, Saptarshee Mitra, Quentin Berrod, Victor Vanpeene, Markus Appel, et al.. Investigating the densification of Li6PS5Cl solid electrolyte through multi-scale characterization techniques. Energy Storage Materials, 2025, pp.104589. 10.1016/j ensm.2025.104589. hal-05253118

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Submitted on 13 Sep 2025

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# Investigating the densification of Li₆PS₅Cl solid electrolyte through multi-scale characterization techniques

Ove Korjus<sup>a,b,*</sup>, Saptarshee Mitra<sup>a</sup>, Quentin Berrod<sup>a,b</sup>, Victor Vanpeene<sup>a</sup>, Markus Appel<sup>b</sup>, Ludovic Broche<sup>c</sup>, Sandrine Lyonnard<sup>a,*</sup>, Claire Villevieille<sup>d,∗</sup>

## ARTICLE INFO

### Keywords:

Electrochemical impedance spectroscopy

X-ray computed tomography

Quasielastic neutron scattering

Cold sintering

Solid-state batteries

Thiophosphates

## ABSTRACT

Li₆PS₅Cl (LPSCI) has recently gained attention as a promising solid-state electrolyte for batteries. However, the mechanisms underlying the “cold sintering” process in LPSCI remain poorly understood. In this study, we performed *in situ* densification of LPSCI while simultaneously measuring electrochemical impedance spectroscopy and micro-tomography to gain deeper insights into “cold sintering” process and to correlate the ionic conduction with the three-dimensional microstructure of the solid electrolyte. We observed that the large (secondary) particles are fracturing, while the grain boundary (GB) conductivity is improving due to better contact between grains. We have found that during the pressure application (up to 510 MPa from 76.2 MPa) at room temperature, the conductivity increases 2.45 times (up to 1.66 mS cm⁻¹). From an in-depth electrochemical impedance and quasielastic neutron scattering (QENS) investigation, we show that the conductivity enhancement primarily arises from improved GB contact, with the bulk material remaining largely unaffected – that is, unsintered. However, the Li⁺ conductivity is not limited by bulk but by GB resistance. The electrolyte’s conductivity without any GB contribution is estimated from QENS results with the Nernst-Einstein equation to be 5.3 mS cm⁻¹, giving us the maximum conductivity that could be reached with shaping without modifying the bulk of the material.

## 1. Introduction

Solid electrolytes are one of the very few viable solutions that could lead to a breakthrough in battery safety since, contrary to organic liquid-based electrolytes, solid electrolytes are less flammable. Another significant advantage is the possibility of using Li metal as a negative electrode, which has a very high theoretical capacity (3860 mAh g⁻¹), increasing the energy density of the system. The search for novel solid ionic conductors is a very active research topic due to several parameters it must fulfill: i) a reasonable ionic conductivity (10⁻³ S/cm) at room temperature, ii) a low cost, iii) an easy processability, iv) a good chemical/electrochemical stability and v) a decent mechanical properties, so it would be possible to sinter/densify it under reasonable conditions. Based on the pre-listed criteria, thiophosphate solid electrolytes seem to fulfill most of them compared to their ceramic Li-ion conducting counterparts, and they especially have the advantage of being densified at room temperature, i.e., “cold sintered” [1–3].

Among the thiophosphate family, Li₆PS₅Cl (LPSCI) stands out as a commercially available solid electrolyte with promising ionic conductivity at room temperature. However, the literature presents a wide range of LPSCI ionic conductivity values, spanning from 0.02 mS cm⁻¹ to 4.73 mS cm⁻¹ at room temperature [4–14], depending on the parameters used to obtain a solid electrolyte pellet. For LPSCI, it is known that annealing of the powder at 550 °C can lead to a significant gain in ionic conductivity [4,15,16]. The highest ionic conductivity (4.73 mS cm⁻¹) was achieved by Yu et al [4], who employed a thermal treatment at an optimal high temperature (550 °C) to enhance crystallinity. However, this process is not feasible for industrial-scale production. It is also well-known that higher-pressure densification can reduce porosity in the solid electrolyte, thereby increasing ionic conductivity. Wang et al [17] demonstrated that “hot pressing”, applying pressure simultaneously with heating, can reduce porosity and significantly increase the pellet’s conductivity compared to cold pressing at the same pressure, yielding 0.66 mS cm⁻¹ at room temperature versus 3.56 mS cm⁻¹ at

<footnote><sup>a</sup> Univ. Grenoble Alpes, CEA, CNRS, Grenoble INP, IRIG, SyMMES 17 rue des Martyrs F-38000 Grenoble, France</footnote>

<footnote><sup>b</sup> Institut Laue Langevin, 71 rue des Martyrs F-38000 Grenoble, France</footnote>

<footnote><sup>c</sup> European Synchrotron Radiation Facility, 71 rue des Martyrs F-38000 Grenoble, France</footnote>

<footnote><sup>d</sup> Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, Grenoble INP, LEPMI F-38000 Grenoble, France</footnote>

<footnote>* Corresponding authors.</footnote>

<footnote>E-mail addresses: korjus@ill.fr (O. Korjus), sandrine.lyonnard@cea.fr (S. Lyonnard), claire.villevieille@grenoble-inp.fr (C. Villevieille).</footnote>
200 °C. Yet, pressure and temperature are not the only factors to consider for enhancing ionic conductivity in a specific material; pressure application time, powder quality, powder granulometry, surface chemistry, and the presence of impurities all contribute to the significant variance in ionic conductivity for the same material.

Recently, studies have shown that the amount of porosity is not the sole parameter to decide whether a solid electrolyte is properly densified. As an example, Perrenot et al [18] demonstrated that amorphous $Li_3PS_4$ could have similar ionic conductivities while using different “cold sintering” protocols, but the distribution of remaining porosity was far from being identical between the samples. Indeed, one of them was prone to dendrites due to a 3D pore percolation network, showing the importance of a detailed 3D microstructure investigation beyond global porosity metrics [18]. Despite the importance of sintering temperature and pressure on the properties of the final material, it has been scarcely studied. To date, there is no general understanding of the “cold sintering” process of LPSCl solid electrolytes and the relevant parameters that can improve their densification and, thus, their ionic conductivity. Indeed, the structural and morphological evolution during “cold sintering” defines the properties of the solid electrolyte since the ion transport mechanism is defined by two different processes – the bulk and grain boundary (GB) conduction. In order to get a detailed understanding of what is happening with the material, the GB and bulk ionic conductivity should be monitored separately, and their dependence on structural evolution should be analyzed individually [19].

In this paper, we conducted an *in situ* “cold sintering” of $Li_6PS_5Cl$ solid electrolyte while simultaneously measuring Electrochemical Impedance Spectroscopy (EIS) and synchrotron µ-computed tomography (µ-CT) to link the conduction mechanism to the 3D microstructure of the solid electrolyte. In the *in situ* experiment, the measured ionic

conductivity was separated into bulk and grain boundary (GB) contributions by repeating the measurements at low temperatures, allowing these processes to be resolved at lower frequencies. To further improve the timescale resolution, the Distribution Function of Relaxation Times (DRT) analysis was applied to the impedance data, enabling clearer separation of the individual processes. The information obtained from µ-tomography has been correlated with additional probes such as Neutron Powder diffraction (NPD, D2B at ILL) and *ex situ* holo-tomography measurements performed at ID16b beamline at ESRF. Finally, QuasiElastic Neutron Scattering (QENS, IN16b at ILL) gave impedance-independent information about Li-ion diffusivity in the electrolyte at molecular scales and the conduction limit achievable with low-temperature material shaping of LPSCl. This combined multi-technique investigation allowed us to correlate the increase in ionic conductivity during “cold sintering” to enhanced $Li^+$ grain boundary transport.

## 2. Experimental section

The overall experimental design (Fig. 1) aims to investigate the effects of applied pressure on Li-ion conduction and microstructural evolution. Among the employed techniques, diffraction provided the finest length scale, probing atomic positions and crystallite sizes across length scales ranging from 0.1 Å to $10^3$ Å, averaged over the entire sample. Quasielastic neutron scattering (QENS), in the chosen configuration, was sensitive to $Li^+$ ion jumps of <30 Å, within a timescale of 10 ps to 1 ns, also averaged over the sample. Impedance spectroscopy captured $Li^+$ conduction dynamics over a broader and slower timescale, from 0.1 µs to 1 ms. For structural imaging, nanotomography offered a pixel size of 50 nm (with an effective resolution of ~150 nm) and a

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Schematic overview of the experimental design, highlighting the techniques employed—nanotomography, microtomography, electrochemical impedance spectroscopy, quasielastic neutron scattering, and neutron powder diffraction—along with their respective spatial and temporal resolution ranges.</figcaption></figure>
cylindrical field of view measuring 128 µm in diameter and 100 µm in height. In contrast, microtomography (µ-tomography) used a pixel size of 600 nm (with a resolution of ~1.8 µm) and a cylindrical field of view 1.5 mm in diameter, encompassing the full pellet height, which varied from 330 to 480 µm during the *in situ* experiment.

## 2.1. Cells

All the measurements were performed with a commercial Li₆PS₅Cl (LPSCI) electrolyte material (NEI corporation, USA) using stainless steel electrochemical cells. During the cell preparation, about 50 mg of LPSCI is introduced into a polyoxymethylene (POM) spacer, which acts as a container for pressing the electrolyte powder, a pellet holder, and an electrical insulator between the two opposite blocking electrodes [20]. All cell preparations mentioned in this work were performed in an Ar-filled glovebox (<1 ppm of water and oxygen).

## 2.2. X-ray micro-tomography

X-ray micro-tomography analyses were conducted at the European Synchrotron Radiation Facility (ESRF) beamline ID19. The supplementary information shows the setup used at ID19 (Figure S1). The *in situ* pressing experiment was conducted with stepwise pressure application, as seen in the supplementary information (Figure S2). The initial “cold sintering” pressure of the LPSCI powder was 76.2 MPa, which was the minimum pressure needed to keep the cell airtight. After initial characterization of EIS and µ-tomography, the pressure was increased to four higher pressures (127 MPa, 255 MPa, 382 MPa and 510 MPa) and the measurement was repeated at those pressures. Additionally, to see the effect of pressure holding time, the pressure was maintained at each pressure for 30 min, and then the measurement repeated. Finally, the pressure was released back to 76.2 MPa and characterized to see if there was any effect of pressure release. During the µ-tomography measurements, the sample was exposed transversally to the X-ray beam, and a detector captured the transmitted beam along a 177° rotation range. Ideally, we would have done a 360° or at least a 180° rotation, but the metal pillars of the press limited the data acquisition angle. Photon energy was about 70–80 keV (filtered white beam), and the detector had 2560 × 2560 pixels resolution with an equivalent spatial sampling of about 0.6 µm voxel⁻¹.

## 2.3. Image segmentation

The 3D volumes were reconstructed from the 2D projections using the Nabu software (ESRF). 3D image processing, filtering, particle segmentation, and quantitative analysis were done using Fiji distribution of ImageJ [21], python, and Ilastik [34]. Post-processing began with cropping and scaling the stack of images. Reconstructed X-ray Computed Tomography (X-CT) images were then filtered using a variance-weighted anisotropic diffusion 3D filter [22] and a patch-based 3D filter [23] to uniformly reduce noise while preserving the particle edges as sharply as possible.

This study followed the random forest implementation within the Ilastik software’s “Pixel Classification” workflow [24] Ilastik’s default setting of 100 trees was used. Ilastik performs the classification of pixels using the output of image filters (including pixel colour and intensity, edge filters, and texture descriptors) as features and “Random Forest” as a classifier. For this study, an individual Ilastik project was created for each scanned sample, which enabled the segmentation of all details captured by the same trained classifier. All samples were segmented into two feature classes: (i) pore and (ii) particles. After the segmentation, the particles were separated with the watershed algorithm [25]. The tortuosity was calculated using a method introduced by Chen et al [26]. More details have been provided in **Supplementary Note 1**.

**Figure S3** shows the microstructure at the initial applied pressure of 76.2 MPa, displayed both as a binary image (Figure S3a) and as a

segmented image processed using watershed transformation (Figure S3b).

## 2.4. Impedance

The impedance measurements were conducted with an SP300 (BioLogic Science Instruments). A CTS “T-series” (CTS Nederland B.V.) benchtop temperature chamber was used for the temperature-controlled experiments. The spectra were collected at open circuit voltage with a signal amplitude of 10 – 100 mV (depending on temperature; at lower temperatures, 100 mV amplitude was used). The impedance was measured in a frequency range from 7 MHz to 10 Hz. Three consecutive EIS spectra were collected upon temperature stabilization (2 to 4 h, depending on the temperature setpoint). The ionic conductivity values were normalized to the pellet geometry. The Kramers-Kroening linearity test confirmed that the linearity condition was fulfilled in the analyzed frequency region (residuals were under 5 %) before the impedance analysis. Both qualitative distribution functions of relaxation times analysis and CNLS-fitting were performed with the Relaxis3 software package (rhd instruments, Germany). The regularisation parameter, λ, was chosen using Lambda-plot and set to 0.001 for all the calculations. The shape factor has been set to 0.5.

## 2.5. Quasi-elastic neutron scattering

For QENS measurements, 2 g of LPSCI, either as a powder or pressed into two 18 mm pellets at 510 MPa, were employed. The samples were sealed in a flat Al-sample holder with In-wire and kept under an Ar protective atmosphere. The QENS measurements were performed at IN16b (Institut Laue-Langevin, Grenoble, France), a sub-µeV energy resolution backscattering spectrometer. The experiments were performed using the standard unpolished strained Si(111) monochromator and analyzer corresponding to an incident wavelength of 6.27 Å (covering a *q*-range between 0.2 and 1.8 Å⁻¹), an instrument energy resolution of 0.7 µeV FWHM and a dynamic range of ±30 µeV. *q* is the momentum transfer defined as $q = (4\pi/\lambda) \times \sin(\theta/2)$, where λ is the wavelength of the incident neutron beam and θ is the total scattering angle. Data have been treated with the QENSH software (available at: www.llb.cea.fr/en/Phocea/Page/index.php?id=21) and sing single-Lorentzian fitting of the quasielastic component and using Vanadium (measured at 300 K with same procedure as sample) for resolution.

## 2.6. X-ray nano-holotomography

The X-ray nano-tomography data was collected at the European Synchrotron Radiation Facility (ESRF) beamline ID16b. For the measurement, a 1 mm diameter cylinder was punched out of a 500 µm thick LPSCI pellet (7 mm diameter), which had been densified at 382 MPa for 30 min. The cylinder was fixed onto a metal piston and sealed with a 2.5 mm PTFE tube (Figure S4). The region of interest was 128 × 108 µm with a voxel size of 50 nm. The acquisition time for the four different holography distances was 22 min (3203 projections with 50 ms exposure time) with a 17 keV X-ray energy. 3D reconstructions were achieved in two steps: (i) phase retrieval calculation using an in-house developed octave script based on a Paganin-like approach using a delta/beta ratio of 139 and (ii) filtered back-projection reconstruction using ESRF software PyHST2 [27].

## 2.7. Neutron powder diffraction

D2B, the high-resolution beamline two-axis diffractometer (Institut Laue-Langevin, France), was used to measure the neutron diffractograms. Approximately 2 g of LPSCI sample was introduced in a Ø8 mm vanadium capillary, sealed with In-wire, and kept under an Ar protective atmosphere. The diffractogram was collected at room temperature in the high-intensity mode for two hours. A wavelength of 1.594 Å was used,
and the detector's centre part was used in the integration for higher resolution. Fullprof [28] was used for Le Bail refinement to calculate the crystallite size and phase quantities.

### 3. Results

#### 3.1. *In situ* "cold sintering" of LPSCl

To follow the “cold sintering” process in the LPSCl solid electrolyte, we simultaneously monitored *in situ* the evolution of the pellet microstructure and the changes in ionic conductivity. This was done as a function of densifying pressure using X-ray computed tomography (X-CT) coupled with electrochemical impedance spectroscopy (Figures S1 and S2). Fig. 2a shows the ionic conductivity of the samples as a function of applied pressure (76.2–510 MPa) along with the corresponding changes in LPSCl pellet thickness, calculated from the X-ray tomographs. The pellet thickness decreases from 480 µm to 330 µm due to the material’s densification. It is directly correlated to a decrease in ionic resistance, as seen in the Nyquist plot (Fig. 2b). Using both Nyquist plots and pellet thickness measures, we could estimate the evolution of the ionic conductivity, $\rho$, at a specific applied pressure during *in-situ* “cold sintering” measurement (Fig. 2a, red curve). At the beginning of the experiment, the ionic conductivity was 0.66 mS cm$^{-1}$ and reached a value of 1.62 mS cm$^{-1}$ at the end (510 MPa), which is in good agreement with the literature [29]. As can be seen, the ionic conductivity of LPSCl is increasing drastically, improving even with a slight application of pressure. Then, starting at ca. 250 MPa, we notice that the densification begins to reach its limitation as the pellet thickness evolution starts to stabilize. At the same time, the ionic conductivity continues to increase slightly. Still, it reaches almost a plateau, as witnessed also in the evolution of the sample thickness (which corresponds to porosity) (Fig. 2a).

Two additional parameters were probed during the *in situ* “cold sintering” measurement: the impact of pressure holding time at each pressure step and the effect of the pressure release (from 510 MPa down to 76.2 MPa). In both cases, we found that the conductivity values mainly remained unchanged (see square data for 76.2 MPa in Fig. 2b). However, as mentioned in the introduction section, ionic conductivity is only one of multiple parameters that need to be checked [18]. Furthermore, the visible semi-circle’s resistance is a sum of at least two contributions – bulk and grain boundary resistance. At the measured conditions (temperature and frequency range), only a segment of the semi-circle is visible, which is insufficient to separate them and explain the gain in conductivity when the pressure is applied. An attempt to separate them will be presented later in the paper to understand the role

of the “cold sintering” process in more detail.

Since we could not start the *in-situ* densification experiment with LPSCl powder, we first analyzed the SEM images of the raw powder to see if there were any significant differences between the raw LPSCl powder and the pellet densified at 76.2 MPa. The SEM images of the precursor powder are given in Figure S5, and the particle size distribution (as a kernel density function) from one image (~450 particles) is given in Figure S6. The particle size distribution has three main populations: P1 (particles around 40 µm), P2 (particles around 20 µm), and P3 (<10 µm particles). This corresponds well with the synchrotron µ-tomography results of the 76.2 MPa slightly densified electrolyte (blue data in Fig. 3g and h); only the population of the smallest particles (<10 µm) is more significant compared to tomography results, which is likely due to the higher resolution of SEM images compared to *in situ* µ-tomography (202 nm/voxel vs. 600 nm/voxel).

Fig. 3g displays the effect of “cold sintering” on the particle size distribution of the LPSCl particles. For the sake of investigation, the particles are ascribed as ideal spheres. When the pressure is increased from 76.2 MPa to 255 MPa, the population P1 reduces to benefit the population P2. P2 proportion drastically increases and shifts from ca. 26 µm to 18 µm. This is a counterintuitive behavior, as we expect the particle tends to grow larger during “cold sintering” (particles merging). Our results indicate that during densification, the larger particles fracture under the pressure applied, resulting in smaller particles. The same trend can be seen when the pressure is increased to 382 MPa.

Interestingly, smaller particles become more prominent with increasing applied pressure. Despite this, the solid electrolyte’s ionic conductivity continues to rise, indicating either improved contact between particles or changes occurring in the bulk of the material. However, there is no indication of the “cold sintering” of the bulk of the material since the density of large particles is not changing (Supplementary Note 2 and Figure S7). Increasing the pressure further (382 MPa to 510 MPa) increases the fracturing of particles, and even more particles reside in population P3 (1.8 µm – 10 µm). Two important points should be noted. First, the analyzed region in the center of the sample is 1.77 mm$^2$, whereas the total sample area is 38.5 mm$^2$. Therefore, with increasing pressure, a greater fraction of particles enters the region of interest, making the observed reduction in large particles particularly notable. Second, the tomography pixel size is 0.6 µm, which limits the resolution and prevents accurate distinction of particles smaller than 1.8 µm.

At 510 MPa, the pressure was held for 30 min to see the effect of pressure holding time, but no change to the ionic conductivity was observed. However, in the pellet microstructure (obtained from X-CT),

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Electrolyte thickness and ionic conductivity of Li$_6$PS$_5$Cl electrolyte (a) at different densifying pressures (76.2, 127, 255, 382, 510 MPa) and the Nyquist plots at those same pressures (b).</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Raw middle-slice images (a–f) of the Li₆PS₅Cl electrolyte at various stages of cold sintering: 76.2 MPa, 255 MPa, 382 MPa, 510 MPa, 510 MPa for 30 minutes, and after pressure release to 76.2 MPa. (g) Particle size distributions at the corresponding stages, calculated as kernel density estimation (KDE). (h) Tortuosity distributions at three selected pressures: 76.2 MPa, 255 MPa, and 510 MPa.</figcaption></figure>

we observed that the densification is still ongoing at the particle level since after 30 min of pressure holding, the amount of small particles (P1) and especially (P2) decreases to the benefit of larger particles (P3) centered around 23 µm. Similar behavior was already observed in the work of Perrenot *et al* [18] for amorphous Li₃PS₄, where the particles reorganized themselves during pressure holding. During this time, the ionic conductivity is strictly the same, showing that the ionic conductivity is just an averaged metric that does not necessarily capture local morphological modifications or chemomechanical dynamics while being pressed for a longer time.

At the end of the measurement, the pressure was released, and the solid electrolyte's microstructure also relaxed. Indeed, the distribution of larger particles (P1) (30 µm—55 µm) becomes slightly broader. At the same time, the contribution of P2 and P3 decreases, indicating that the “cold sintering” of the solid electrolyte is not a fixed state and that, with time, the sample may relax and reorganize. This last point is interesting, considering that if the microstructure relaxes without electrochemical

activities, it might impact dendrite propagation or fracture, for example.

The geometrical tortuosity of the pellet is also impacted by the increase in “cold sintering” pressure (Fig. 3h). A geometrical tortuosity equal to 1 would mean that the path of Li⁺ ions from the top to the bottom of the pellet would be straight without any obstacle. The more the value deviates from 1, the longer the distance would be for Li⁺ ions to move across the material. Increasing the “cold sintering” pressure from 76.2 MPa to 510 MPa gradually shifts the geometrical tortuosity peak from 1.24 to 1.1, meaning that the reduction of the porosity is efficient and that the connection between particles improves, which likely is one of the reasons for the increased conductivity observed in Fig. 2a.

To further analyze the electrolyte microstructure evolution during the *in situ* “cold sintering” measurement, we also investigated the impact of uniaxial pressure on the shape of the particles using Sneed and Folk’s representation [30,31]. Graphical representation of different particle shapes observed in the Sneed and Folk plot is displayed in the
Supplementary information (Figure S8). We determined the shape of the LPSCl electrolyte particles at the lowest pressure (76.2 MPa) and the highest pressure (510 MPa) (Fig. 4a and b) for the three different particle size regions – <10 µm, 10–33 µm, and >30 µm, corresponding to the populations (P1, P2 and P3) observed in Fig. 3g. As expected, there is no defined particle shape in the smallest particle region ( < 10 µm). There are even quite irregular particles (slab or flat block) compared to the larger particles, which are mostly equant or slightly elongated. In this context, “particles” mean secondary particles or aggregates since the crystallite size is ~50 nm, calculated from the neutron powder diffraction Le Bail fit (Figure S9 and Table S1). Clearly, the large particles show no significant change in shape under the applied pressure during the “cold sintering” process. However, even if the particle’s shape looks similar after applying pressure, we observe that the amount of particles in each category drastically evolves. In the case of small particles ( < 10 µm, red dots in Fig. 4), their number has tripled from 3555 analyzed particles up to 10,241, and for medium particles (10–30 µm, green dots in Fig. 4), their amount has increased from 5787 to 14,011. At the same time, the number of the largest particles (blue dots in Fig. 4) decreased from 4424 to 2865 particles. These observations confirm the cracking of the largest particles, indicating again that the large particles are fracturing during the “cold sintering” process.

Another critical parameter to quantify is the total porosity charac-
teristics and their variations during the densification process. However,
micro-CT does not resolve porosities smaller than 1.8 µm, hence not
adequately accounting for the hierarchical pore structure in the elec-
trolyte. To gain insights into nanoporosities, we conducted *ex situ* nano-
holotomography and imaged the electrolyte morphology with submi-
cron resolution. The *ex situ* nano-tomography was conducted at one

particular pressure (382 MPa, which is also one of the pressures used in
the *in situ* LPSCl densifying experiment). In our case, we were limited to
a resolution of 50 nm/voxel because of the beam damage, which means
that the average crystallites are under the resolution limit to be detected
(resolution is around 3 times the voxel size). Also, some inhomogeneity
in the gray-scale value of LPSCl has been observed (**Supplementary
Note 3** and **Figure S10b**). Generally, the nano-tomography images
(**Figure S10**) confirm the results seen in µ-tomography – significant
intraparticle porosities and cracking in the particles. The image stack
was segmented, and the porosity value was estimated to be 9.5 vol %.
The porosity value obtained from *ex situ* measurements was used as a
reference to correlate thickness values derived from *in situ* µ-tomogra-
phy, enabling the estimation of porosity (vol %) at various stages of
densification. Since the pellet’s mass and crystallographic density
remain constant, any reduction in thickness is attributed to a decrease in
porosity. With a constant cross-sectional area, changes in thickness
translate linearly to changes in pellet volume—and consequently, to
porosity (**Figure S11**). The median pore diameter was 479 nm, and 10 %
of the total pore volume comes from pores larger than 1 µm in diameter,
which means that if we were only estimating porosity from *in situ*
µ-tomography, we would have biased results.

3.2. *Grain and bulk ionic conductivity*

To get more insight into the impact of the “cold sintering” pressure
on the ionic resistance (grain boundaries or bulk conductivity) of the
LPSCl electrolyte, a similar experiment was carried out at the laboratory
using the same procedure and setup as the one described for *in situ* “cold
sintering” but with high-precision impedance measurements at very low

<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Sneed and Folk’s representation of Li₆PS₅Cl electrolyte particles’ shape at different stages of “cold sintering”, calculated for initial pressure 76.2 MPa (a) and final pressure 510 MPa (b). Each dot corresponds to a particle, highlighting visually the changes in numbers of small (red), medium (green), and large (blue) particles after high-pressure sintering.</figcaption></figure>
temperatures. The goal is to deconvolute grain boundary and bulk
resistance. As seen from Fig. 5a, the characteristic frequency of the semi-
circle shifts to lower frequencies, which is logical since the resistance of
Li-ion conduction increases with the decrease in temperature, resulting
in a reduction of characteristic frequency (τ = RC, where τ is the char-
acteristic time, R is the resistance of the process, and C is the capacitance
of the process). In Fig. 5b, we can see the effect of the “cold sintering”
pressure on the Nyquist plot. Impedance decreases as pressure increases,
and the characteristic frequency of the semicircle increases slightly. This
indicates that either the ratio between bulk and grain boundary con-
ductivity has changed, and/or the nature of the processes has changed.
However, the bulk and the GB conductivities are difficult to separate
with complex nonlinear least squares (CNLS) fitting, even at the lowest
measured temperature. In order to enhance the separation, we applied
the distribution of relaxation times (DRT) model to the EIS spectra. The
DRT is usable when Kramers-Kroening analysis residuals are under 5 %
in the analyzed frequency range [32,33], and in our case, this value was
below 1 %. In Fig. 5c and d, we can see the calculated DRT for the same
data as in Fig. 5a and b We can see two separate processes, Pr1 and Pr2,
attributed to bulk and grain boundary ionic resistance. Small satellite
peaks can be seen at low characteristic time (high frequency), but DRT is
known to give small side peaks at high frequency [19], so they have not
been analyzed further in this work, taking into account that at very high
frequency, the setup (cable, cell, etc.) might also play a role. In Fig. 5d,

we can clearly see that the area of Pr2 decreases as a function of the
pressure applied, meaning that the resistance of this process also de-
creases. There is no apparent decline in the Pr1 area since the distri-
bution gets wider, which might mean that the distribution of particle
sizes changes (becomes broader).

CNLS fitting was used to quantify the properties of Pr1 and Pr2.
Based on the DRT results, the equivalent circuit was constructed con-
sisting of Li-ion bulk conductivity, grain boundary ionic conductivity,
and the contribution from blocking electrodes (Fig. 6b). The alpha value
(fractional exponent) for the first constant phase element (CPE) was
close to 1 (>0.99) for all the fits, showing ideal capacitive behavior. In
the case of CPE2, the alpha value was between 0.9 and 1. The capaci-
tance values for Pr1 were around 10<sup>-10</sup> F, and Pr2's was higher (~10<sup>-9</sup>
F), which indicates that Pr1 is bulk ionic conductivity and Pr2 is the GB
ionic conductivity [34,35]. Using the fit results and Arrhenius's relation,
we can extrapolate the activation energies of both processes (Fig. 6a and
Table 1). As seen, the GB resistance is significantly higher than the bulk
conductivity, meaning that the GBs are limiting for Li-ion conduction.
Secondly, the bulk ionic conductivity and its activation energy are very
little influenced by increasing the “cold sintering” pressure, meaning
that, most likely, the bulk (of the particle) does not significantly change
when pressures are applied up to 510 MPa. On the contrary, grain
boundary activation energy decreases heavily with the increase in
densification pressure, meaning that the conduction mechanism at the

<figure><img src="image_8.png" /><figcaption>**Fig. 5.** Nyquist plots (a and b) and DRT plots (c and d) of 382 MPa densified Li₆PS₅Cl electrolyte. Impedance temperature dependence between –18 and –36 °C (a and c) and pressure dependence from 76.2 to 510 MPa (at similar temperature –35 °C) (b and d). Pr1 and Pr2 in (c) and (d) correspond to electrochemical processes 1 and 2 respectively.</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>**Fig. 6.** Temperature dependence (so-called Arrhenius plots) of bulk and grain boundary (GB) conductivities measured from –40 to –20 °C (a) of Li₆PS₅Cl electrolyte at different “cold sintering” pressures (127, 255, 382, 510 MPa). The equivalent circuit used for fitting the impedance spectra is displayed in section (b). *R* denotes resistance, and *CPE* means a constant phase element. Quasielastic neutron scattering spectra *S*(|*q*|, *DE*) as a function of energy transfer (Δ*E*) measured at 380 K and averaged over momentum transfer (|*q*|) for powder, pellet pressed with 510 MPa, and elastic peak (c).</figcaption></figure>

<caption>**Table 1**</caption>

Activation energies of Li₆PS₅Cl electrolyte at different “cold sintering” pressures (127, 255, 382, 510 MPa). The activation energies were calculated from –40 to –20 °C from Arrhenius plots.

<table><thead><tr><th></th><th>E<sub>a,Rb</sub> [eV]</th><th>± [eV]</th><th>E<sub>a,RGB</sub> [eV]</th><th>± [eV]</th></tr></thead><tbody><tr><td>127 MPa</td><td>0.44</td><td>0.03</td><td>0.42</td><td>0.02</td></tr><tr><td>255 MPa</td><td>0.42</td><td>0.03</td><td>0.38</td><td>0.02</td></tr><tr><td>382 MPa</td><td>0.41</td><td>0.03</td><td>0.37</td><td>0.02</td></tr><tr><td>510 MPa</td><td>0.40</td><td>0.03</td><td>0.33</td><td>0.02</td></tr></tbody></table>

boundary changes with the application of higher pressure.

The low-temperature EIS results highlight the prominent grain boundary transport properties changes during the sintering process. To further verify the characteristics of bulk ionic motion, we used quasielastic neutron scattering (QENS), a powerful technique to probe molecular-scale ion dynamics in electrolytes [36]. By analyzing the dynamical structure factor *S*(*q*, Δ*E*), with *q* the momentum transfer and Δ*E* the energy transfer, it is possible to determine the nature of atomic/ionic movements (for instance, diffusive vs localized motions [37, 38]) and extract physical parameters as jump distances, residence times or diffusion coefficients, on a time scale of few hundred of ps over few Å to nm [39,40]. We measured raw powder and 510 MPa pressed pellets in the range of 300 K to 380 K using a high-resolution backscattering spectrometer. Comparing the Q-averaged scattering spectra at high temperature (Fig. 6c), we see that the signals from the raw powder and the 510 MPa pressed pellet both contain a well-defined, intense quasielastic broadening. These features are superimposed within experimental accuracy, indicating that the Li-ion dynamics is similar on the probed timescales. These results go in the direction of our impedance fitting, where only little changes in the bulk ionic conductivity or activation energy were noticed when pressing the pellet up to 510 MPa. Additionally, in both powder and pellet samples, the width of the quasielastic component increases with the momentum transfer *q*, revealing a long-range diffusive behavior at high temperatures. Clearly, the Li-ion mobility, and thus also the QENS signal, is heavily influenced by the measurement temperature, leading to the intense quasielastic signal at 380 K. In comparison, a very narrow quasielastic broadening is visible at 300 K because the room temperature dynamics are almost too slow to be resolved within the present experimental resolution (Figure S12). The Li-ion diffusion coefficients and residence times at 300 K, 350 K, and 380 K can be obtained from fitting the half-width at half-maximum (HWHM) of the QENS signal. The HWHM increased with the momentum transfer

Q and reaches a plateau around 1.5 Å⁻¹. This behavior is characteristic of jump diffusion and is well described by the Q-dependence predicted by the Chudley-Elliott model [41]. In this model, the motion of particles is represented as a sequence of instantaneous jumps assumed to be fixed, separated by an average residence time (Supplementary note 4). The data were fitted using a fixed jump length of 2.25 Å, a value derived from crystallographic data reported by Dewald et al [42].

The Chudley-Elliott fitting results are displayed in the supporting information (Figure S13). The activation energy calculated from diffusion coefficients obtained with QENS measurements and using the Arrhenius relation at different temperatures is similar for the 510 MPa pressed pellet and raw powder (like in the impedance case). However, the activation energy value is very different, 0.15 eV (±0.1 eV), from that of electrochemical impedance spectroscopy. The discrepancy in activation energy between EIS and QENS usually arises because impedance spectroscopy captures the overall conductivity on a macroscopic scale, which spans several orders of magnitude larger than the length scale of individual Li-ion jumps measured with QENS. Additional factors limiting Li diffusion at the macroscopic level likely contribute to the observed difference in activation energy between EIS and QENS.

Nernst-Einstein equation [43] has been used to calculate the ionic conductivity from the diffusion coefficient obtained from the QENS data fitting at room temperature (*D* = 2.28 10⁻¹¹ m² s⁻¹). The ionic conductivity value of the sample estimated by QENS is 5.3 mS cm⁻¹, which is far from the one obtained even with a densified sample. However, this is the ionic conductivity if there are no grain boundaries at all in the sample. Higher bulk ionic conductivity could be observed if the solid electrolyte is properly sintered (higher pressure and temperature). However, increasing the bulk conductivity is significantly less important than improving the GB ionic conductivity in the system since the maximum ionic conductivity (from impedance) is heavily restricted by the grain boundaries.

## 4. Conclusion

The electrochemical and microstructural evolution of LPSCl during “cold sintering” has been studied using multiple characterization techniques, mainly *in situ* µ-tomography and electrochemical impedance spectroscopy.

As expected, the ionic conductivity of the sample improves as a function of the pressure applied. Nevertheless, the ionic conductivity reaches a plateau at some point, and the microstructure continues to
evolve. There were no significant changes in the density and shape of observable particles in any used "cold sintering" pressure, meaning that the bulk properties of the big particles did not change during the experiment. However, cracking of large LPSCl particles was observed when applying high densifying pressures.

Impedance data have been deconvoluted into bulk and grain boundary contributions at low temperatures (–18 – –40 °C) using DRT and quantified with CNLS fitting. According to these results, the bulk ionic conductivity does not depend much on the pressure applied, and the Li-ion conduction is limited mainly by the grain boundaries, which is confirmed by QENS analysis. In that sense, “cold sintering” the solid electrolyte with pressures up to 510 MPa only reorganizes the particles, leading to improved contact and decreased porosity, while the bulk itself does not sinter. By calculating the ionic conductivity of the electrolyte without grain boundaries from QENS data using the Nernst-Einstein equation, we get 5.3 mS cm⁻¹, a 3.3 times higher value than the “cold sintered” electrolyte observed in this study (1.62 mS cm⁻¹). This means that the grain boundaries heavily restrict electrolyte Li⁺ conductivity, and there is room for significant improvement in material shaping and sintering. However, 5.3 mS cm⁻¹ is also far from the limit of LPSCl conductivity, which could be potentially reached using high-temperature or higher-pressure sintering, where the bulk starts sintering as well. Therefore, the term "cold sintering" may be misleading and should be reconsidered, as the bulk material does not undergo densification and, hence, is not truly "sintering" under these conditions.

## Data availability

The data that support the findings of this study are openly available starting from 2026. The ID19 is available at doi.org/10.15151/ESRF-ES-1108,105,347, and ID16B nanotomography data can be accessed at doi.org/10.15151/ESRF-ES-1259,505,667. Quasi-elastic neutron scattering (QENS) data is available at doi.ill.fr/10.5291/ILL-DATA.6–05–1081, and neutron powder diffraction (NPD) data at doi.ill.fr/10.5291/ILL-DATA.LTP-1–4. Data will be available upon reasonable request.

## Funding sources

ANR Grant OpInsolid is acknowledged for the financial support of this work. MA4929 "multi-scale multi-techniques towards a European battery hub" is acknowledged for synchrotron beamtime. The neutron beam time used in this work was allocated through long-term proposal LTP-1–4.

## CRediT authorship contribution statement

**Ove Korjus:** Writing – review & editing, Writing – original draft, Visualization, Methodology, Investigation, Formal analysis. **Saptarshee Mitra:** Methodology, Investigation, Formal analysis. **Quentin Berrod:** Writing – review & editing, Methodology, Formal analysis. **Victor Vanpeene:** Writing – review & editing, Methodology, Formal analysis. **Markus Appel:** Writing – review & editing, Investigation, Formal analysis. **Ludovic Broche:** Writing – review & editing, Formal analysis. **Sandrine Lyonnard:** Writing – review & editing, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization. **Claire Villevieille:** Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Investigation, Funding acquisition, Formal analysis, Conceptualization.

## Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Ove Korjus reports financial support was provided by French National Research Agency. Claire Villevieille and Sandrine Lyonnard reports financial support was provided by French National Research

Agency. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

The authors appreciate the possibility of using the Hybriden IRIG-SyMMES platform for a part of the electrochemical tests. The authors would also like to thank Dr. Sergio Federico Mayer for helping at the IN16b beamtime, Dr. Partha Paul for helping with ID19 data reconstruction, and Dr. Emmanuel Suard for support at neutron diffraction measurements.

## Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.ensm.2025.104589.

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