# Selective recovery of Co(II), Mn(II), Cu(II) and Ni(II) by multiple step batch treatments with nanocellulose products

Francisco de Borja Ojembarrena, Eric van Hullebusch, Rémi Marsac, Noemi Merayo, Angeles Blanco, Carlos Negro

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► To cite this version:

Francisco de Borja Ojembarrena, Eric van Hullebusch, Rémi Marsac, Noemi Merayo, Angeles Blanco, et al.. Selective recovery of Co(II), Mn(II), Cu(II) and Ni(II) by multiple step batch treatments with nanocellulose products. Environmental Science and Pollution Research, 2024, 31 (59), pp.66725-66741. 10.1007/s11356-024-35699-0 . hal-04993496

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Selective recovery of Co(II), Mn(II), Cu(II) and Ni(II) by multiple step batch treatments with
nanocellulose products

Francisco de Borja OJEMBARRENAª, Eric VAN HULLEBUSCHᵇ, Rémi MARSACᵇ, Noemi MERAYOᶜ,
Angeles BLANCOª, Carlos NEGRO*ª

ªCellulose, Paper and Advanced Water Treatments Research Group, Department of Chemical Engineering, Complutense University of Madrid, Avda. Complutense s/n, Madrid, Spain

ᵇUniversité Paris Cité, Institut de Physique du Globe de Paris, CNRS, F-75005 Paris, France

ᶜETSIDI, Mechanical, Chemical and Industrial Design Eng. Dept., Universidad Politécnica de Madrid, Madrid, Spain

*e-mail address: cnegro@ucm.es
The recovery of Co(II), Mn(II), Ni(II) and Cu(II) from black mass e-waste solutions through
cellulose nanofibers (CNFs) and nanocrystals (CNCs) was investigated. These materials were
synthetized by TEMPO-oxidation followed by high-pressure homogenization, and acid
hydrolysis, respectively. The NC characterization included the measurement of consistency,
cationic demand, carboxylic content, dissolved amorphous cellulose, and transmittance at
λ=600 nm. These parameters revealed a high transmittance of the NC solutions and a large
presence of anionic groups onto the surface. The high surface area and charge of the NC justify
their high interaction with the cationic metals. Results indicate that short contact times (even 1
minute) and low sorbent doses (10 mg/L) at acidic pHs (2 to 4) implied remarkable sorption
capacities in most cases with more than 1 g/g of sorption capacity of Co(II), Mn(II) and Cu(II) in
single step sorption tests. Such levels of sorption capacities exceed in at least one order of
magnitude most of the literature values of metal recovery applying cellulosic materials. Isotherm
modeling through a combination of Langmuir and Freundlich models suggested that both
sorption and surface precipitation occurred. A novel procedure following multiple step batch
operation was applied for Mn(II) sorption. This new method was applied as a five-step process,
leading to a 4-fold and 18-fold increase of sorption capacity onto CNCs and CNFs, respectively,
compared to the single step process. Therefore, this process shows an innovative way to
implement the multiple step batch sorption with NC as an efficient and environmentally
friendly solution for the critical metals recovery from e-waste leachates.

Key-words: black mass, electronic waste, metal recovery, nanocellulose, multiple step batch
sorption, critical and strategic metals .
GRAPHICAL ABSTRACT

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ABBREVIATIONS

* BML: Black Mass Leachate

* CD: Cationic Demand

* CNCs: Cellulose Nanocrystals

* CNFs: Cellulose Nanofibers

* MSB: Multiple-Step Batch

* PDADMAC: Poly(diallyldimethylammonium chloride)

* PesNa: Polyethylenesulfonate

* TEMPO: 2,2,6,6-tetramethylpiperidin-1-yl-oxyl

* SSB: Single-Step Batch
# 1. INTRODUCTION

Worldwide production of electronic devices has been steadily increasing over the past few decades. This growth is driven by several factors, including technological advancements, increased consumer demand for electronics and the proliferation of smart devices . However, this rise in electronic devices production has also led to a corresponding increase in electronic waste, commonly referred to as e-waste . E-waste includes not only devices but also their components, such as batteries, screens, circuit boards, and more. Improper disposal of e-waste can lead to environmental pollution and health hazards. Toxic substances found in electronic components, such as heavy metals, can leach into the soil and water, posing severe risks to ecosystems and human health. Therefore, responsible e-waste management, including the recovery of valuable materials from e-waste is crucial, according to the principles of sustainability and circular economy. The global e-waste generation has increased by 2 Mt annually over the last decade up to the 61.3 Mt generated during 2023 and it is expected to grow to 75 Mt by 2030 (2023c). The amount of e-waste generated in Europe in 2022 reached 16.2 kg of electronic devices per inhabitant (Ruiz, 2023). Similar values were observed in other regions of the world as in Oceania (Tipre et al., 2021). However, only one fifth is recycled globally (Ruiz, 2023). Those levels indicate that, from the circular economy perspective, there is an important gap to promote the recyclability of these materials. Furthermore , there is an urgent need of innovative solutions to improve e-waste management and to recover valuable materials as metals (Rautela et al., 2023) . Metals are present in many ways: volatile metals (such as Cd or Zn), high added-value alloys (like Mn, Co or Ni) or enriched in the slag (rare earths) (Ambaye et al., 2020; Wang et al., 2022). The recovery of these metals is critical for the economic feasibility of the process, as their prices are rising exponentially in the last years, until reaching values in the order of 12.000 to 33.000 US$ per Mt, depending on the metal recovered (Raj et al., 2022). In addition, some of these metals are considered as *Critical Raw Materials* (such as manganese and cobalt) or as *Strategic Raw Materials* (such as lithium and vanadium).
*Materials* (such as nickel and copper) by the UE, which has highlighted the relevance of their recovery for the EU economy (2023b), mitigating the risks of supply disruptions.

Nowadays, different technologies can be used for the recovery of metals from e-waste, depending on the waste and the specific targeted metal as reviewed by Dutta et al. (2023). Hydrometallurgical and pyrometallurgical processes are the most common technologies, although there are other alternative treatments developed at industrial level (Do et al., 2023). Biohydrometallurgy has also gained relevance in the sector and it is expected to become a great alternative in the near future, but it still does not show the same level of implementation at industrial level (Roy et al., 2021). According to the state of the art, hydrometallurgy is efficient, predictable, and cost effective. Furthermore, it consumes less energy, results in high metals purity, and requires less capital cost than pyrometallurgy (Dutta et al., 2023) but wastewaters must be treated (Alipanah et al. 2021). However, talking about metal recovery from Li-ion batteries waste at industrial level, a combination of pyrometallurgy and hydrometallurgical treatments is applied in most of the facilities, and only two plants were running only with hydrometallurgical processes in 2019 (Larouche et al., 2020).

Hydrometallurgy-based processes include the separation of the metals from the crushed spent batteries, called black masses, by leaching in presence of acid, alkali or bacterial solutions and a subsequent purification step (Whitworth et al., 2022). Acid leaching at atmospheric pressure under HCl (2-6 M) or H₂SO₄ (1-4 M) has been widely applied to reach extraction yields of metals like manganese, cobalt, copper, nickel, lithium or aluminum up to 100% from spent Ni-based and Li-ion batteries (Larouche et al., 2020; Wang et al., 2022). As an idea of the levels of metal extracted from the e-wastes, the values reported of manganese, cobalt, and nickel levels in black mass leachates (BML) could reach dozens of grams per liter. Once the metals are dissolved, the second step of the recovery process consists of the selective recovery of these metallic ions.
Reaching high metal recoveries in this step is fundamental, to minimize the spillage of acidic wastewaters from the hydrometallurgical process (Chakraborty et al., 2022). This can be carried out by different operations, such as precipitation, solvent extraction, ion-exchange, cementation, absorption, electrodeposition, electrolysis, electrowinning, or sorption, besides their combinations (Kumar et al., 2022; Sethurajan et al., 2019; Wang et al., 2022; Ajiboye et al. 2023). Although processes like precipitation have been more utilized at industrial level (Saleem et al., 2023), sorption is considered in this paper as an interesting alternative since it is often used for the removal of heavy metals. It has several advantages: it is a simple and flexible operation, easy to scale up, it can be tailored to selectively target specific metals, environmental friendliness, it produces low waste and it requires a low energy consumption (Iftekhar et al., 2022). Furthermore, the enrichment of metals on the sorbent surface would facilitate their recovery at higher purity levels (Nithya et al., 2021). However, the choice of sorbent, process conditions, and overall process design is critical for a high efficiency since it will influence the effectiveness of the metal separation step.

To achieve higher sorption capacity on the sorbent surface, multi-step batch (MSB) operations can be carried out by splitting the equivalent dosed sorbent of a single batch treatment (SSB) into several steps. Although this MSB procedure achieves lower removal yields in each step, it maintains high levels of sorbate in the liquid bulk along the entire process. Consequently, the driving force, which is proportional to the difference between sorbate concentrations in both liquid and solid surface, promotes the movement of the sorbate from the liquid bulk to the sorbent surface (Ghaedi, 2021). A larger driving force reduces the contact time to reach high retention of sorbate per gram of sorbent, minimizing the volume of each batch. Therefore, the multistage process not only enhances the sorption efficiency, but also minimizes the total quantity of adsorbent making the process more economically attractive (Hijab et al. 2021).
However, to the best of our knowledge, the advantages of this concept have not been widely studied yet.

Various materials can serve as effective sorbents (fast kinetics, high capacities, robustness) for metal separation in hydrometallurgy based e-waste treatment, being activated carbons widely used; although the new trend is the use of sustainable biomaterials produced from cost-efficient raw materials (Kharissova et al., 2021). A main limitation is that metal uptake capacity is usually low. In a recent review dealing with metal sorption onto nanomaterials, there was just one case where metal uptake capacity above 1 g/g was reached, among the dozens of included articles (Jiang et al., 2023).

Nanocellulose (NC) has gained significant attention in recent years for its potential applications in various fields, including environmental remediation and metal recovery. These materials can be obtained from inexpensive lignocellulosic raw materials and agroforestry waste materials. TEMPO-oxidized CNF have been commonly used for the adsorption of several metals (Negro et al. 2020). As biosorbents they have gained a great interest (Kardam et al. 2014). Its unique properties, such as large aspect ratio, high surface area, and functionalization potential, make NC products attractive as sorbents for metal recovery. The large surface area facilitates the efficient adsorption and removal of contaminants. The surface charge of NC is key for optimal interactions with metals (Sanchez-Salvador et al. 2023). NC presents active functional groups such as carboxylic and hydroxyl groups. These surface groups can be easily modified through surface charge modification, hydrophilization and other techniques, which give a wide versatility and applicability to the NC products (Madivoli et al. 2016). NC products have been applied as metal sorbents, mainly focused on wastewater treatments (Reshmy et al., 2021), reaching relevant results in the removal of hexavalent chromium (Ojembarrena et al., 2022a; Ojembarrena et al., 2022b; Deng et al., 2024; Hu et al. 2023), nickel (Xie et al., 2011; Song et al., 2022), copper (Zhang et al., 2016), zinc or cadmium (Hokkanen et
al., 2013), among others. However, to the best of our knowledge, the potential use of NC for
metal recovery from e-waste leachates has not been fully investigated yet. Hong et al. (Hong
et al., 2019) have published the recovery of Pt from automobile waste leachates with
polyethyleneimine treated cellulose nanofibers (CNFs) and Xu et al. (2023) have demonstrated
the potential use of nanopapers made from cellulose and ionic covalent organic frameworks to
recover Au from e-waste leachates. Both studies shows that better sorption
capacities are obtained in these applications in comparison to wastewater treatment
applications.

The potential of cellulosic products for the recovery of metals opens new possibilities
to increase the recovery of metals from e-wastes. However, there is a real research need
in this field to fill the gap of knowledge required to optimize the process. Therefore, this
study is focused on the development of new knowledge for the recovery of metals from
complex solutions by the application of cellulose nanocrystals (CNCs) and CNFs. The recovery
potential of a group of metals specifically present in the composition of black masses was
studied, including cobalt, manganese, nickel, and copper from solutions harboring equivalent
concentrations to BML is assessed.

## 2. MATERIALS AND METHODS

### 2.1. Chemicals

The raw materials to produce CNFs and CNCs were bleached eucalyptus pulp and commercial
cotton linters, respectively. The reagents and chemicals used for the synthesis and
characterization of the celluloses were: hydrochloric acid (37% v/v) and sulfuric acid (98% v/v)
purchased from Labkem (Spain), sodium hydroxide pellets, sodium chloride, sodium bromide
and sodium hypochlorite solution (10% w/v) purchased from Panreac (Spain); hydroxylamine
hydrochloride, 2,2,6,6-tetramethylpiperidin-1-yl-oxyl (TEMPO), and silver nitrate purchased
from Sigma Aldrich (USA). Poly(diallyldimethylammonium chloride) (PDADMAC) and polyethylenesulfonate (PesNA) standard solutions of 0.25 meq/L were prepared from commercial concentrated solutions of 0.001 N of concentration purchased from BTG Instruments AB (Sweden). The metal salts used to prepare the synthetic solutions were the following: CuCl₂·2 H₂O and CoCl₂·6 H₂O, purchased from Fisher Scientific (USA); and MnCl₂·4 H₂O and NiCl₂·6 H₂O, purchased from Carlo Erba (Switzerland). Dialysis membranes (12000-14000 Da weight cut-off) were used for CNCs purification. 0.22 µm syringe filters were used for the filtration of blanks and treated samples. Standard solutions of Co, Mn, Cu and Ni for ICP calibration (1.000 mg/mL) were used for the calibration of the ICP device. All the utilized reagents were of analytical grade and the water applied for the preparation of solutions and dilutions was ultrapure water produced with MilliQ purity with a device supplied from Merck.

## 2.2. Methods

### 2.2.1. Synthesis of CNFs

The synthesis of CNFs was performed as indicated by Ojembarrena et al. (Ojembarrena et al., 2022b). Briefly, the eucalyptus kraft pulp at 1% w/w suspension was disintegrated using a commercial blender, then placed in a stirred beaker for the selective oxidation with hypochlorite solution using TEMPO (0.1 mmol/g dried cellulose) and NaBr (1 mmol/g dried cellulose) as catalysis (Xu et al. 2022). This pre-treatment reduces the energy cost required for the mechanical defibrillation of the cellulose in the homogenizer where individual nanofibers are isolated in a gel-like macrostructure. Two materials, CNFs-5, and CNFs-15, were obtained under two different oxidizing reagent doses: 5 mmol NaClO/g dried cellulose and 15 mmol/g. The reaction was maintained for two hours controlling the pH at 10 by adding NaOH. After that, the obtained materials were separated, washed and resuspended up to 1% w/w before being
introduced in the homogenizer during three cycles at 600 bars of pressure. Figure S1 displaying
the synthesis route of CNFs can be found in the supplementary material.

2.2.2. Synthesis of CNCs

To produce the CNCs, an acid hydrolysis process was followed to dissolve the amorphous part
of cellulose maintaining the crystalline part as detailed by Campano et al. (2020). The cotton
linters used as raw cellulosic material was introduced in sulfuric acid 64% w/w in a dose of 13.5
g dried material/mL acid at 45 °C of controlled temperature for 45 minutes to promote the
hydrolysis of the cellulose chain. After that, a ten-times equivalent volume of water was added
to the solution to complete the reaction and the sample was allowed to sediment for 24 h to
separate the nanocrystals from the dissolved amorphous cellulose material and acid excess. The
obtained sediment was washed and placed into 50 mL Falcon tubes for subsequent
centrifugation several times until the obtained supernatant shows turbidity, indicating that the
isoelectric point of the CNCs was reached and they could be resuspended. Finally, the remaining
acid present was separated by dialysis. The turbid suspension was poured into dialysis
membranes (12000 to 14000 Da) and the closed membranes were then added 5-L beakers filled
with ultrapure water. Water was replaced in batches until the pH value becomes stable and
close to pH 7. A final sonication of the suspension was performed to disperse the cellulose
nanocrystals and homogenize their concentration. Figure S1 displaying the synthesis route of
CNFs can be found in the supplementary material.

2.2.3. Characterization of the synthetized CNFs and CNCs

Physical-chemical characterization of the materials was carried out as in previous studies
(Ojembarrena et al., 2022b). The consistency of the CNF and CNC, which corresponds to the
amount (g) of solid material in 100 g of suspension, was determined as the ratio of solid material present after drying the sample at 60 °C during 24 h. It allows to calculate the sorbent doses. To evaluate the concentration of anionic active sites and to compare the electrical charge attractions, cationic demand (CD) was measured by titration of 0.1% w/w solutions of NC with Poly(diallyldimethylammonium chloride) (PDADMAC) by triplicate. In the case of CNFs, to know the active sites in the different samples, the carboxylic groups onto the surface were also determined , by conductimetric titration with NaOH standard solution of 1.25 g/L CNF suspension at pH 2.5-2.8 acidified with HCl. The nanofibrillation yield was estimated by the value of transmittance of 0.1% w/w solutions of CNFs at λ=600 nm (Tλ=600 nm). It is related to the efficiency of the process to break down cellulose into nanofibers. Finally, the CNC synthesis yield was evaluated by measuring the dissolved amorphous cellulose (DAC) as a function of the chemical oxygen demand (COD) of the supernatant separated from the acidic medium of hydrolysis. The yield losses in the process were quantified as the total of cellulose added as raw material minus the sum of solid amount of CNC produced and the DAC solubilized by the sulfuric acid.

CNFs and CNCs were morphologically examined using Optical Microscopy (OM) with a Zeiss Axio
Lab.A1 microscope, fitted with an AxioCam ERc 5s camera at 5x magnification (Carl Zeiss
Microscopy GmbH, Göttingen, Germany), and by Transmission Electron Microscopy (TEM) under
1000x magnification at the National Centre of Electronic Microscopy (Madrid, Spain) using a JEM
1400 microscope (JEOL, Tokyo, Japan). For sample preparation, 15 µL of a 10% Poly-l-Lysine
solution was applied to a copper grid coated with a continuous Formvar/carbon layer, followed
by the deposition of 12µL of a 0.005 wt% CNF suspension, which was left to dry prior to analysis
(Sanchez-Salvador et al. 2022; Campano et al. 2021). Aspect ratio was calculated from TEM
images in the case of CNCs and 15 TEMPO CNFs, whereas the difficulty to calculate AR in
5TEMPO require the use of other techniques, as the gel point methodology, based on
sedimentation of the NC at different concentrations (Sanchez-Salvador et al. 2024).
### 2.2.4. Sorption experimental procedure

The sorption experiments to determine the effects of the pH (1-6), the sorbent dose (10-1000 mg dried NC/L) and the initial concentration of metals (1 to 1000 mg/L) were carried out as equilibrium tests up to three hours. The applied conditions for each experiment for each combination of metal and nanocellulosic material are indicated in Table 1 :

<Insert here>

Table 1. Operating conditions applied during the batch test experiments for metal sorption using NC.

These tests were performed in 50 mL plastic Falcon® tubes, filled with 25 mL of individual synthetic metal solutions at the selected operation pH, fixed with HCl or NaOH solutions. Then, the corresponding doses of NC were added. Metal concentrations have been chosen according to the average values found in black mass leachates. The tubes were placed in a roller stirring device until the contact time was reached. After that, the samples were placed into the centrifuge Eppendorf 5810 R for 15 min at 4200 x g. A sample of each supernatant was filtered with 0.22 µm syringe filters for further analysis.

For the ICP measurement, the filtered samples were diluted with nitric acid 2% v/v solution to achieve concentrations in the order of the calibration curve of the device (below 50 mg/L). The metals were measured using a Spectrogreen (Germany) inductively coupled plasma optical emission spectrometer (ICP-OES) applying a sampling flowrate of 1 mL/min through the quartz nebulizer. All the experiments and measurements were performed in triplicates. The adsorbed amount ($q_{metal}$) was calculated with equations 1 and 2.

$$ \text{Adsorbent mass [g dried material]} = \text{Dosed solution mass [g]} \cdot \text{Consistency[\%]} \quad (1) $$

$$ q_{metal} \left[ \frac{\text{mg metal}}{\text{g adsorbent}} \right] = \frac{([\text{Metal}]_{\text{Blank}} - [\text{Metal}]_{\text{Treated}})[\text{mg/L}]}{\text{Adsorbent mass [g dried material]}} \cdot V_{\text{Treated}}[\text{mL}] \quad (2) $$
To represent the experimental data of variable initial concentration of each metal, two common isotherm models were selected to adjust the isotherm data: Langmuir and Freundlich equations. The first isotherm equation is usually applied to explain saturation processes, such as the coverage of the active sites on a monolayer sorption mechanism. Freundlich model is applied to represent the exponential growth of the experimental data, which in sorption terms is commonly associated to multilayer sorption (Ayawei et al., 2017). The non-linear equation of combined Langmuir and Freundlich models correspond to equation 3.

$$q_{L+F} \left[ \frac{mg \ metal}{g \ adsorbent} \right] = \frac{k_L \cdot q_{max} \cdot C_e[mg/L]}{1 + k_L \cdot C_e[mg/L]} + k_F \cdot (C_e[mg/L])^{\frac{1}{n_F}} \quad (3)$$

The adjustment of this equation was performed by the following procedure. Initially, an estimation of the Langmuir $k_L$ and $q_{max}$ for low concentration values, below 200 mg/L was carried out, until reaching the minimum residual sum of squares (RSS) in the fitting of these experimental data. The reason is that the treatment of low metal levels corresponds to where adsorption played the major role in the recovery mechanism. The $q_{max}$ was estimated as the same value for all the studied metals onto each type of NC as the base hypothesis is that the way the metals interact with the surface-active sites is equivalent for each metal. Once these parameters are estimated, $q_{max}$ value is kept fixed and the rest of the combined parameters are calculated to reach the lowest RSS in the whole analyzed interval. This method provides an accurate modeling of the experimental data and shows how both mechanisms are implicated in the interaction of each pair of NC -metal combinations.

After the determination of the pH conditions corresponding to the highest sorption capacities of each metal with each material, a first kinetic study was carried out to ensure that the equilibrium was reached in the rest of the experiments. The experimental procedure and main results of these experiments are presented in Figure S2 and discussed in detail in Annex 2 of the supplementary material.
Finally, the sorption under MSB operation was performed by repeating the mentioned
equilibrium sorption procedure to the treatment of a synthetic Mn(II) solution. The
experimental conditions of the tests are indicated in Table 1. After the first sorption step
the sample is centrifuged, to separate the metal, and the supernatant is treated again as shown
in Figure 1 to increase the metal recovery.

<Insert here>

Figure 1. Graphical scheme of MSB operation to treat Mn(II) solutions with nanocellulosic
sorbents

**3. RESULTS AND DISCUSSION**

**3.1. NCs characterization**

Table 2 summarizes the results obtained from the characterization of CNCs and CNFs samples.

The consistency of the synthetized CNFs was similar to those found in bibliography, as this value
is associated with the requirement of suspensions to enhance the high-pressure
homogenization process, as well as to avoid the clogging of the inner tubing (Xu et al., 2022).
The consistency of the CNCs after centrifugation was below 0.5 g/100 g in the same order than
the data from Wang et al. (2012), for the same synthesis route.

<Insert here>

Table 2. Physical-chemical parameters of the synthetized NC products

The production yield of the CNCs considering the losses and the DAC caused by the acid attack
onto the amorphous part of the cellulose chain was 17.5% ± 0.6%. Guo et al. (2016) obtained
a comparable value (18.3%) by treating softwood sulfite pulp under the same conditions of acid
concentration and time. According to their results, the overall yield of the operation was
enhanced by both increasing contact times and applying ultrasounds during the acid hydrolysis.
A total of 25.2 ± 0.5% of the initial cellulose was converted into DAC, lower than the previously
reported by Campano et al. (2021) when using cotton linters as raw material (33.8%). The
material losses between steps were the cause of the lower yield efficiency. Higher treatment
times would lead to an increased efficiency in the nanocrystals production but always under
acute control of operation parameters to prevent from excessive DAC generation by acid attack.

The CD was used to evaluate the capability of these nanomaterials to attract positive ion
charges. The results revealed the presence of a much lower CD in the case of CNCs than for CNFs
(Table 2 ). However, the CD of CNCs was higher than the ones obtained by Beltramino et al.
(2015) and Campano et al. (2020) for their corresponding CNCs synthetized from cellulase-
pretreated and raw cotton linters, respectively. According to these last authors, lower CD would
be associated to the presence of cationic charges due to the large generation of sulfate groups
after the sulfuric acid attack, which are not present in the untreated fibers (Beltramino et al.,
2015). The sulfuric acid-synthetized CNCs showed an anionic surface when pH values vary from
1 to 10 (Prathapan et al., 2016).

The difference of CD between CNFs-5 and CNFs-15 was not significant, meaning that the
introduction of a much higher amount of oxidizing reagent (NaClO) had little influence in the
final number of surface-active groups, compared to the difference between CNCs and CNFs. This
trend is different than the achieved by Serra et al. (2017), who produced several samples of CNFs
under variable NaClO doses (0.5 to 16 mmol/g). In their case, the CD values for CNFs-5 and CNFs-
15 were in the same order than the ones indicated in this study, but the authors reported that
the increase in CD value between 5 to 15 mmol/g was 65%. Nevertheless, these authors reached
a stable CD value of the synthetized CNFs between 10 to 16 mmol/g, reinforcing the concept
that there is a maximum value for this parameter which could not be exceeded with additional
NaClO in the medium. As in the case of CNCs, this anionic behavior of the TEMPO-oxidized CNFs has been shown to appear in a wide interval of pH in the case of CNFs synthesized in equivalent conditions, not even reaching the pH zero charge between pH values of 2 and 12 (Liu et al., 2016; Park et al., 2019).

The quantity of active sites was also measured in terms of carboxylic content in CNFs. The results were identical for both CNFs (around 1.55 mmol/g) and the same as the amount of CNFs-5 CD value. The superior value of CD of CNFs-15 compared to the carboxylic content would indicate the presence of other active groups onto their surface which are able to attract cations apart from carboxylic groups. Serra et al. (2017) also reported higher values of the CD than the carboxylic content of their TEMPO-CNFs produced under similar conditions. Nevertheless, in the case of the CNFs synthesized by these authors, the gap between both parameters is much higher (around 0.8 mmol/g of difference), than in the current study. In the present work, more than 90% of the total CD of CNFs-15 material would be associated to the carboxyl groups. These results suppose a significant rise in comparison with the TEMPO-oxidized CNFs produced by Campano et al. (2020), whose amount of carboxylic groups was 1.10 mmol/g, and remark the relevant capacity of attraction of cations of the CNFs produced in this study.

Finally, the transmittance of the suspensions at λ= 600 nm of suspensions of 0.1% w/w of CNFs was measured to evaluate the nanofibrillation yield of the process. CNFs-5 and CNFs-15 reached comparable results of 90.4 ± 0.5% and 89.7 ± 0.5% transmittance values, indicating a large transparency of the suspensions at that wavelength. These results agree with the data reported by Isogai et al. (2011), Xu et al. (2022), and Lee et al. (2021) for similar TEMPO-oxidized CNFs suspensions.

Morphological data shows the smaller width on CNF with respect to CNC and the higher fibrillation of CNF-15 due to the stronger chemical pre-treatment.
## 3.2. Single metal sorption onto nanocellulose products

### 3.2.1. Effect of the pH on the metal sorption

The pH effect on the sorption of Co(II), Ni(II), Mn(II), and Cu(II) onto the studied NC products was evaluated. Table S1 in the supplementary material summarizes the optimum pH to achieve the highest sorption of each metal with the different NC products. The experimental results of Co(II) sorption are shown in Figure 2.a. Both CNFs-5 and CNFs-15 show larger sorption capacities when the pH is increased over 4 and 2, respectively, and that the removal of Co(II) was low or negligible in the case of CNFs-15 when pH was below 1. This fact happened in most cases for each metal and material since the concentration of protons over 0.1 M generates a strong competition with the metal of interest occupying the active binding sites in the carboxylic groups. When using CNCs, Co(II) binding is less sensitive to pH variations since the sulfate groups are less affected by the pH. This caused the Co(II) amount adsorbed onto CNCs to be over 30 mg/g for all the tested pH conditions although higher values are obtained at pH below 4-5 because the CNCs are more negatively charged as the half-sulfate ester groups are in their acidic form. The maximum sorption capacities of the tested CNCs and CNFs with each metal at the optimum pH are shown in Figure 2.b. There is a large preference of the CNCs and CNFs-5 to Mn(II) and Cu(II) than to the rest of the contaminants, reaching sorption capacity values over 100 mg/g. Meanwhile, CNFs-15 shows a similar interaction with all the tested metals. The pH value used in each experiment corresponds with the pH of highest sorption capacities shown in Table S1 in the supplementary material. pH values between 4 and 5 favor the sorption of Ni(II) onto the three materials and Cu(II) onto CNFs-15 (Figure 2.a). In previous studies, Madivoli et al. (2016) reported this increasing trend of Cu(II) sorption capacities from pH 3 to pH 6 onto CNCs and Kardam et al. (2014) depicted a yield increase in Ni(II) removal through acid-treated CNFs when moving from pH 2 to 4 which remained constant at pH 6-6.5. For the rest of the metals, the tested CNFs and CNCs worked better while operated in the pH interval between 2 to 4. The recovery of Co(II) from nuclear industry wastewater
reported by Anirudhan et al. (2016) was also enhanced when pH was higher than 3.5 by using NC /nanobentonite composite thanks to the deprotonation of the surface carboxyl groups. In a recently published study, Silva and Orefice (Silva and Oréfice, 2023) showed only minor differences in Mn(II) removal efficiency between pH 2 and pH 6.5 intervals after reaching equilibrium by applying castor oil polyurethane foam containing cellulose-halloysite nanocomposite, as happened exactly while applying CNCs and CNFs.

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Figure 2. a) Experimental results of sorption capacity of Co(II) onto CNCs, CNFs-5 and CNFs-15 at pH from 1 to 6. Initial Co(II) concentration: 250 mg/L; sorbent dose: 500 mg/L; contact time: 180 min; room temperature; and b) maximum sorbed amounts at optimized pHs for Co, Mn, Cu and Ni onto CNCs, CNFs-5 and CNFs-15. Initial metal concentration: Co(II): 250 mg/L, Mn(II): 100 mg/L, Ni(II) and Cu(II): 80 mg/L; sorbent dose: 500 mg/L; contact time: 180 min; room temperature.

### 3.2.2. Effect of the sorbent dose on the metal sorption yield

The applied sorbent dose interval varied from 10 to 1000 mg/L and the pHs applied were the ones displayed in Figure 2 .b) and shown in Table S1 for each combination of metal and NC .

The experimental data and the correlation for the sorption of Mn(II) on the three nanocellulosic materials at the studied dose interval is shown in Figure 3 . The adjustment was performed by applying the following empirical equation:

$$q_{\text{metal}} \left[ \frac{\text{mg metal}}{\text{g adsorbent}} \right] = \frac{\left( a + \frac{b}{(\text{adsorbent dosage [mg/L]})^n} \right)}{g + r \cdot (\text{adsorbent dosage [mg/L]})^p} + c \quad (4)$$

The corresponding units of each parameter of the equation 5 are:

* a: [mg metal]

* b: $\left[ \frac{\text{mg metal}^{(n+1)}}{L^n} \right]$

* c: $\left[ \frac{\text{mg metal}}{\text{g adsorbent}} \right]$
* g: [g adsorbent]

* r: $\frac{[g adsorbent] \cdot (L)^p}{(mg metal)^p}$

* n and p are non-dimensional parameters

This equation showed a fair correlation with the experimental data. The resulting equation constants and correlation parameters are elaborated in the supplementary material in Table S2. The use of the equation 4 allows a precise prediction of sorption capacity of the tested metals over CNCs and CNFs surface between 3 orders of magnitude of measurement. As it was expected, as the sorbent dose increased, the sorption capacity decrease, obtaining the maximum sorption capacity at the lower doses. Between 10 and 100 mg/L of sorbent dose, it is observed a drastic drop in the sorbent capacity, slightly decreasing thereafter. The results plotted on Figure 4 indicate a good performance of the CNCs and CNFs at low sorbent addition, reaching over 2000 to 2500 mg/g of sorption capacity of Cu(II) and also of Co(II) in the case of CNCs, and in the order of 1000 mg/g for Mn(II) and Co(II) in the rest of the cases. Ni(II) apparently showed smaller interaction with the CNCs and CNFs-5 at low doses. These uptake levels are in the same order of magnitude to the one obtained by Xu et al. (2023) during the recovery of gold from automobile waste acid leachate (200 ppm of Au), which found out a total capacity of 1.9 g/g of Au recovery with nanopapers of cellulose fibers and guanidinium-based ionic covalent organic framework. However direct comparison is limited by the use of different metals and sorbents. An increase of the sorbent amount it is supposed to lead to lower sorption capacities, which in this case dropped up to about 50 mg/g in most of the analyzed cases. Such levels of sorption were similar to the ones previously reported for CNFs, amino-functionalized CNCs and mesoporous carbon by Liu et al. (2021), Xu et al. (2021), and Aldawsari et al. (2017) under similar treatment conditions of dose (above 500 mg/L) and initial metal concentration (around 100 mg/L).
<Insert here>

Figure 3 . Experimental results and proposed model adjustment of Mn sorption capacities onto CNCs, CNFs-5 and CNFs-15 under different sorbent doses (10 to 1000 mg/L). Initial Mn(II) concentration: 100 mg/L, CNCs and CNFs-5 sorption at pH: 2, CNFs-15 sorption at pH: 4, contact time: 180 min; room temperature.

Figure 4 . Maximum sorption capacities reached as a function of the sorbent dose for Co (initial concentration 300 mg/L), Mn, Cu and Ni (initial concentration 100 mg/L) onto CNCs, CNFs-5 and CNFs-15 (optimum sorbent doses: 10 mg/L); contact time 180 min; room temperature.

The high amounts of adsorbed metals found in this study are associated to two main factors: the large initial concentrations of the metal in the solutions, and the low sorbent doses where these capacities were reached, in most of the cases in the order of 10 mg/L. The NCs are applied as suspensions, whose content in water is 99% or higher, which are the solid contents required for their synthesis. Therefore, the addition of high amount of sorbent means the addition of large volumes of liquid that implies the dilution of the metals in the solution. To operate always under high driving forces between the bulk and the surface, thus, reaching large sorbent capacities, it is key to apply lower NCs doses and work always in the highest possible concentration of metal, which allows an easy recovery of the spent celluloses. The easier recovery is caused by the larger density after the attachment of the metals. This provokes that the spent sorbent can be simply separated by centrifugation. In this way, highly efficient use of the material is achieved in terms of amount of metal sorbed per unit of sorbent mass, which enhances the overall operation performance. This can be confirmed by the sorption capacities over 1 g/g and above seen in Figure 4 . Such values were reached by the CNCs in the treatment of Co(II) (3.18 g/g), Mn(II) (1.01 g/g) and Cu(II) (2.48 g/g), by the CNFs-5 in the Co(II) (1.36 g/g) and Cu(II) (2.64 g/g) treatment, and by the CNF-15 in the Co(II) (1.26 g/g), Mn(II) (1.35 g/g) and
Cu(II) (2.76 g/g). These results are the basis for a further experimental trial using MSB strategy, operating multiple steps under low dose each step.

The recovery of Ni(II) was considerably lower than the recovery of the other metals. Such results are in line with the ones achieved by Hokkanen et al. (2013). These authors applied succinic anhydride modified mercerized NC for the removal of heavy metals including (Zn(II), Ni(II), Cu(II), Co(II), and Cd(II)). Their results show a lower Ni(II) adsorption capacity (0.7 mmol/g instead of values over 1.3 mmol/g for the other metals). Authors have correlated these values to the highest primary hydration number (N) and the lowest hydration radius ($R_H$) of Ni(II) among the studied metals. The reason is that the higher the $N/R_H$ ratio value, the lower the charge interaction between the metal ions and the amorphous surfaces which are found in the cellulosic matrix. According to the experimental results reported by Trivedi and Axe (Trivedi and Axe, 2001), Ni(II) shows the highest $N/R_H$ ratio between the studied metals in this work ($Ni(II) > Cu(II) \approx Co(II) > Mn(II)$). This explains the smaller removal of Ni(II) compared to the other tested metals.

### 3.2.3. Effect of the initial metal concentration on the metal sorption. Isotherm analysis

The effect of the initial concentration of Co(II), Mn(II), Cu(II) and Ni(II) on the sorption process onto CNCs, CNFs-5 and CNFs-15 was analyzed. The experimental data are shown on Figure 5.

It is observed a trend of the sorption capacities when the initial metal concentrations increased up to 1000 mg/L. The shape of the curves can be associated with the occurrence of two different steps. The first involves a sharp increase of the sorption capacity at very low concentrations, followed by a continuous decrease of the slope, which is appreciated in most cases at doses below 200 mg/L. After that, a second increase of the slope can be seen in most of the cases between 200 and 400 mg/L. This behavior is much clear in the experimental data of CNFs-15 and CNFs-5. The separation of these two mechanisms
could be better appreciated while going reverse in the Irving-Williams series of the metals (Cu,
Ni, Co and Mn). This can be confirmed by the clear split into two mechanisms of the Mn(II)
sorption isotherms with all the materials, while the Cu(II) and Ni(II) isotherm sorption data onto
CNCs evolved linearly. Therefore, it is assumed a first sorption step as the ruling mechanism
at low concentrations followed by a second surface precipitation mechanism at higher metal
contents. Although no precipitation was expected for the presently investigated conditions
and metal ions, according to aqueous speciation calculation (Shen et al., 2017), particle surfaces
are known to serve as template for polymeric species formation and surface precipitation (Shen
et al., 2017). For instance, this trend was previously mentioned in the use of other nanomaterials
by Goberna-Ferrón et al. (2021) and Kanematsu et al. (2018), which depicted sorption and
surface precipitation as the main interaction mechanism between Si and magnetite
nanoparticles surface (Goberna-Ferrón et al., 2021). It was also observed by Ratié et al. (2023)
in case of the sorption of Ce(III) and its partial oxidation and surface precipitation of Ce(VI) onto
goethite. As performed in previously mentioned studies, the present sorption isotherms of each
material and metal were modeled using a combination of a Langmuir equation, to describe the
sorption behavior and the plateau at the lowest concentrations, and a Freundlich model for the
second surface precipitation (Kanematsu et al., 2018; Ratié et al., 2023). Analyzing the data for
CNCs, the tendency indicates a major relevance of Freundlich model for the less stable metals
(Mn(II) and Co(II)), according to the Irving-Williams series (Mn, Co, Ni, Cu), than for those with
higher stability (Ni(II) and Cu(II)). While the reduction of slope associated to Langmuir at high
concentrations could be observed for Mn(II) and Co(II), it was not detected for Ni(II) and Cu(II).
In the case of CNFs-5 and CNFs-15, the experimental data were well fitted by the combination
of both models.

<Insert here>
Figure 5. Experimental sorption capacities measured for the different initial concentrations of Mn(II), Co(II), Ni(II), and Cu(II) using CNCs, CNFs-5, and CNFs-15 as sorbents, and the adjustment to combined Langmuir and Freundlich models; sorbents dose: 500 mg/L; contact time: 180 min; room temperature.

As t he combination of Langmuir and Freundlich equations allows to predict the behavior of the analyzed metals under both low and high capacities (Kanematsu et al., 2018; Ratié et al., 2023), t hese models were successfully applied to all the experimental data obtained from the sorption of each metal with each NC . The obtained Langmuir and Freundlich constants and fitting parameters are summarized in Table 2. The R² coefficient is in most of the cases over 0.96 and the curves could efficiently predict the behavior of the sorbent applied to the metals, indicating that the proposed mechanism could successfully explain the interaction between CNCs and CNFs with Mn(II), Co(II), Ni(II) and Cu(II). For CNFs, k_L values increase following the Irving-Williams series from Mn to Ni, and reducing again in Cu, and k_F values show kind a reverse tendency. A high k_L value is associated to a steeper slope at low concentrations, which would mean a higher impact of sorption mechanism. This trend is better seen for Ni(II) than for the other metals. As well, Ni(II) was the only metal with n_F < 1 for CNFs, involving that Freundlich isotherm curve will also suffer an exponential rise, treating highly concentrated solutions.

<Insert here>

Table 2. Equation parameters of adjustment of equation 3 (combined Langmuir and Freundlich model) and correlation parameters of the combined mechanism to the fitted experimental data.
The sorption capacities for each metal were converted into equivalents/g and their values were compared with the maximum sorption capacity predicted by the first Langmuir adjustment (selected to predict the sorption part of the mechanism) and CD values of each sorbent, which would correspond to the maximum amount of active sites of each material (Figure 6 ). This multiple isotherm analysis, with a maximum capacity of sorption fixed by Langmuir and the description of surface precipitation was previously described by Ratié et al. (2023) for Ce(III)/Ce(IV) adsorbed and surface precipitated onto goethite, by Goberna-Ferrón et al. (2021) for Se(IV) adsorption and surface precipitation onto silica-coated magnetite, and Marsac et al. (2014) for Pu(IV) onto humic acid. Some noticeable differences can be seen between the modeled results from CNCs and from CNFs-5 and CNFs-15 through the combined Langmuir and Freundlich models. Firstly, the shape of the curves for CNCs (Figure 6.a) were mainly linear (Co, Ni and Cu), being the Mn curve the only one following a continuously decreasing slope trend. Such linear trend happened for the cases of the sum of Langmuir and Freundlich (Co) and when Freundlich was the most relevant model and Langmuir equation played a minor initial role (Ni and Cu). This result could be attributed to a major impact of surface precipitation for those metals rather than sorption onto the CNCs. In the case of the CNFs-5 and CNFs-15 (Figures 6.b) and c)), the plotted curves were similar in all the cases, following a decreasing slope shape until reaching a certain stable slope under high concentrations. This tendency is observed in all the cases except for the linear shape found for Cu onto CNFs-15, and for Ni onto CNFs-5, where a maximum capacity was reached. This fact reinforces the previously mentioned issue that the mechanism could be better appreciated for nanofibers and going reverse in the Irving-Williams series. The obtained results are in accordance with the observed sorption and surface precipitation mechanisms seen for Cu(II) onto cellulosic biomass by Schneider et al. (2001). The trends of the isotherm modeling changes following the Irving-Williams were also described for other processes, like the metal binding of the series of lanthanide rare earths onto microplastics shown by Blancho et al. (2022).
<Insert here>

Figure 6. Adjustment of combined Langmuir and Freundlich models to Co(II), Mn(II), Ni(II) and Cu(II) equilibrium sorption data onto a) CNCs, b) CNFs-5, and c) CNFs-15, and their corresponding cationic demand values and Langmuir's maximum sorption capacities.

Regarding the maximum sorption capacities predicted by the Langmuir model for each material, the values calculated for CNFs-5 and CNFs-15 from the experimental data (Figures 5.b) and c)) were similar to the quantity of active sites (depicted by the CD). This is a great indicator of the good performance of the combined Langmuir and Freundlich model prediction. By contrast, the $q_{max}$ of Langmuir adjustment for CNCs is much higher than the number of active sites in the sorbent. As explained before, the Freundlich model adjusted for the surface precipitation mechanism played a major role in the explanation of the recovery of the metals. Thus, the $q_{max}$ estimation for this material would be less representative than in the case of the CNFs modeling. This could be attributed as the main reason for the difference between the predicted maximum Langmuir capacity and the measured CD for CNCs.

### 3.2.4. Evaluation of operation methodology: Single-step batch and Multi-step batch

The exponential rise of the sorption capacity achieved under extremely low concentrations of sorbent indicates that adding small amounts of NC in sequential operations could maximize the metal sorbed per sorbent gram. To confirm this hypothesis, a multibatch sorption test was performed with Mn(II) under optimal pH conditions. SSB was applied by adding 500 mg/L of each nanomaterial for 180 min as control test and, five consecutive MSB sorption tests of 100 mg/L
of NC dose for 36 min were performed in parallel. The Mn(II) sorption capacities on the surface of CNCs, CNFs-5 and CNFs-15 in SSB and MSB experiments are presented in Figure 7.

<Insert here>

Figure 7. Sorption capacities of Mn(II) onto CNCs, CNFs-5 and CNFs-15 by applying SSB and MSB (up to 5 steps) methodologies. Initial Mn(II) concentration: 5 g/L; sorbent dose: SSB: 500 mg/L, MSB: 100 mg/L each batch; contact time: SSB: 180 min, MSB: 36 min each batch; room temperature.

Figure 7 shows a similar sorption capacity under SSB conditions for each material, between 442 mg/g and 536 mg/g for CNFs-5 and CNFs-15, respectively. The trend changes noticeably when the MSB is applied, showing as high as a 4-fold rise in the sorption capacity in the case of CNCs, and an 18-fold for CNFs-5 and CNFs-15 only in the first stage. Overall, the total capacity of MSB was enhanced up to 6.19 g/g, 14.09 g/g and 13.29 g/g for CNCs, CNFs-5 and CNFs-15, respectively.

Nevertheless, while analyzing the MSB results, it is important to remark that in the case of CNFs-5 and CNFs-15, the total Mn(II) recovery in the first stage was 57% and 73% of the overall, meaning that a large recovery would be obtained in a single stage at low dose without further additional steps. In the case of CNCs, the sum of the subsequent steps leads to a total of 69%, so the application of additional batches after the first one would enhance the final total metal recovery.

In the Mn(II) sorption experiments, the application of MSB operation mode enhanced several times the retained metal onto the surface of the materials. The values obtained were 6 g/g for CNCs and 13-14 g/g onto CNFs, that means more than the double of the single step. As a
comparison, the MnO₂-coated CNFs hybrid material synthesized to treat dyes in the study of Wang et al. (2014) showed an enrichment ratio equivalent to 8.3 g of MnO₂ per gram of dried NC following a treatment using permanganate as the base of manganese specie. Thus, the proposed methodology to recover metals from BML shows better performance than specific synthetic routes to produce metal and NC composite materials. The most relevant results of the present study and the optimized conditions to reach them are presented in Table S3 of the supplementary materials. To facilitate the comparison between these results and the ones reached by other researchers, the maximum metal capacities and optimized conditions of other bibliographic references were added to Table S3.

## 4. CONCLUSIONS

The applicability of nanocellulosic materials for the recovery of Co(II), Mn(II), Cu(II) and Ni(II) from highly concentrated solutions has been demonstrated. The high number of active charge sites indicates a strong affinity between metallic cations and the nanocellulosic materials. Acidic conditions can be used to recover the tested metals. pH values below 3 were the most efficient to recover Mn(II), Co(II) and Cu(II) with CNCs and CNFs-5, while pH over 3 was better to recover Ni(II). Co(II), Cu(II) and Mn(II) can be recovered in levels over 1 g/g with very low dosages (10g/L) of CNCs or CNFs. Isotherm experiments show a double isotherm curve shape when the metal initial concentration increases. The combination of firstly Langmuir model and subsequently Freundlich model predicted accurately a first sorption onto the material at low concentration followed by surface precipitation of the metals on the materials. MSB operation up to five consecutive batches at reduced contact times and low sorbent doses was more efficient than the common SSB. It is concluded that MSB operation leads to an increase of total sorption capacities of 420% in the case of CNCs, and of 18 times for CNFs-5 and CNFs-15. The very high recovery of metals
represents a significant progress with respect to the state of the art where recoveries are usually
one order of magnitude lower (dozens of mg/g).

The good performance of CNCs and CNFs under large metal concentrations will open new opportunities for the recovery of critical metals by treating lower volumes of concentrated solutions. The obtained results will be used as a base to establish new procedures to recover selectively critical metals from BML by applying MSB treatments with both types of NC at different pHs.
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# STATEMENTS & DECLARATIONS

## Ethical approval

This work does not contain any research involving humans or animals.

## Consent to participate

The work described has not been published before; that it is not under consideration for publication anywhere else; that written informed consent was obtained from individual or guardian participants.

## Consent for publication

The publication consent was obtained from all co-authors.

## Funding

The authors are grateful for the financial support by the Ministry of Science and Innovation of Spain [grant number PID2020-113850RB-C21 "CON-FUTURO"] as well as for the grant provide to Francisco de Borja OJEMBARRENA [grant number PRE2018-085034] for the stay at Institut de physique du Globe de Paris. In addition, Eric VAN HULLEBUSCH (Université Paris Cité and Institut de physique du Globe de Paris) thanks the Horizon 2020 ERA-MIN2 Project Bio-assisted Closed Loop Recycling for E-mobility Metals from waste PCBs and Li-Ion Batteries - BaCLEM [Grant number Project ANR-20-MIN2-0002, 2021-2024] for financial support.

## Author Contributions
Francisco de Borja OJEMBARRENA: Conceptualization, Data curation, Formal analysis, Investigation, Software, Methodology, Writing, Validation – original draft. Eric VAN HULLEBUSCH: Methodology, Resources, Writing- review & editing. Rémi MARSAC: Software, Data curation. Noemi MERAYO: Conceptualization, Methodology, Supervision, Writing- review & editing. Angeles BLANCO: Conceptualization, Methodology, Resources, Supervision, Writing- review & editing. Carlos NEGRO: Conceptualization, Funding acquisition, Methodology, Supervision.

**Competing Interests**

The authors have no relevant financial or non-financial interests to disclose.

**Data Availability**

The authors declare that the data supporting the findings of this study are included in the manuscript and its supplementary material.
Table captions

Table 1. Operating conditions applied during the batch test experiments for metal sorption using
NC .

Table 2. Physical-chemical parameters of the synthetized NC products.

Table 3 . Equation parameters of adjustment of equation 3 (combined Langmuir and Freundlich model) and correlation parameters of the combined mechanism to the fitted experimental data.
<table><caption>Table 1. Operating conditions applied during the batch test experiments for metal sorption using NC.</caption><thead><tr><th rowspan="2">Studied operating condition</th><th rowspan="2">Interval of operation</th><th colspan="4">Fixed conditions</th></tr><tr><th>Initial metal content (mg/L)</th><th>pH</th><th>Sorbent dose (mg/L)</th><th>Contact time (min)</th></tr></thead><tbody><tr><td>pH</td><td>1-6</td><td>Co(II): 250<br>Mn(II): 100</td><td>-</td><td>500</td><td>180</td></tr><tr><td>Sorbent dose (mg dried NC /L)</td><td>10-1000</td><td>Ni(II) and Cu(II): 80<br>Co(II): 300<br>Mn(II), Cu(II) and Ni(II): 100</td><td>Previously optimized pH</td><td>-</td><td>180</td></tr><tr><td>Initial metal concentration (mg metal/L)</td><td>1-1000</td><td>-</td><td>Previously optimized pH</td><td>500</td><td>180</td></tr><tr><td>Multi-Step Batch</td><td>5 batches</td><td>Mn(II): 5000</td><td>Previously optimized pH</td><td>100 mg/L per batch</td><td>36 min/batch</td></tr></tbody></table>

All the mentioned studies were performed at 25 mL of volume and room temperature (around 15 °C)
<table><caption>Table 2. Physical-chemical parameters of the synthetized NC products.</caption><thead><tr><th>Analyzed parameters (units)</th><th>CNCs</th><th>CNFs-5</th><th>CNFs-15</th></tr></thead><tbody><tr><td>Consistency (g dried material)</td><td>0.429 ± 0.012</td><td>1.102 ± 0.002</td><td>1.065 ± 0.012</td></tr><tr><td>60 °C /100 g)</td><td></td><td></td><td></td></tr><tr><td>DAC (%)</td><td>25.20 ± 0.49</td><td></td><td></td></tr><tr><td>Synthesis yield (%)</td><td>17.46 ± 0.61</td><td></td><td></td></tr><tr><td>CD (µeq/g)</td><td>403.0 ± 18.9</td><td>1548.8 ± 1.7</td><td>1719.1 ± 1.4</td></tr><tr><td>Carboxylic content (µmol/g)</td><td>-</td><td>1.54 ± 0.07</td><td>1.55 ± 0.03</td></tr><tr><td>T<sub>λ=600 nm</sub> (%)</td><td>-</td><td>90.36 ± 0.49</td><td>89.72 ± 0.45</td></tr><tr><td>Width (nm)</td><td>22</td><td>15</td><td>12</td></tr><tr><td>Length (nm)</td><td>110</td><td>10000</td><td>500</td></tr><tr><td>Aspect ratio</td><td>5</td><td>670</td><td>40</td></tr></tbody></table>
<table><caption>Table 3. Equation parameters of adjustment of equation 3 (combined Langmuir and Freundlich model) and correlation parameters of the combined mechanism to the fitted experimental data</caption><thead><tr><th>Material</th><th>Parameter</th><th>Mn</th><th>Co</th><th>Ni</th><th>Cu</th></tr></thead><tbody><tr><td rowspan="7">CNCs</td><td>k<sub>Langmuir</sub> (L/mg)</td><td>6.71·10<sup>-3</sup></td><td>4.92·10<sup>-3</sup></td><td>2.75·10<sup>-5</sup></td><td>8.63·10<sup>-7</sup></td></tr><tr><td>q<sub>max,Langmuir</sub><br>(mg/g)</td><td>46.96</td><td>46.96</td><td>46.96</td><td>46.96</td></tr><tr><td>k<sub>Freundlich</sub></td><td>0.49</td><td>5.16·10<sup>-2</sup></td><td>0.26</td><td>0.53</td></tr><tr><td>n<sub>Freundlich</sub></td><td>1.24</td><td>0.81</td><td>1.00</td><td>1.08</td></tr><tr><td>R<sup>2</sup> combined</td><td>0.9719</td><td>0.9892</td><td>0.9988</td><td>0.9973</td></tr><tr><td>RSS combined</td><td>572.79</td><td>489.85</td><td>53.53</td><td>176.88</td></tr><tr><td>k<sub>Langmuir</sub> (L/mg)</td><td>2.32·10<sup>-3</sup></td><td>0.11</td><td>0.42</td><td>3.02·10<sup>-3</sup></td></tr><tr><td rowspan="7">CNFs-5</td><td>q<sub>max,Langmuir</sub><br>(mg/g)</td><td>35.97</td><td>35.97</td><td>35.97</td><td>35.97</td></tr><tr><td>k<sub>Freundlich</sub></td><td>0.23</td><td>0.57</td><td>3.79·10<sup>-2</sup></td><td>1.65</td></tr><tr><td>n<sub>Freundlich</sub></td><td>1.15</td><td>1.34</td><td>0.86</td><td>1.60</td></tr><tr><td>R<sup>2</sup> combined</td><td>0.9901</td><td>0.7931</td><td>0.9700</td><td>0.9883</td></tr><tr><td>RSS combined</td><td>116.61</td><td>2452</td><td>129.48</td><td>176.59</td></tr><tr><td>k<sub>Langmuir</sub> (L/mg)</td><td>1.61·10<sup>-2</sup></td><td>7.59·10<sup>-2</sup></td><td>0.11</td><td>1.00·10<sup>-6</sup></td></tr><tr><td>q<sub>max,Langmuir</sub><br>(mg/g)</td><td>41.47</td><td>41.47</td><td>41.47</td><td>41.47</td></tr><tr><td rowspan="7">CNFs-15</td><td>k<sub>Freundlich</sub></td><td>1.32</td><td>0.20</td><td>3.59·10<sup>-2</sup></td><td>0.49</td></tr><tr><td>n<sub>Freundlich</sub></td><td>1.51</td><td>1.13</td><td>0.80</td><td>1.16</td></tr><tr><td>R<sup>2</sup> combined</td><td>0.9650</td><td>0.9724</td><td>0.9952</td><td>0.9938</td></tr><tr><td>RSS combined</td><td>667.40</td><td>256.70</td><td>171.05</td><td>186.92</td></tr></tbody></table>
## Figures captions

Figure 1. Graphical scheme of MSB operation to treat Mn(II) solutions with nanocellulosic sorbents

Figures 2. a) Experimental results of sorption capacity of Co(II) onto CNCs, CNFs-5 and CNFs-15 at pH from 1 to 6. Initial Co(II) concentration: 250 mg/L; sorbent dose: 500 mg/L; contact time: 180 min; room temperature; and b) maximum sorbed amounts at optimized pHs for Co, Mn, Cu and Ni onto CNCs, CNFs-5 and CNFs-15. Initial metal concentration: Co(II): 250 mg/L, Mn(II): 100 mg/L, Ni(II) and Cu(II): 80 mg/L; sorbent dose: 500 mg/L; contact time: 180 min; room temperature.

Figure 3. Experimental results and proposed model adjustment of Mn sorption capacities onto CNCs, CNFs-5 and CNFs-15 under different sorbent doses (10 to 1000 mg/L). Initial Mn(II) concentration: 100 mg/L, CNCs and CNFs-5 sorption at pH: 2, CNFs-15 sorption at pH: 4, contact time: 180 min; room temperature.

Figure 4. Maximum sorption capacities reached as a function of the sorbent dose for Co (initial concentration 300 mg/L), Mn, Cu and Ni (initial concentration 100 mg/L) onto CNCs, CNFs-5 and CNFs-15 (optimum sorbent doses: 10 mg/L); contact time 180 min; room temperature.

Figure 5. Experimental sorption capacities measured for the different initial concentrations of Mn(II), Co(II), Ni(II), and Cu(II) using CNCs, CNFs-5, and CNFs-15 as sorbents, and the adjustment to combined Langmuir and Freundlich models; sorbent dose: 500 mg/L; contact time: 180 min; room temperature.

Figure 6. Adjustment of combined Langmuir and Freundlich models to Co(II), Mn(II), Ni(II) and Cu(II) equilibrium sorption data onto a) CNCs, b) CNFs-5, and c) CNFs-15, and their corresponding cationic demand values and Langmuir's maximum sorption capacities.
Figure 7. Sorption capacities of Mn(II) onto CNCs, CNFs-5 and CNFs-15 by applying SSB and MSB (up to 5 steps) methodologies. Initial Mn(II) concentration: 5 g/L; sorbent dose: SSB: 500 mg/L, MSB: 100 mg/L each batch; contact time: SSB: 180 min, MSB: 36 min each batch; room temperature.
<figure><img src="image_4.png" /><figcaption>Figure 1</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figures 2</figcaption></figure>
<figure><img src="image_6.png" /></figure>

b)
<figure><img src="image_7.png" /><figcaption>Figure 3</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>Figure 4</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>Figures 5</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>Cu CNFs-5 (pH 3)</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>Cu CNFs-15 (pH 5)</figcaption></figure>

<figure><img src="image_12.png" /></figure>
<figure><img src="image_13.png" /><figcaption>Figures 6</figcaption></figure>

<figure><img src="image_14.png" /></figure>
<figure><img src="image_15.png" /></figure>

c)
<figure><img src="image_16.png" /><figcaption>Figure 7</figcaption></figure>